If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

In this issue: Warp Sciences raises $215M to bring medicinal chemistry back onshore with chemists and robots — Pfizer deploys Edison's Kosmos across its R&D — Singapore's 450K-genome program goes dual-vendor — Formation Bio's $600M fund for stranded drugs — Hugging Face's Carbon-X reads DNA in plain English — China now hosts 45% of new drug trial starts, and more…

This issue is presented by: Molport

Molport brings together over 6 million in-stock screening compounds and building blocks from vetted suppliers worldwide, complemented by focused compound libraries tailored to specific research needs.

Explore chemical diversity, select individual compounds or customized sets, and simplify sourcing for your next screening or medicinal chemistry project.

Explore Molport’s compound catalog —>

Main Story

Much of the hands-on chemistry behind drug discovery, meaning the hundreds of small variations chemists make to tune a promising molecule, has long been outsourced to lower-cost labs overseas such as WuXi AppTec.

Warp Sciences, led by former OpenAI VP of Science Kevin Weil, wants to bring that work back to the US. It came out of stealth with $215M led by Lightspeed, at an $865M valuation, to run a US chemistry CRO that pairs experienced chemists with AI and robots, charging per compound delivered instead of per chemist-hour. The chemists come first, and their work becomes the data that gradually automates it.

The open question is whether the robots can be kept busy enough, and messy real-world chemistry tamed enough, to match offshore prices. C&EN explores the case, read the full piece.

The Brief

💰 Follow the Money

• Buying stranded drugs, not companies — New York-based Formation Bio launched a $600M Drug Development Accelerator Fund to acquire or in-license 10–15 Phase 1–2 programs over 3–5 years. Each program sits in its own entity and runs on Formation’s AI-native development platform.

  ---

• Basel-based Atlas Bio launched from stealth with a $10M seed led by Creandum, bringing total funding to $12.5M. Its foundation model, trained on ~2M human RNA readouts, simulates drug response across a virtual patient cohort.

  ---

• Robots for the AI wet lab — New York-based Opentrons raised a $40M Series E led by Avego, with BroadOak Capital Partners, to expand its lab robotics, software and data infrastructure for AI-driven experiments. The company says it has 11,000+ robots deployed in 80+ countries.

  ---

🤝 Deals & Alliances

• Edison Scientific will deploy its AI platform and Kosmos across Pfizer’s R&D, with access to Pfizer’s proprietary oncology, internal medicine and immunology data. No financial terms were disclosed.

  ---

• 10x Genomics launched Sentira Single Cell, a Claude-powered cloud agent that turns natural-language questions about Chromium data into reproducible analysis notebooks. Pricing is consumption-based, about 60 credits for a full analysis according to GEN

  ---

• UCB tapped Cradle to work on up to three antibody programs, in a partnership that could eventually extend across its pipeline; no value was disclosed.

  ---

• Singapore goes dual-vendor — Phase III of Singapore’s national genome program (400,000–450,000 more people) is split between Illumina and a Lucence-led consortium using Ultima’s UG200, with QIAGEN on sample prep. As Alex Dickinson noted, national population programs have been Illumina-only turf since the start of NGS.

  ---

• Cell biology meets molecule design — Dutch QurieGen and Rayca Precision partnered to feed QurieGen’s time-resolved single-cell multi-omics into Rayca’s AI-plus-physics molecular design.

  ---

🔬 Science to Watch

• Chatting with DNA — Hugging Face released Carbon-X, an open 14.8B model that reads DNA and English together and explains, for example, whether a mutation is likely harmful.

  ---

• Parse Biosciences and Nomic Bio announced Cascade, a licensable dataset that will pair 100M single-cell RNA profiles with 11,000+ secreted-protein profiles across 150,000+ cytokine and drug perturbations. GSK, Pfizer, Sanofi, Graph Therapeutics and Turbine are founding partners.

  ---

• The WashU-founded consortium C-BRAIN is building open Alzheimer’s models that learn directly from human brain data, and is exploring with NVIDIA how BioNeMo and MONAI could help train them.

  Leave a comment

We are happy to announce that our media partner, analytica Vietnam 2027, officially returns to Ho Chi Minh City!

We are pleased to announce the 9th edition of analytica Vietnam, taking place from 31 March to 2 April 2027 at the Saigon Exhibition and Convention Center (SECC), Ho Chi Minh City.

Part of the internationally renowned analytica brand led by Messe München, analytica Vietnam continues to serve as the region’s most established platform connecting global technology providers with Vietnam’s fast-growing laboratory and life sciences markets.

Why analytica Vietnam 2027

• Vietnam’s largest and ASEAN’s leading exhibition for laboratory and life sciences industries

• Live Lab – ASEAN’s only interactive laboratory experience, offering hands-on demonstrations and real-time innovation insights

• Expanded international pavilions showcasing global technologies and solutions

• Biotechnology Pavilion - a first in Vietnam, we aim to bring together industry leaders, researchers and decision-makers from across southeast Asia fostering a vibrant environment for collaboration, discovery, and growth.

• High-level Supporting Programme – conferences, exhibitor forums, workshop and tutorials

• Curated networking connecting manufacturers, distributors, laboratories, research institutions, and policymakers

Building on the strong momentum and record growth of recent editions, analytica Vietnam 2027 reinforces its role as a unique, hands-on platform for knowledge exchange, technology transfer, and business development across Southeast Asia.

Event Date: 31 March – 2 April 2027. Location: Hall A1 & A2 - Saigon Exhibition & Convention Center (SECC). Ho Chi Minh City, Vietnam

For exhibition or participation enquiries, please contact:
Email: analyticavietnam@mmiasia.com.sg
Whatsapp sms/call:  +65 8712 3652 (Singapore)

A Thing To Know This Week

Aging is the biggest risk factor for chronic disease, but regulators don’t recognize it as a disease. That means no formal indication, no accepted endpoints, and little reason for investors to fund “anti-aging” directly. There are three big ideas in aging research that could shift the therapeutic landscape anyway…

The first is GLP-1s as a possible first longevity drug class. Lilly’s Andrew Adams argued that their benefits across many organ systems, from cutting progression from prediabetes to diabetes by up to 94% to lowering cardiovascular events, already delay age-related disease, while stopping short of claiming they slow aging itself.

The second is proxy diseases. Dr. Zhavoronkov of Insilico Medicine and colleagues scored 13 diseases against the hallmarks of aging, and idiopathic pulmonary fibrosis came out on top. It progresses quickly and has well-defined endpoints, and Insilico’s TNIK inhibitor rentosertib is being developed for it.

The third is the microbiome. Scientists from Maxwell Biosciences argue that microbial imbalance speeds up aging, and they are developing stable synthetic mimics of the antimicrobial peptide LL-37 to counter it.

The full piece goes further. It covers why Novo Nordisk’s Lotte Bjerre Knudsen titled her ARDD talk “Semaglutide as a Proven Longevity Medicine,” which other geroprotectors are being tested in IPF, and why antibiotics may cut immunotherapy efficacy by up to 50%.

Read the full deep dive here: Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

Strategic Signals…

According to a Bloomberg Big Take, China now hosts 45% of new drug trial starts, and early-stage biotech is following

At the center of the piece by Amber Tong, Ashleigh Furlong and Fabienne Kinzelmann is InGel Therapeutics, a Boston startup working on a rare genetic eye disease. It was down to its last $1M and used it to fund a trial run by a Shanghai hospital, which has so far treated six patients. One of its investors estimates the same study would have cost $10–20M in the US.

The numbers behind the anecdote: China’s share of new innovative-drug trial starts went from under 5% in 2008 to 45% in 2025, according to Norstella data compiled with Bloomberg. Recruitment there runs two to five times faster, and costs are a fraction of Western levels.

🧬 What’s different now is who is going and why. China used to be where Western pharma licensed assets or added sites to late-stage trials. Increasingly, it’s where you get first human data, the go/no-go evidence that decides whether a seed-stage company can raise its next round. That changes what is fundable at the earliest stage.

Time will tell how durable this is. The piece itself raises safety and transparency concerns, US lawmakers are questioning how the FDA treats data from uninspected Chinese sites, and early results still have to hold up in multiregional trials.

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii and WTMB Team!

Read also:

Biotech IPOs Roar Back, With Nvidia-Backed Iambic Next in Line🔒

The $2.7B Question: How Do We Know If Isomorphic’s AI Works?

Big Pharma Is Betting On LLMs and Agents. What Would Count As Success?

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

In this issue: AstraZeneca joins a shared 1,152-GPU supercomputer in Sweden as pharma's compute race outpaces its published results — Anthropic's S-1 shows 9 of the 10 largest pharma companies are paying customers — insitro and AI Proteins sign deals worth $1.5B and $400M+ — Iambic prices its IPO while Recursion raises $200M — OpenAI buys Orchestra Bio and sets nearly 2,000 agents loose on a brain atlas — China drafts a ban on foreign takeovers of its CGT and siRNA platforms, and more…

This issue is presented by: Scala Biodesign

Antibodies by design: fix developability and affinity from the first design round

Live webinar · Wednesday, November 4, 2026 · 10:00 AM ET | 4:00 PM CET | 5:00 PM Israel time

Scala Biodesign combines AI with physics-based calculations to design antibody frameworks and antigen-binding regions, building on a decade of development across antibodies, vaccines, gene therapies and other biotherapeutics.

In this session, co-founders Dr. Ravit Netzer (CEO) and Dr. Adi Goldenzweig (CTO) draw on Scala’s work with top-10 pharma companies and biotechs to walk through experimental antibody case studies: the starting problem, the sequence changes designed, and how variants compare with the parent antibody across affinity and developability assays — which properties improved and which were retained.

You’ll learn how Scala’s design framework addresses:

• Stability: aggregation, self-association, polyreactivity and expression yields

• Activity: affinity and selectivity

• Program constraints: controlling the location and load of mutations

• Sequence diversity: antibodies with diverse sequences and V-gene combinations that meet binding and developability requirements, giving teams multiple candidates to advance

• Antigens: an antigen design module to improve the expression and stability of antigens and drug targets

Teams developing scFvs, VHHs, multispecifics or ADCs can use the session to assess which design approaches are worth testing in their own programs.

👉 Register for the webinar

Main Story

On October 15, AstraZeneca and a group of Swedish industrials, including Ericsson, Saab, SEB and Wallenberg Investments, launched Sferical One, a shared NVIDIA supercomputer reportedly built on 1,152 Blackwell Ultra GPUs for more than SEK 1 billion. AstraZeneca plans to use it for drug discovery.

The list goes on. Lilly’s LillyPod has been live since February with 1,016 GPUs, Roche now runs more than 3,500, BMS’s Vera Rubin system is due in Q1 2027, and Novo Nordisk and Zealand Pharma compute on Denmark’s Gefion. The software is following: Boltz will run its models inside BMS’s SuperPOD, trained on BMS data.

What’s still missing is the output. None of these systems has been tied to a published molecule or utilization figure yet, and each “most powerful” claim uses a different yardstick. Lilly’s chief AI officer Thomas Fuchs put it plainly: the bottleneck is biology.

More compute also means more candidates to check. Google’s new Deep Review agent has already verified more than 16,000 manuscripts at major ML conferences, and in drug discovery, Moe Alsumidaie argues the bottleneck has simply moved to clinical validation.

So what should count as a return on a SuperPOD?

🔒 From our members' deep dives: Big Pharma Is Betting On LLMs and Agents. What Would Count As Success? — the deals, and how to measure each kind of value.

The Brief

💰 Follow the Money

• A frontier lab files, with pharma on the customer list — Anthropic filed for a Nasdaq IPO under “ANT” today, and its S-1 shows 9 of the 10 largest Fortune 500 pharma companies each spent at least $100,000 with it in the year to Sept 30. The filing lists healthcare and life sciences first among its new markets and names Claude Science as a core product; first-half 2026 revenue was $16.3B, the FT reported.

• AI drug discovery tests the public markets — Iambic priced its IPO at $16 a share for $150M on Oct 15, the same day Recursion raised $200M in a follow-on at $3.25 that it says funds operations into 2029. We track the public cohort in 13 AI Drug Discovery Companies to Watch in 2026.

• Pricing a platform before the clinic — Isomorphic Labs is reportedly in early talks to raise at a $40B–$50B valuation, Bloomberg reported, after a $2.1B Series B in May.

• Robots instead of CROs — Warp Sciences, co-founded by former OpenAI science lead Kevin Weil, launched with $215M led by Lightspeed to automate molecule making and testing in the US, work now often sent to Chinese CROs.

• Engineered working dogs — Colossal-backed Warhound raised a $200M seed at a $1.2B valuation to clone and gene-edit military dogs equipped with Anduril gear; first births are expected in early 2027.

• Chemistry-native AI — Oakland-based Albert Invent raised a $55M Series B led by TCV for its R&D platform, used by BASF, Henkel and Clorox to retrieve lab knowledge and design formulations.

• Patient data from four countries — BioStack raised a $9.5M seed co-led by Peak XV and Afore Capital to build de-identified longitudinal datasets from a claimed 100M+ records in the US, India, Brazil and Argentina.

  ---

🤝 Deals & Alliances

• Cardiometabolic targets for the Virtual Human — AstraZeneca will pay insitro $40M upfront and up to ~$1.46B in milestones, plus royalties, to take targets in MASH and cardiomyopathies to development candidate.

• Miniproteins by design — Astellas licensed AI Proteins’ de novo miniprotein platform in a deal worth more than $400M including milestones.

• A milestone and a trial predictor — Insilico hit the first milestone in its $888M oncology deal with Servier and launched inClinico Agent, which reportedly predicts trial efficacy with an AUROC of 0.828 (medRxiv preprint).

• Open models, inside the firewall — Boltz will deploy Boltz Lab inside BMS’s NVIDIA SuperPOD and co-develop custom models on BMS data; no terms disclosed.

• Exploratory, for now — Oracle and AstraZeneca signed a non-binding agreement to explore AI and real-world data for trial recruitment and evidence generation.

  Share

  ---

🔬 Science to Watch

• Genetics without the lab test — Sooknah, Xu et al. (medRxiv preprint, Apr 14, 2026) at Calico found disease genes directly from AI embeddings of MRI scans, linking a CASP9 variant to kidney failure and an ADGRG6 variant to asthma and COPD, with no blood or breathing tests.

• Mapping the nervous system — Precision Neuroscience released a neural atlas from 70 patients and more than 180 hours of recordings with its thin-film brain interface.

• Dodo, 95% done — Colossal says its dodo genome is about 95% complete, with ~2,300 candidate gene-editing targets for beak shape still being validated in its closest living relative, the Nicobar pigeon.

• Your brain as a password — Paris-based Yneuro, backed by Bpifrance, is building Neuro ID, software that continuously verifies identity from EEG signals in earbuds and smart glasses.

• Banking immune cells — Cellino’s Reservoir now cryopreserves people’s immune cells for $5,000 plus $270 a year, betting on future personal cell therapies.

  ---

📋 From the Regulators

• China moves to keep its platforms at home — China’s Ministry of Commerce proposed banning foreign acquisition of proprietary cell and gene therapy and siRNA platforms; out-licensing and CRO/CDMO services are excluded, and comments are due Nov 15.

  Leave a comment

A Thing To Know This Week

OpenAI goes full “bio” mode

Nearly 2,000 GPT-Rosalind agents, built by PerturbAI and OpenAI with Scripps Research, analyzed a whole-brain CRISPR atlas of the mouse in 32 minutes — work estimated to take humans months. In blinded comparisons, experts preferred the agents’ interpretations 75% of the time (bioRxiv preprint).

A day earlier, OpenAI acquired Orchestra Bio, whose agents monitor drug programs and flag problems such as a failed manufacturing batch, and folded it into its Rosalind life sciences offering. Put together, OpenAI is building agents for both ends of the pipeline: finding targets upstream and running programs downstream.

Xaira, too, introduced X-Scientist this week, reporting hit rates on par with human-curated picks in a fraction of the time.

Usual caveats apply: preprints, self-reported results, and expert preference is just that — preference. Marketing play or a serious push into biotech?

Strategic Signals…

According to Arjun Murthy of Maven Bio, every bispecific ADC at Phase 3 or later was discovered in China

His team analyzed 243 bispecific and biparatopic ADC programs across 114 developers. Most are still preclinical, but China originated 46 of the 53 clinical programs and all four at Phase 3 or later, while six Western-owned clinical programs have been discontinued since 2018.

The timing matters: several of those Chinese assets, including BMS-partnered iza-bren and CTTQ’s TQB2102, reported Phase 3 data at ESMO in Madrid this week. And 36 of 46 Chinese clinical assets still have no disclosed ex-China deal; those that did, like iza-bren ($800M upfront from BMS) and JSKN016 ($125M upfront from Pathos AI), have set the price.

🧬 Time will tell, but with targets and payloads crowding (23 EGFR × MET programs, and topoisomerase I payloads in at least 77%), Murthy expects follow-on programs to compete on tolerability, dosing and patient selection rather than novelty. Combined with China’s draft limits on selling its platforms, the West’s role looks increasingly like licensing the assets, not owning where they come from.

Want the deep dives? Members get the full analysis of every deep dive plus our complete archive. Become a member →

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii and WTMB Team!

👉 Register for the webinar

Read also:

Biotech IPOs Roar Back, With Nvidia-Backed Iambic Next in Line🔒

The $2.7B Question: How Do We Know If Isomorphic’s AI Works?

Big Pharma Is Betting On LLMs and Agents. What Would Count As Success?

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

In this issue: a new review names "TechBio 3.0" just as Alex Zhavoronkov says prompt-to-drug may be here soon for low-to-moderate novelty — Schrödinger's Bunsen now launches ~80% of the company's own modeling jobs — ByteDance spins out Anew Labs at a RMB 10B valuation — Tempus becomes part of the manufacturing chain for Merck and Moderna's personalized cancer vaccine — a scaled-back version of a Nobel-winning reprogramming trick shows first signs in human eyes, and more…

Main Story

A couple of days ago, Alex Zhavoronkov, founder and CEO of Insilico Medicine, posted that he thinks we are approaching a “pharmaceutical singularity”, and that “prompt to drug is now possible in low-moderate novelty space.” The real moat now, he added, is operational efficiency and the ability to deliver.

It is a strong statement, I’ll come back to it.

Now, last week, Krish Ramadurai and Abhirup Banerjee published a review in npj Drug Discovery that gives the underlying trend a name: TechBio 3.0. They split the last decade into three generations:

• TechBio 1.0 (≈2015–2019), prediction: ML models ranking and filtering compounds inside conventional pipelines.

• TechBio 2.0 (≈2020–2023), acceleration: generative models and end-to-end platforms, with Insilico’s IPF program going from target to preclinical candidate in about 18 months versus the usual 3–5 years.

• TechBio 3.0, the closed loop: multimodal models, generative design with toxicity and PK constraints built into the objective rather than filtered afterwards, and automated experiments feeding structured data straight back into the models.

The authors are fairly sober about the evidence. As of mid-2026, no AI-designed small molecule has FDA marketing approval. Rentosertib remains the most advanced proof point, with Phase IIa data in 71 IPF patients (a mean +98.4 mL in forced vital capacity at the top dose) and Phase III expected in the second half of 2026. They also cite Iambic, which filed for its Nasdaq IPO a few weeks ago, as a working example of weekly design-make-test cycles.

It is interesting how much of the news lately is about the loop rather than the models:

• Lilly’s TuneLab released a nanobody developability model trained on 2,500+ VHHs that BigHat characterized in six one-week design rounds.

• AstraZeneca and Carterra are co-building hardware and software to produce standardized binding data for lab-in-the-loop biologics discovery.

• PacBio and TychoBio are sequencing full-length transcriptomes from 10,000+ samples to learn how antisense oligonucleotides behave across the transcriptome.

None of these is a model launch, but rather they are about producing data a model can trust (details in The Brief below).

The execution layer is moving too. Over the weekend, I published my interview with Robert Abel, CSO of Schrödinger, about Bunsen, the company’s agentic co-scientist. One number is especially telling: roughly 80% of the computational modeling jobs on Schrödinger’s own HPC (e.g. free energy calculations, molecular dynamics, quantum calculations, etc.) are now run by Bunsen. Importantly, the LLM is not predicting molecular properties itself. It chooses among validated physics methods and runs them, after a scientist has reviewed the work plan.

That brings me back to Alex’s qualifier. Abel makes a related point from the other side: ML accuracy generally worsens the further you move from the training data, and real discovery often happens exactly there — novel scaffolds, new resistance mutations, targets with few known ligands. His answer is physics as a data generator. A typical lead-optimization project might synthesize fewer than 1,000 designed molecules in a year, while atomistic simulations can produce several thousand data points in an evening.

So “prompt to drug in low-to-moderate novelty space” and “closed loops that work where data exists” may be describing the same frontier. The open question is high novelty, i.e., first-in-class targets, new modalities, where the loop has the least data to close on. The npj authors list it among the unresolved problems: predictors need applicability-domain checks before molecules go to synthesis. The authors are warning that a model can give a precise-looking score for a molecule it effectively knows nothing about. Their fix is to keep the model’s confidence level attached to each prediction at every step, so a shaky guess is not used for the final choice.

All in all, TechBio 3.0 may turn out to be less about a smarter model and more about who owns the data factory and the execution layer.

Read the full interview with Robert Abel here: https://www.biopharmatrend.com/interviews/interview-with-robert-abel-from-schrodinger/

🧠 Neurotech, nine months later

In January, we argued that 2025 was the year neurotech started designing around use cases: speech restoration as a defined clinical endpoint, noninvasive BCIs scaling on large datasets, organoids turning into standardized tools. This week offers two small tests of that thesis.

Silicon Valley-based Bridge Neurotech emerged from stealth with $13.5M from General Catalyst, reMind Capital, Sunflower Capital, Scott Sandell and others, to read brain activity through the skull with functional ultrasound imaging (fUSI) and AI decoding, with no surgery or implant. Founder Will Biederman designed the neural interface chip later used in Neuralink’s first implants during his Berkeley PhD, and co-founded Forest Neurotech. Bridge has licensed Butterfly Network’s Ultrasound-on-Chip through Butterfly Embedded and is enrolling its first research study in Redwood City.

What held: the pitch is a concrete one (a wearable, non-surgical interface, starting with a research study), not a general mind-reading device. What’s still open is what the company itself names as its two hurdles: getting reliable signal through the skull, and decoders that generalize across people. That’s the same cross-subject problem Tether Evo’s papers attacked in #85.

On brain delivery, WhiteLab Genomics’ AI-designed AAV capsids showed 50x higher brain DNA enrichment than AAV9 in IV-dosed mice (more in Follow the Money). It’s still mouse data, and larger-animal results will be the real check.

🔒 From our members’ deep dives: 2025 Neurotech Review: BCIs, Brain Delivery, Organoids and Neuro-AI Move Closer to Clinic — more than $1.3B in tracked financings led by Neuralink’s $650M round, the clinical proof points, and the forward signals we flagged for 2026. Worth rereading against what this year has delivered. Read it as a member →

The Brief

💰 Follow the Money

• Big tech spins out AI pharma — ByteDance’s Anew Labs raised a $290M angel round at a reported ~$1.5B valuation. It has four preclinical assets, led by an oral IL-17A/F inhibitor.

• mRNA made in cells — Sensible Biotechnologies raised $47M, including up to $20M in EU and Slovak grants, to scale cell-based mRNA manufacturing as an alternative to in vitro transcription.

• AI-designed capsids — WhiteLab Genomics raised a $26M Series B led by AVP. Its AAV capsids reached the brain at 50x the level of AAV9 in mice, with no detectable liver signal.

• Ultrasound BCI out of stealth — Bridge Neurotech raised $13.5M from General Catalyst and others to read brain activity through the skull with ultrasound and AI, no implant needed.

• Watching immune cells kill — SpectaCell closed a seed round of EUR 6 million led by imec.xpand for a platform that tracks immunotherapy–target interactions in real time.

  ---

🤝 Deals & Alliances

• Sequencing as a manufacturing step — Tempus expanded its deal with Moderna and Merck to run sample logistics and the sequencing used to design each patient’s personalized cancer vaccine, V940.

• Data for Lilly’s models — Eli Lilly’s TuneLab released NanoLab, a nanobody developability model trained on 2,500+ VHHs characterized by BigHat Biosciences.

• Lab data built for AI — Carterra and AstraZeneca will co-build hardware and software to produce standardized binding data for lab-in-the-loop biologics discovery.

• Long-read RNA for model training — PacBio and TychoBio will sequence 10,000+ samples to train models predicting how antisense therapies for rare diseases act across the transcriptome.

• Data first, agents next — Novo Nordisk runs ~900 TB of data on Snowflake for nearly 40,000 users and plans to turn its commercial data into an agentic system, per a Snowflake case study.

  Share

  ---

🔬 Science to Watch

• Neurotech, nine months on. In January we argued that 2025 was when neurotech started building devices around specific clinical jobs, with noninvasive BCIs advancing mainly through AI trained on large brain datasets. This week, Bridge Neurotech’s ultrasound BCI round fits that picture but still faces the hard part, decoders that work across people. Separately, on getting therapies into the brain, WhiteLab’s AI-designed capsids look promising but so far only in mice (both in Follow the Money).

  🔒 From our members’ deep dives: 2025 Neurotech Review: BCIs, Brain Delivery, Organoids and Neuro-AI Move Closer to Clinic — more than $1.3B in tracked financings led by Neuralink’s $650M round, the clinical proof points, and the forward signals we flagged for 2026. Useful as a baseline for judging what 2026 has actually delivered. Read it as a member →

• Partial reprogramming reaches human eyes — Life Biosciences reported early Phase 1 data for its three-factor epigenetic reprogramming therapy in glaucoma: no treatment-related side effects so far, and visual-field gains in two of three patients at eight weeks. It is a conference presentation in three people, so very early.

  ---

💁‍♀️ People 💁

• Miriam González, a software engineer in Spain with a rare metastatic breast cancer, built AI agents that helped her doctors choose a biopsy site. Anthropic has since taken her project into its AI for Science program.

Share

A Think To Know This Week

The 2026 Nobel Prize in Medicine goes to optogenetics

On Oct 5, the Nobel Assembly at Karolinska Institutet awarded the 2026 Nobel Prize in Physiology or Medicine to Georg Nagel (University of Würzburg), Peter Hegemann (Humboldt University Berlin) and Karl Deisseroth (Stanford) for their work on light-gated ion channels and optogenetics. The three share 12 million Swedish kronor, about $1.2M.

The idea is that some green algae use light-sensitive proteins, called channelrhodopsins, to sense light and swim toward it. In the early 2000s, Nagel and Hegemann showed these proteins work as channels that open when light hits them, letting charged particles flow into the cell. In 2005, Deisseroth’s lab put one of them into mammalian neurons and showed that a flash of light could make those neurons fire on command.

That turned light into a switch for specific brain cells. Researchers can now genetically target one cell type, turn it on or off in milliseconds, and watch what changes in behavior. The Nobel committee noted that the method is now used in labs worldwide to study how the brain works.

Specifically, optogenetics became a standard tool for working out which circuits drive pain, addiction, movement or mood, which is the kind of evidence drug and neuromodulation programs build on. It has also reached patients: in 2021, a man blinded by retinitis pigmentosa partially regained sight after an optogenetic gene therapy, reported in Nature Medicine.

Strategic Signals…

According to Padraig McDonnell, President and CEO of Agilent, digital pathology is becoming the foundation for pathology data generation, analysis and application

Agilent agreed to acquire Proscia in an all-cash deal: $240M at closing plus up to $30M in performance milestones. Proscia’s vendor-agnostic software serves as a central operating layer for digital pathology. It connects scanners, lab information systems, image analysis apps, AI tools, people and data for more than 4,000 labs, hospitals and clinics and 16 of the top 20 pharma companies. It has trailing-twelve-month revenue above $18M and FDA 510(k) clearance for primary diagnosis.

Time will tell, but an instruments-and-reagents company paying roughly 13x trailing revenue (about 15x if the milestones are paid) for a software layer says where it thinks value is moving. Agilent already sells the stains, and it closed the $950M Biocare acquisition in June. What it didn’t own, despite distributing Proscia’s software since 2022, was the layer between the slide and the model. McDonnell says the deal establishes an Agilent platform connecting data generation with AI-based interpretation, from biomarker research through routine clinical use.

Members get the full access to every deep dive plus our complete archive. Become a member →

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii and WTMB Team!

Read also:

Biotech IPOs Roar Back, With Nvidia-Backed Iambic Next in Line🔒

The $2.7B Question: How Do We Know If Isomorphic’s AI Works?

Big Pharma Is Betting On LLMs and Agents. What Would Count As Success?

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

In this issue: OpenAI's fund leads Biossil to unicorn status on a bet that failed drugs failed the wrong patients — Anthropic says it won't take its own programs into the clinic — Enveda, Anew Labs, Varda and Precision each raise $250M+ — Roche lays out a path to autonomous labs — optogenetics wins the Nobel — Xaira finally shows its antibody pipeline — a microbe built to live on Mars, and more…

Main Story

In April, Toronto-based Biossil emerged from stealth with $70M and a plan that sounded a bit contrarian for an AI company: instead of designing new molecules, buy or license the ones that failed in their own clinical trials.

About five months later, Biossil raised another $153M (C$216M) at a $1B valuation, this time led by the OpenAI Startup Fund, with Founders Fund, Quiet Capital, Modern Capital, Golden Ventures, Panache Ventures, Duke University’s endowment and the Abu Dhabi Investment Council participating. The money goes to expanding clinical development capacity and acquiring more drug candidates, with programs spanning sickle cell disease, idiopathic pulmonary fibrosis, glioblastoma, breast cancer and Alzheimer’s disease.

The idea is not classic drug repurposing. Repurposing looks for a new disease for an old molecule. Biossil’s approach is closer to asking whether the drug actually worked — just not for everyone in the trial. If an efficacy signal existed in a more precisely defined patient group, it may have been diluted across a broad trial population.

That reframes a familiar number. Pharma’s 90%+ clinical failure rate is usually read as a story about how hard biology is. Part of it, though, may be a story about the purely matchmaking side of things, and that is exactly the kind of problem where AI on rich clinical and molecular data could make a difference.

CEO Anthony Mouchantaf argues that AI-generated biomedical insights still have to be translated into the physical world: “That requires dedicated infrastructure capable of integrating AI and medicine together from discovery through development and into the clinic,” adding, “We’re building that infrastructure in the United States and Canada.”

The round also fits OpenAI’s broader push into life sciences. In April, it launched GPT-Rosalind, a reasoning model for biology, drug discovery and translational medicine, released as a research preview through its trusted access program with Amgen, Moderna, the Allen Institute and Thermo Fisher Scientific named as partners, on top of an earlier-announced drug discovery partnership with Novo Nordisk.

Biossil is not alone, though. We mapped the “drug rescue” category in our members’ deep dive — who else is working this angle (Lantern Pharma, Pathos AI, BPGbio, etc), what the Roivant precedent teaches, and the approaches that didn’t work.

🔒 Read the full deep dive → become a member — members get new deep dives plus the full archive.

The Brief

💰 Follow the Money

• Nature’s chemistry, AI-ranked — Enveda raised a $311M Series E at a $2B valuation, led by Catalio Capital Management (total raised: $845M+). Proceeds go to three clinical programs, including one for severe skin conditions and one for maintaining weight loss after stopping GLP-1s.

• ByteDance’s AI biotech prices in — Anew Labs raised $290M in its first external round at a reported $1.5B valuation, led by HSG, IDG Capital, GL-C Ventures/Hillhouse and 5Y Capital; ByteDance reportedly keeps 56%. Its work spans protein structure prediction, molecular design and antibodies, and its research includes small-molecule IL-17 inhibitors.

• Drug manufacturing in orbit — Varda raised a $251M Series D co-led by Lux Capital and Natural Capital at a $1.6B valuation. It has completed six capsule reentries and booked 28 launches for 2027–2029.

• BCI money keeps concentrating — Precision Neuroscience closed a $250M Series D co-led by Pershing Square and the Ackman Oxman Institute ($430M total). Its Layer 7 interface has been used in 100+ procedures across 18 institutions.

• From models to medicines — Basecamp Research raised $140M from investors including S32, NVIDIA and Menlo’s Anthology Fund to launch a pipeline of AI-designed therapeutics, starting with medicines that “reprogram the body to repair itself.”

• An AI-designed ADC enters the clinic — BigHat Biosciences raised a $75M Series C co-led by DFJ Growth and Premji Invest, mainly for BHB810, a CDH17-directed ADC for GI cancers that dosed its first Phase 1 patient in September.

  ---

🤝 Deals & Alliances

• Another Roche-group bet on AI discovery — Earendil Labs and Genentech signed a $1.5B research collaboration on cancer therapies, following Earendil’s autoimmune licensing deals with Sanofi.

• Paying for delivery, not the drug — Novartis paid $125M for Sironax’s platform for moving large molecules across the blood-brain barrier, its latest BBB deal after BioArctic and SciNeuro.

• Roche plans for lab autonomy — At Pharma Day, Roche laid out a path to autonomous labs, naming Medra and Anthropic as collaborators. It says 40% of recent pipeline decisions had a tracked AI contribution, and one program went from lead ID to clinical candidate in 18 months.

• AbbVie, argenx, Lundbeck and Takeda joined Ginkgo Datapoints and Apheris’s developability consortium: ~10,000 antibodies tested to one standard train a shared model that each member fine-tunes privately. First data due early 2027.

• AbbVie partnered with Valkai, starting in clinical sciences, as it sees pharma’s bottlenecks shifting from discovery to trials.

• Twist Bioscience joined Eli Lilly’s TuneLab as an antibody characterization data provider, after Ginkgo Datapoints.

• Boston-based Tremont AI emerged from stealth with Mass General Brigham-licensed foundation models and agents for drug safety pathology; funding not disclosed.

  Share

  ---

🔬 Science to Watch

• A Nobel for switching neurons with light — Karl Deisseroth, Peter Hegemann and Georg Nagel won the 2026 Nobel Prize in Physiology or Medicine for optogenetics, which uses light to turn specific brain cells on and off with millisecond precision.

• Antibodies “drug-ready from the start” — Xaira unveiled its X-Design platform and first programs in a company blog post: XA-1 (oncology) reached a progressable binder in seven weeks, and XA-4 hit a GPCR where conventional screens and llama immunization had failed.

• Pretraining on the brain — Neuralink pretrained each participant’s encoder on thousands of hours of their own unlabeled neural data (50,000+ hours across its trial), producing decoders that need far less recalibration — some users went from 10 minutes a day to 10 a week — and reports a BCI record of 11.32 bits per second.

• A microbe made for Mars — Pioneer Labs says it engineered a microbe that lives only on nutrients found on Mars and makes building materials.

• Measurement before models — Sculpta Bio says its new RNA barcoding and sequencing approach improves isoform capture at scale across bulk, single-cell and spatial applications.

  ---

💁‍♀️ People 💁

• Richard Bonneau left his role as Genentech’s global head of AI for drug discovery, Endpoints’ Andrew Dunn reported, the latest in a string of AI departures there including KyungHyun Cho, Stephen Ra and Nathan Frey; two sources cited tension with Aviv Regev, which Genentech denies.

• AMD will acquire World Labs, with Fei-Fei Li joining AMD as chief scientist.

• BrainGate founder John Donoghue joined Precision Neuroscience as Scientific Advisor.

Leave a comment

Strategic Signals…

According to Andrew Dunn’s report, Anthropic will not take its pipeline programs into human trials — and will not compete with its pharma customers

The quote, from Dunn’s report: “Anthropic does not plan to start human testing or Phase 1 trials for its pipeline programs, with Eric Kauderer-Abrams saying they will not compete with its pharma customers.”

Well, it is a big claim, and it changes a lot of assumptions about Anthropic’s current push into pharma, doesn’t it?

Time will tell, but it reads like a deliberate choice to stay a supplier rather than become a drug developer. And the customer list is growing fast: Bristol Myers Squibb put Claude in front of more than 30,000 employees earlier this year, Novo Nordisk signed its own deal (both covered in our last issue), and Roche named Anthropic as a collaborator on its path to autonomous labs at last week’s Pharma Day. If you are selling the reasoning layer into every big pharma’s R&D, owning clinical assets that compete with those same customers is an obvious conflict.

The open question is what “pipeline programs” Anthropic has at all, and what happens to them if they don’t go into humans — partnering or licensing would be the natural route, but the report, as quoted, doesn’t say.

A model retirement can be a regulatory event

Yujan Shrestha, MD, describes a problem few generative-AI device makers seem to plan for: Claude Sonnet 4 was released in May 2025 and retired in June 2026, about 13 months, shorter than most De Novo reviews, and one of his team’s API keys sent 10,236 failed requests in a single day afterwards.

Anthropic gives at least 60 days’ notice, less than the FDA’s 90-day goal for a Traditional 510(k), and swapping the model string can be a design change needing verification and validation. His advice: write model replacement into a PCCP (agreed with FDA in a Pre-Sub), keep a sequestered, labeled test set that can requalify a new model in days, and pin dated model snapshots rather than aliases that move on their own.

Members get the full access to every deep dive plus our complete archive. Become a member →

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii and WTMB Team!

Read also:

Biotech IPOs Roar Back, With Nvidia-Backed Iambic Next in Line🔒

The $2.7B Question: How Do We Know If Isomorphic’s AI Works?

Big Pharma Is Betting On LLMs and Agents. What Would Count As Success?

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

In this issue: pharma signs enterprise LLM deals at scale but it's unclear what would count as success — Iambic files for Nasdaq while Orbis lands Novo Nordisk for up to $1.4B — Mayo and Thermo Fisher start a million-biospecimen omics venture — Stanford turns papers into agents that talk to each other — the brain turns out to have grown from two separate roots all along, and more…

Main Story

Earlier this year, Bristol Myers Squibb put Claude in front of more than 30,000 employees, with a stated goal of halving the time from target selection to lead molecule.

Novo Nordisk's new Anthropic deal is the latest in the same trend. Besides, there is Merck that has committed up to $1 billion to Google Cloud, deploying Gemini Enterprise across R&D, manufacturing, and commercial. Amgen deployed ChatGPT Enterprise. Novo itself already had an OpenAI partnership from the spring... the list goes on.

Over the weekend, I finally completed my editorial article, Big Pharma Is Betting On LLMs and Agents. What Would Count As Success?, exploring this trend. The deals of this type carry two quite different value propositions, and the return on each needs quite different ways to measure.

One is the operational aspect: software engineering, regulatory and medical writing, knowledge retrieval, financial planning, etc. The evidence of potential value is real, albeit somewhat mixed, according to several studies outside pharma.

The other aspect is scientific reasoning, and it is probably harder to measure. While there are different studies and benchmarks, there is a notable new attempt at benchmarking, published in Cell, where authors assess the performance of several leading frontier models and their own smaller models against 17 aging biology tasks. Beyond presenting a framework for measuring AI in bio, this study also leads to a conclusion that the model size alone may not be the only key to what decides performance on biological data.

This is in line with a rapidly growing market of smaller but more specialized and more grounded AI platforms, also with LLM and agentic capabilities. Those include Schrödinger, OWKIN, Causaly, BenchSci, Insilico Medicine, Lantern Pharma, and others building on physics simulation, patient cohorts, or other curated knowledge graphs.

BenchSci, for example, makes the same argument from the demand side. Its EMET agentic environment was picked by argenx‘s scientists after their own competitive evaluation — which CEO Liran Belenzon called earning trust “at the bench, not in the boardroom”. argenx’s Tim Van Acker described it as “… a scientist in your pocket – always available, always reasoning across the evidence.”

Pharma is buying both camps, and in my article I list some deals and observations.

More important, though, is that an agentic layer on top of these tools lets people who were never trained on them take (some) part. For instance, Schrödinger‘s execs say Bunsen is for “drug hunters who are not computational chemists.”

Causaly, in its turn, is putting scientific reasoning into MS Teams for medical and commercial teams, allowing for more kinds of specialists in the same interdisciplinary work.

All in all, big pharma is increasingly betting on LLMs and agents, but the questions become more and more critical: how to assess success in a relevant way?

Read the full deep dive here: https://www.biopharmatrend.com/business-intelligence/big-pharma-is-betting-on-llms-and-agents-what-would-count-as-success/

Share

📅 I am excited to share that I’ll be attending BIOSPAIN 2026 as guest media.

BIOSPAIN is a massive event, recognized as the largest biotechnology conference organized by a national bioindustry association in Europe and one of the largest in the world for partnering and industry collaboration.

The Brief

💰 Follow the Money

• AI drug discovery goes public — San Diego-based Iambic filed for a Nasdaq IPO under "IAM," with J.P. Morgan, Jefferies, BofA Securities and Citigroup leading; share count and price are not yet set.

  Proceeds go mainly to IAM1363, an oral, brain-penetrant HER2 inhibitor in Phase 1 for HER2-altered solid tumors that the company claims is the only known HER2 TKI binding the inactive DFG-out conformation, with a registrational trial targeted "as early as 2027"; IAM217 (KIF18A) and IAM-C1 (CDK2/4) follow.

  The filing lands mid-rebound — after a trickle of listings in 2025, 2026 has already brought Aktis Oncology ($318M, January), Eikon Therapeutics ($381M, February), Generate:Biomedicines ($400M, the largest biotech IPO since 2024) and Kardigan ($400M upsized, June), with ADARx, TRexBio and Retension queued behind.

• AI for regulatory science — Paris-based Biolevate raises €30M Series A co-led by RAISE France and Orange Ventures, with MSD Global Health Innovation Fund, STATION F, EQT Ventures & Growth and Future4care participating, to scale its AI platform that turns scientific and regulatory knowledge into auditable, evidence-grade workflows for regulated life sciences. The company reports 20x ARR growth over 12 months and 12+ enterprise customers in production, including work with Sanofi, and will open a Boston office to drive US expansion.

• AI infrastructure for pharma — Mithrl raises a $20M Series A backed by Headline, AGI House and a group of pharma executives, to build custom AI infrastructure for biopharma R&D. The company is positioning at the middle layer of the AI-for-biology stack — proprietary data, biomedical world models and per-customer infrastructure that let each pharma team run frontier models on its own data and pipeline, rather than competing at the application layer.

• A verification layer for AI-generated biology — New York-based Polyphron raised a $20M seed to pair an automated "Tissue Foundry" growing human micro-tissue from stem cells with a "Tissue World Model" simulation layer, testing what AI-generated therapeutic hypotheses actually do in human biology. Former Google DeepMind Gemini researcher Vinh Q. Tran joins as co-founder and Chief AI Scientist.

  ---

🤝 Deals & Alliances

• Pre-symptomatic disease biology at scale — Mayo Clinic and Thermo Fisher launched Precure, LLC, a Mayo-majority JV generating multi-omics data from one million biospecimens linked to longitudinal clinical records, using Thermo Fisher's Olink Explore HT proteomics and Orbitrap mass spec. The aim is to detect molecular disease signals years before diagnosis; no deal value disclosed.

• Standardized data as the entry ticket — In a new agreement, Ginkgo Datapoints will supply small molecule ADME and antibody developability testing to companies in Lilly TuneLab, Eli Lilly's federated-learning platform that lets biotechs use models trained on hundreds of thousands of Lilly molecules without either side exposing proprietary data. Uniform assay protocols should help the shared models learn faster, and new members can submit Datapoints-generated data to unlock additional benefits; no financial terms disclosed.

• Oral macrocycles against injectable targets — Copenhagen-based Orbis Medicines signed a multi-target discovery and license deal with Novo Nordisk worth up to $1.4B in upfront and milestone payments plus tiered royalties, with Novo also taking an undisclosed equity stake. The collaboration will use Orbis's nGen platform, which pairs generative AI with automated chemistry, to develop orally bioavailable macrocycles for cardiometabolic targets.

  ---

🔬 Science to Watch

• The brain grows from two roots, not one — Jokhai, Dundes et al. (Nature Neuroscience, Sept 18, 2026) found that the thinking part of the brain and the brainstem that runs breathing and heartbeat come from two separate groups of cells that split apart at the very start of embryo development, rather than from one common pool as textbooks assume. Knowing this, the Stanford-led team finally grew human brainstem motor neurons in a dish — the cells lost in ALS and spinal muscular atrophy, which had resisted lab-growing until now.

• Papers that run themselves — Miao, Zou et al. (Nature, Sept 16, 2026) built Paper2Agent, which converts a manuscript's text, code and data into an MCP-based AI agent that reproduces the study and then answers questions or applies its methods to new datasets; 74 of 100 computational biology papers were successfully converted. In a paired demonstration, an AlphaGenome agent and an ADHD GWAS agent reportedly surfaced a previously unreported variant near MPHOSPH9 associated with ADHD risk.

  

  Share

  ---

📋 From the Regulators

• Pulling first-in-human trials back to the US — The FDA launched its Expedited IND Pilot on Sept 15 under HHS's Operation TrialBlazer, letting sponsors submit parts of an IND application as they're ready instead of waiting for the full package, with optional expert review partners and site setup running in parallel. Applications close Oct 30 and participants are picked Dec 18; the pilot prioritizes commercial INDs for novel Phase 1 trials of products with no prior clinical experience.

• A second AI organ model into FDA's qualification path — Absentia Labs’ co-founder and CEO, Farhan Khodaee, says the FDA accepted its AI model for predicting drug-induced cardiotoxicity into the ISTAND pathway, which qualifies novel drug development tools that don't fit existing FDA categories. It follows the company's Digital Liver model and forms the second organ system in a planned multi-organ AI safety platform aimed at replacing some animal toxicology work.

  ---

💁‍♀️ People 💁

• Cellular Intelligence, the rebranded Somite Therapeutics, building a universal virtual cell-signaling model to direct stem cells into therapeutic cell types, added Yann LeCun (AMI Labs, ex-Meta), Bob Langer (MIT, Moderna co-founder), Jens Nielsen (BioInnovation Institute) and Fabian Theis (Helmholtz Munich) to its Scientific Advisory Board, with Langer also joining the board as an observer.

Leave a comment

Strategic Signals…

According to Eric Lefkofsky, Founder/CEO at Tempus AI, healthcare will likely be the biggest beneficiary of AI

Time will tell, but it seems like Tempus AI is trying to position itself as an infrastructure player in the AI-centric future of life sciences already today. From recent notable updates, for example, the company is building a research platform of 100,000 whole genomes over the next several years. The longer-term goal is 1 million.

🧬 This idea is different from big genome programs like national biobanks, because the latter mostly sample the general population. They are not typically linked to how a disease progresses or how patients respond to treatment. Tempus’s dataset, in contrast, focuses on specific diseases and ties each genome to clinical outcomes over time. So, it is likely built for AI work, including training and fine-tuning models, not just as a database resource.

Also, Tempus is arguably moving beyond targeted gene panels (tests that read only selected genes) to reading the whole genome. The data joins its existing de-identified records: clinical histories, imaging, pathology and outcomes. Researchers could use it through Tempus Lens, so they can build and test models without moving data between systems. This plays in favor of usability, which naturally increases chances of better insights.

Lefkofsky says it himself: “A large dataset is only valuable if you can turn it into insight.”

Regarding the timing, this work has started, and early data is available through an Early Adopter Program, where more members join in waves, and full availability is planned for mid-2027.

On a personal note, I recently joined Rafael Rosengarten of Genialis' Talking Precision Medicine podcast (episode #61, Sept 17) to argue that counting "AI-discovered drugs" is the wrong yardstick — candidates come out of long collaborative processes where the AI contribution can't be cleanly separated, so R&D productivity, faster killing of weak candidates and actual software adoption tell you more.

We also got into why AI became so polarizing, what stays human as information gets commoditized, and why the next era may run on patient samples, organoids and whole-system models rather than single frontier models and target-ligand reductionism.

Listen here (around 50min): https://www.genialis.com/2026/09/17/the-kodak-moment-for-drug-discovery-ai-adaptation-and-what-stays-human-tpm-podcast-61/

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii and WTMB Team!

Read also:

Could Anthropic Disrupt the Techbio Companies Built for Pharma/Biotech?

What Do the New AI Model Releases by Anthropic and OpenAI Change for Life Sciences?

The Bigger Point Beyond Insilico’s Aging Research Milestone

Into the Dark: Finding Novel Drug Targets Within the Depths of Our Proteome

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

In this issue: a retired chemist designs a renin inhibitor with ChatGPT and Gemini — Astromech raises at $3.8B and Forus at $3B while BioXcel files Chapter 11 — Google maps the largest connectome yet — Claude runs a protein design campaign — and a stablecoin issuer quietly publishes three BCI papers.

Main story

Chemical & Engineering News (C&EN) recently published an interesting case study on using off-the-shelf AI chatbots to assist in drug design work.

As Bethany Halford explains in her article, at ACS Fall 2026 in Chicago, Guibai Liang, a veteran medicinal chemist who co-founded Sheo Pharmaceuticals after retiring from big pharma, presented a talk in the Division of Medicinal Chemistry about how his team designed a novel renin inhibitor for hypertension using ChatGPT and Gemini, off the shelf, with no proprietary model in the loop.

Renin is about as picked-over as targets get: every major pharma ran a program, and aliskiren (Novartis’s Tekturna/Rasilez) is the only one the FDA ever approved — a mediocre drug, in Liang’s words, mostly on bioavailability.

Sheo took Takeda’s TAK-272 as a starting point and put what Liang calls “critical and revealing questions” to the chatbots: what does the hydrogen bond donor on the piperidine do, is the morpholine oxygen needed for activity, is metabolic stability a concern.

The models answered by synthesizing decades of published structure-activity relationship (SAR) insights — “it’s impossible for human chemists to remember all those data to come up with a clear picture,” Liang said for C&EN. From those answers, the team designed a new chemical class, had a CRO make 200 compounds across several iterations, and landed on SHEO-054, which reportedly outperformed aliskiren in a monkey model of hypertension.

Caveats: The structure wasn’t disclosed, only a general scaffold, and the data are self-reported from a conference talk, no paper yet. Also, “outperformed aliskiren” in one primate model is a long way from a development candidate.

The AI here read the literature no human could hold in working memory and handed back a coherent SAR picture, and Liang himself flags that renin may be a special case precisely because so much was published before the field walked away. The enabling condition is a dense, abandoned literature, which describes a surprisingly large share of pharma’s dead targets, and points at a strategy that doesn’t need a $100M platform to run.

Liang’s takeaway was blunt: “If you are not using AI in your medicinal chemistry, start now.”

Read “This company designed a drug candidate with help from ChatGPT and Gemini“ by Bethany Halford.

Share

📅 I am excited to share that I’ll be a speaker at the upcoming TechBio Europe 2026 event in Paris, on November 30.

TechBio Europe 2026 brings Europe’s TechBio founders, investors, and pharma partners to Paris for one day on Nov 30 at Future4Care — financing, dealmaking, hiring at the bio/code intersection, plus a pitch contest for the continent’s newest startups.

TechBio Europe is organized by the TechBio Commission, co-led by WhiteLab Genomics and Scienta Lab, under the guidance of France Biotech, France Deeptech, Future4care, and proudly sponsored by In Extenso Innovation Croissance, ICOSA | European Intellectual Property Firm, BioLabs, McDermott Will & Schulte, BioTalent, and Wellcome Genome Campus.

TechBio Europe also kicks off Bioweek, a week of industry events in Paris.

Register for TechBio Europe and let’s meet: https://www.eventbrite.fr/e/techbio-europe-2026-tickets-1996434242562.

The Brief

🚀 New Launches

• Geodesic Intelligence launched out of the gate with two products, NovaDDE and NovaAtom-Lite-Preview, pitching an AI-native platform for protein therapeutics and describing its aim as "AGI for drug discovery" — no funding, team, validation data or partners disclosed in the announcement.

  ---

💰 Follow the Money

• Astromech, the Colossal Biosciences spinout founded by Ben Lamm and George Church, raised $20M led by Bob Nelsen (PEAK6, NeoGenesis, Builders VC and CAZ participating) at a company-reported $3.8B valuation ($60M total) to expand its genomic training datasets and model infrastructure for longevity work on evolutionary outliers like bowhead whales and Brandt's bats, though no externally validated performance, revenue or deployment data was disclosed.

• Paul Allen's science fund is backing AI BioDesign, a Seattle effort, with ~$95M over five years — $46.1M to the Allen Institute, $43.8M to UW, $4.7M to Fred Hutch — for a loop where AI designs proteins and genetic switches that don't exist in nature, labs test them, and the results retrain the models.

• BioXcel Therapeutics, the AI-driven neuroscience biotech behind the approved agitation drug Igalmi, filed for Chapter 11 with Teva as stalking-horse bidder at $57.5M upfront plus $67.5M in milestones — a cautionary marker for AI-derived pipelines

• Forus raised a $150M Series C at a $3B valuation led by Bain Capital Ventures, taking total equity past $300M for its AI-agent network that cuts prior authorization from weeks to under 48 hours across physicians, pharmacies, payers and manufacturers.

  ---

🤝 Deals & Alliances

• BenchSci and argenx partnered to apply BenchSci's agentic AI platform EMET to preclinical drug discovery, pitched by CEO Liran Belenzon and argenx's Tim Van Acker as an "always-on AI research partner."

• Owkin licensed K Pro, its agentic "AI scientist," plus multimodal patient data from its MOSAIC network to Servier for oncology research.

• Merck KGaA is paying PostEra "mid-double-digit millions" for its two fertility programs — oral small-molecule agonists of the FSH receptor and the LH/choriogonadotropin receptor that could replace the injection standard in IVF. Both are designed on PostEra's AI platform to solve the selectivity and half-life problems that sank earlier attempts, while PostEra keeps its PMOS program in-house with trials planned for early next year.

• Ginkgo Bioworks won a subcontract worth up to $17.5M under ARPA-H's GIVE program, joining Waterfall Scientific on ESCALATOR — a multi-organization effort to compress end-to-end RNA drug manufacturing onto a benchtop footprint.

  ---

🔬 Science to Watch

• Google Research and HHMI Janelia published in Cell the complete AI-reconstructed wiring diagram of the male fruit fly's brain and nerve cord — 166,000 neurons and 125 million synapses.

  

  It is the largest connectome to date, which, paired with the existing female map, lets researchers compare the sexes neuron by neuron and sets up the methods for mapping zebrafish and mouse brains next.

• AlphaGenome Atlas by Google DeepMind, scores all 9 billion possible mutations, coding and non-coding ones. They say that Gareth Hawkes, a Medical Research Council fellow at the University of Exeter, arguably found 22% more non-coding associations in the UK Biobank just by re-ranking with the Atlas.

• Anthropic reports Claude, orchestrating existing open-source design tools rather than modeling proteins itself, produced 354 wet-lab-confirmed binders from 1,320 designs across 15 targets — a 22.6–35.1% hit rate against the 10–15% industry norm. Though the work is unreviewed, has no human-expert control arm, and the best-performing models stay access-restricted on biosecurity grounds.

• Insilico Medicine Doses First Patient in GENESIS-IPF-3, the World's First Phase III Trial of a Generative AI-Driven Innovative Drug

  

  ---

📋 From the Regulators

• The FDA is putting sponsors on notice that it will refuse clinical data it cannot inspect or verify — with extra scrutiny on foreign Phase 1 and non-IND/IDE studies in countries where site access is denied or informed consent is questionable — and is expanding foreign inspections and publicizing where access was blocked.

  ---

💁‍♀️ People 💁

• Hon Weng Chong, founder of Cortical Labs, the Melbourne company behind the DishBrain work and the CL1 biological computer, announced on LinkedIn that he has resigned after seven years, saying he's proud of what was built and no longer has access to his company email.

  

Leave a comment

A Thing To Know This Week

Addressing one of the biggest challenges in brain-computer interfaces

Tether Evo, a frontier tech division of Tether, the stablecoin issuer, had three brain-computer interface (BCI) papers accepted at the Journal of Neural Engineering, Imaging Neuroscience, and Neural Networks, two of them with the University of Rome Tor Vergata.

All three attack the same bottleneck: every brain produces different signals, so decoders have historically been rebuilt from scratch for each patient, and the calibration burden is a real barrier to fielding these devices. The common move across the papers is an alignment step that maps different people’s neural data into a shared space, so one model can be trained across subjects and then fine-tuned for a new one.

The speech paper (preprint on bioRxiv) deals with a cross-subject neural-to-phoneme decoder trained on invasive recordings from multiple participants implanted in different cortical regions, which is the hard version of the problem. Tether reports it matches or beats single-patient systems while adapting to a new person in minutes to hours rather than the usual long calibration, and describes it as the first of its kind. The vision paper reconstructs what macaques were looking at from 200 ms of spiking data, identifying the exact image out of thousands 70% of the time.

The music paper ran fMRI on five people hearing 540 songs across 10 genres, hitting 61% genre identification against 10% chance and ~25% song identification among 60 candidates against under 2% — classical and jazz the most distinctive, metal and disco the most confusable.

It is notable that Tether took a $200M majority stake in Blackrock Neurotech in April 2024, the company behind a large share of the world's chronic human intracortical implants.

Share

Strategic Signals…

👉 AI labs are pivoting hard into health care to fix the notorious public perception trend. Anthropic is talking up biology ahead of its IPO, Nvidia and Lilly are building a $1B drug discovery lab, etc., partly because curing disease is a far better public story than data centers hogging power and driving up utility bills, and partly because life sciences diversify revenue as these companies head to public markets.

The catch is timing: real breakthroughs are years off, AI is making some health care more expensive, and biosecurity risk is real enough that Anthropic added safeguards to Claude Fable 5 after finding it could give a bad actor "significant uplift," so the goodwill is being spent well before the results arrive…

👉 AI-enabled drug repurposing is one of the most straightforward value propositions of the modern AI drug discovery movement. THPharm ran its Phase 3 metabolic drug THP-001 through Insilico Medicine’s PandaOmics (including 16 public datasets, 269 samples of post-treatment gene expression) to find new indications it might also treat, surfacing heart failure, fatty liver disease, and obesity as candidates.

The logic is capital efficiency: the drug already has human safety data, so each new indication starts with a big chunk of risk removed. Though these are computational hypotheses that still have to clear cell models, animals, and human trials.

👉 Aaron Blotnick argued on LinkedIn that OpenAI's integration of ChatGPT directly into Epic (the EHR holding records for 325M+ patients) just wiped out an entire startup category. Clinicians can now summarize labs, pull patient history, prep for visits and build clinical timelines without leaving the chart, plus a new plug-in pulling live data from ClinicalTrials.gov, CMS, RxNorm, DailyMed and PubMed. His conclusion: "If your startup's moat was 'AI + EHR integration,' it's time to find a new moat."

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii and WTMB Team!

Share

Read also:

What Do the New AI Model Releases by Anthropic and OpenAI Change for Life Sciences?

The Bigger Point Beyond Insilico’s Aging Research Milestone

Into the Dark: Finding Novel Drug Targets Within the Depths of Our Proteome

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

In this issue: The FDA opens the question of how you evaluate a clinical AI that answers differently every time — Network Bio, Harell Data and Lilly's TuneLab each try a different way of getting proprietary data into AI models without the owner handing it over — Claude runs a 48-hour protein design campaign on its own and publishes the prompt — Insilico Medicine sketches an ageing virtual cell — Cell publishes fifteen grand challenges for generative AI in biology — Nature Reviews Neurology asks what happens after a clinical model works — Faro raises $37M to speed up trials — GSK starts paying NOETIK to rent its models — An emerging market for DNA as a programmable building material. And more…

The FDA writes down how it might grade a clinical AI, and opens the docket

This month, the FDA’s Center for Devices and Radiological Health (CDRH) published Considerations for the Regulation of Generative AI-Enabled Medical Devices. It’s a discussion paper, not guidance, and comments close October 19.

It is a conceptual matter, with potentially far-reaching legal and business implications for anyone building AI-driven medical devices… so make sure to read it.

In a nutshell, the old approach to assessing medical devices is to assume a device answers the same way every time, i.e., like “good old software”. Generative AI does not behave this way, it can answer differently tomorrow, and the foundation model underneath it can be updated by a third party, influencing the device behavior in unpredictable ways. So, trying to evaluate the behavior of AI-driven devices precisely might be unrealistic. The paper’s own words: “… it may be unreasonable to evaluate every conceivable input…”

So how do you evaluate something like that?

The FDA’s tentative answer is that you do it roughly the way you evaluate a doctor. Exams to check they know the material and won’t do anything dangerous, then supervised practice, then keeping an eye on them once they are working alone.

In practice, for a device that could become benchmarking, then clinical confirmation — which might be retrospective review, or shadow deployment, or a full prospective trial depending on the stakes. Then monitoring for as long as it is in use. In other words, where there is no single right answer, the device gets compared to a panel of clinicians or a median clinician rather than to an ideal correct response.

How much scrutiny you get depends on what the software actually does (just informs, directs, or acts on its own), and how badly things can go if it is wrong. A simple diagram explains the framework:

An important food for thought for businesses building AI-driven medtech devices — about risk management. A lot of health apps give someone specific advice and then add "talk to your doctor" underneath, on the assumption that the disclaimer keeps them in the safe, informational category. The FDA is signalling that it probably does not… What does is what the output actually tells the person to do.

⚡ This issue is brought to you by SYDRA

The Brief

💰 Follow the Money

• In a historical milestone, Moderna and Merck's intismeran, an mRNA vaccine built individually for each patient using data of their own tumour's mutations, kept melanoma from returning for longer when added to Keytruda, in a Phase 3 of about 1,100 people whose tumours had been surgically removed. It's the first randomised Phase 3 win for a personalised cancer vaccine, though the actual numbers come later at a conference, and each dose still takes months to manufacture. Anyway, Moderna’s stock jumped 177% on the news, its biggest one-day move ever, with Merck also gaining substantial upward movement.

• Network Bio, a biobank-focused biotech startup, launched out of stealth with $50M and what it calls the world’s largest patient-tissue training dataset — 500,000+ patients with paired tissue, blood and longitudinal outcomes from Mass General Brigham, Penn, Duke and CU Anschutz on a common data model. Investors include Section 32, Thiel Bio, Founders Fund and Breyer Capital, which led the company’s first institutional round in 2022.

  Interestingly, Network Bio and NVIDIA are also building what they describe as the first foundation model trained on cell-free RNA, using Parabricks and BioNeMo Recipes. The company also disclosed a $30M+ co-development and licensing agreement with a Fortune 100 healthcare company to identify and interpret novel disease signatures using Network’s proprietary AI architecture.

• Harell Data, founded by Adaptive Biotechnologies co-founder Harlan Robins, raised $15M from Fuse and Cercano Management to let data owners host proprietary training sets and take a cut of the compute revenue from models trained on them, rather than waiting on downstream royalties.

  Why it matters: it prices scientific data as a rentable asset instead of an equity bet. Early datasets come from A-Alpha Bio and Adaptive.

• Faro, an AI startup working on clinical trials, raised $37M from Merck's venture fund and S32. CEO Scott Chetham says the startups chasing faster trial documents "just made tiny bits a little bit faster."

🤝 Deals & Alliances

• Eli Lilly’s TuneLab models are now in Benchling. AbLab predicts antibody developability (thermal stability, aggregation, viscosity, solubility, etc) from heavy and light chain sequences. ChemLab returns ADME/Tox predictions from a SMILES string.

  The catch: access is reciprocal. Participating biotechs contribute their own assay data through TuneLab’s federated learning platform, which never exposes the raw data, and admins install the models from Benchling’s Model Hub registry.

• NOETIK hit the first payment milestone in its five-year GSK deal by getting its OCTO-VC cancer foundation models running inside GSK's own systems, which matters mainly because GSK is paying subscription-style fees to rent the models rather than buying drug candidates, and that arrangement is now producing money.

🔬 Science to Watch

• Claude ran a 48-hour autonomous protein design campaign and published the prompt. Anthropic reports de novo binders against 14 of 15 targets — 1,320 designs, 354 of which bound in wet-lab testing at Adaptyv Bio and Twist Bioscience, with hit rates of 22.6–26.7% across the multi-target run and 35% in a single-target 24-hour campaign, against a stated field baseline of 10–15%.

  The caveat, per Endpoints News, noted by Andrew Dunn: Claude generated nothing much itself, it orchestrated open-source tools (PXDesign, RFdiffusion, BoltzGen) and reasoned over the results, and hit rate moves with target difficulty. Maltose-binding protein defeated all 90 designs against it. Designs, raw data, a 29-page technical report and the full ~16,000-word prompt are public.

• Insilico Medicine sketched out what an ageing virtual cell would look like. Most virtual cell models are trained on cells caught at a single moment, so they can tell you what a cell looks like but not how it got there or where it's going. Insilico wants to go further, making age the thing the model is operating on. Instead of one big gen network, they plan on using a group of AI agents that each handle a different level — molecules, cells, tissues, organs, the whole organism, communicating between each other.

  The idea is you could ask what happens if you, say, knock out a gene, and get the answer accounting for time and space. I think it is more of a concept for now, as I did not find specific data or paper yet. They say more thinking is coming at Aging Research and Drug Discovery Meeting in Boston soon.

  

• In a new article in Cell, authors published fifteen grand challenges for generative AI in cell biology, sorted into four categories: molecular interactions, molecular functions, cellular and systems function, and translation.

  Why it matters: the authors argue current systems are benchmarked on retrospective statistical tasks rather than decisions, and call for CASP-style held-out evaluation.

• A Nature Reviews Neurology perspective maps what happens after a clinical model works: outcome benefit, workflow fit, reimbursement and drift, arguing deployment is not the end of model development but another stage of evaluation.

📋 From the Regulators

• The FDA approved Revolution Medicines' daraxonrasib for previously treated metastatic pancreatic cancer — the first drug ever cleared that hits RAS broadly, the cancer gene that defeated the industry for forty years and drives nearly every pancreatic tumour. It doubled median survival to 13.2 months against 6.7 on chemotherapy in the Phase 3 RASolute 302 trial, and the FDA cleared it six and a half months ahead of schedule.

Leave a comment

⚡In partnership with SYDRA

Most AI drug-discovery companies begin with a target and use algorithms to optimize molecules around an assumption. SYDRA reverses the logic.

Our proprietary AI selects and generates novel chemistry; whole-organism lifespan assays reveal which molecules actually affect aging biology; and only the phenotype-proven winners advance into aged-mouse studies, human-cell target deconvolution and disease positioning.

Starting from six million molecules, we identified five significant lifespan hits, advanced two lead programs into late-life mouse pilots, and created a new generative chemistry cohort now entering synthesis. We don’t use AI to decorate a target hypothesis. We let living biology decide which AI discoveries deserve to become medicines.

SYDRA is now raising a CHF 2.6 million pre-seed round to accelerate lead programs toward pharma partnering.

A Thing To Know This Week

Beyond the Code: How DNA Nanotechnology is Moving from Molecular Origami to Programmable Biotech Platforms

In a new article published on BiopharmaTrend, Louise von Stechow and Marco Lolaico make the case that DNA is worth treating not only as a carrier of genetic information but as a construction material, one whose predictable base pairing lets researchers fold structures that place proteins, ligands or fluorophores exactly where they want them, and even build devices that switch shape or release cargo on cue.

In the article, Louise and Marco walk through where that has actually reached the market, which so far is mostly research tools and diagnostics:

- GATTAquant already sells DNA origami calibration standards for microscopy,

- Amplifold raised €5 million to make rapid tests roughly a hundred times more sensitive without changing the familiar lateral-flow format,

- Nanogami and MediQuant are building biochips and point-of-care drug monitoring, respectively… and so on.

Therapeutics are further back:

Plectonic's logic-gated T-cell engagers, DoriNano's cancer vaccine now working with Memorial Sloan Kettering and Daiichi Sankyo, DNA Nanobots' non-viral gene delivery — all still preclinical.

The authors are clear-eyed about why: the structures are expensive to make, they fall apart in the body, and nobody has settled how to prove batch-to-batch consistency.

Cost is improving fast, though (a 2026 study got to about $6 per milligram in the lab), but they argue cheaper DNA alone won't do it, and that the field needs standardized manufacturing, better stabilization, quantitative quality control, and regulators willing to say which structural attributes actually matter.

Read the article here.

Share

Strategic Signals…

Bart De Witte, co-founder and CEO of Isaree, argues that Apple's new M5 Ultra chip, 512GB of unified memory under a desk, kills the assumption that hospital AI has to mean shipping patient data to someone else's data centre, because a frontier-scale medical model now fits in local memory. His company is building for that world: an open platform where clinicians build their own agents, running on-device or on-prem, with GDPR compliance built into the architecture (especially relevant for EU-based facilities).

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii and WTMB Team!

Share

Read also:

Could Anthropic Disrupt the Techbio Companies Built for Pharma/Biotech? (Also: The Numbers Behind China’s Biopharma Ascent)

Is the Future of AI Drug Discovery Hybrid?

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

Cancer as a Data Problem: What AI Is Doing in Oncology

Where Tech Meets Bio, as well as BiopharmaTrend, are now published by WTMB Research & Media SL, a company based in Spain.

This follows the restructuring of our business. Our editorial commitment remains focused on covering the cutting-edge technological advances in pharma, biotech, and medtech industries, companies that drive those advances, and regular analysis of industry trends.

As part of this transition, we are updating our payment system. This means:

— If you are a free subscriber, no action is needed. Your subscription continues as normal.

— If you are a paid subscriber, your current subscription will be cancelled, and you will receive an automatic prorated refund for any unused portion of your subscription. We wish we could avoid it, but this is due to Substack's internal hard limitation to be able to transfer payment arrangements when the newsletter moves to another country.

We will notify you when the new payment system is live so you can resubscribe if you wish. We apologise for the inconvenience and deeply appreciate your support.

Importantly, the data controller for this newsletter is now WTMB Research & Media SL (CIF: B93869147), C/ Almirante Cadarso nº 26, 46005 Valencia, Spain. Please read our Privacy Policy to know your rights concerning your personal data.

You can unsubscribe at any time using the link at the bottom of this newsletter if you do not wish to receive future emails from us. However, we do hope you continue reading our work, because we are going to expand and deepen our analysis and coverage of the “tech+bio” frontiers.

Thank you for being part of our community!

In the meantime, keep reading this week’s highlights as we are gradually renewing our weekly cadence.

Cheers!

— Andrii and the Team of Where Tech Meets Bio newsletter, from sunny Spain🌴.

In this issue: a decade-in report card on AI drug discovery; frontier AI labs moving into the CRO and clinical-trial layer; agentic co-scientists landing inside pharma research organizations; what is happening in in vivo cell therapies; the FDA piloting a faster route into first-in-human trials, and other key signals.

After a decade of AI drug discovery, two of its vocal voices assess progress

Perhaps unusually for August, there is a lot of business and research activity in the artificial intelligence (AI) drug discovery space. Notably, within four days of each other, two respectable voices in the AI drug discovery space independently published two important pieces about the state of progress, where industry stands about all sorts of AI tools as of 2026, and where it may take us from here.

On August 3, insitro founder and celebrity in the field of artificial intelligence published “Drug Discovery Has No Magic Wands.” She splits development broadly into three stages:

… and argues AI effort has concentrated overwhelmingly on the middle one, molecular design, while more than 90% of clinical failures come from picking the wrong mechanism. Even total success on the AI-addressable portion, she notes, touches only about half a development timeline; the cell atlases needed to attack stage one are “orders of magnitude too small.”

On August 7, Dr. Andreas Bender, Professor for Machine Learning in Medicine at Khalifa University, and a large co-author group published “Artificial intelligence in drug discovery — what it is, where we stand and the path forward” in Nature Reviews Drug Discovery.

Its verdict on a decade of work: clinically relevant impact has been “disappointingly limited,” caused by too little focus on clinical translation, the context-dependent nature of real biological data, and problem definitions too vague for the decisions the models are meant to inform. The prescription is a shift from “technology push” to “science pull,” and benchmarks that measure improved decision-making rather than model performance.

Neither piece cites the other, the convergence seems to be independent, which likely signals a growing industry consensus about the current state of AI in drug research.

⚡ This issue is brought to you by SYDRA

The Brief

💰 Follow the Money

🔹Dash Bio raised a $30M Series A led by Oak HC/FT for its robotics-run bioanalysis lab — preclinical assays back in days, not months.

🔹Pathos AI in-licensed two oncology assets in one day for a reported ~$2.2B — a TROP2/HER3 bispecific ADC from Alphamab and an ERα PROTAC from AstraZeneca.

🔹Bruker took a majority stake in organ-on-a-chip maker MIMETAS (terms undisclosed). Why it matters: positions Bruker in the New Approach Methodologies push to replace animal testing.

🔹Anthropic opened rare disease research grants — up to $50,000 in Claude credits over six months, two tracks, applications closed August 2.

🤝 Deals & Alliances

🔹Bristol Myers Squibb is deploying Schrödinger’s agentic AI co-scientist Bunsen across its research organization, plus the RetroSynth synthesis planner. Terms undisclosed.

🔹Genentech exercised its first option on a Recursion-discovered neuroscience target, moving it into joint small-molecule discovery. The numbers: first target out of a collaboration that has paid Recursion $216M to date, with up to 40 possible programs. — link

🔹ICON, a top-five CRO, signed a multi-year deal to embed Claude across the clinical trial lifecycle. Backstory: caps a year of Anthropic life-science moves — Claude for Life Sciences, the ~$400M Coefficient Bio buy, Claude Science, and hiring AlphaFold’s John Jumper.

🔹J&J paid $785M for an option to acquire in vivo CAR-T player Sail Biomedicines for a further $2.58B. Backstory: the fifth major in vivo CAR-T deal since Lilly’s $7B Kelonia buy in April thinned the field of outright targets.

🔹Merck KGaA adopted Evinova‘s AI-native clinical development platform — AstraZeneca’s in-house health-tech business selling to a competitor.

🔹Pharma is pooling its structural data. C&EN on the Federated OpenFold3 Initiative, where AbbVie, J&J, BMS, Takeda and Astex train a shared open model without exposing IP.

🔬 Science to Watch

🔹A CRISPR enzyme that kills cancer cells by shredding their own DNA. Doudna’s group published Cas12a2 in Nature: triggered by a mutant RNA transcript, it destroys the host cell’s chromatin, killing p53-mutant cells while sparing healthy ones. Preclinical.

🔹An AI biologist called XunZi flagged CHK2 as a Parkinson’s target; inhibiting it rescued dopaminergic neuron loss and motor deficits in mice. Nature Biomedical Engineering, Aug 4.

🔹Open-weights models that read chemistry out of patents. Edison Scientific’s MarkushGlyph parses Markush structures at 58–64% accuracy; single-structure recognition hits 93.8%. What it is: Markush diagrams are how one patent claims millions of compounds.

🔹Clinical AI’s dangerous failure is omission, not fabrication. The NOHARM benchmark found errors of omission account for >80% of severe errors across 20 LLMs and 4 RAG clinical tools. Preprint.

🔹Recursion says protocol simulation against real patient data expanded trial eligibility 10–40%, with enrollment 30–60% above historical projections. Vendor-reported.

🔹Insilico launched a benchmark for AI drug discovery models — 300+ evaluations across two suites, live since July 30. No leaderboard scores published yet.

🔹~50 authors proposed an L0–L5 autonomy ladder for laboratories, arguing self-driving labs need a shared “world model” layer. Leskovec, Uhler, Ioannidis and Shah among the signatories.

📋 From the Regulators

🔹FDA is piloting a faster route into first-in-human trials. The Expedited IND Pilot would let sponsors use pre-vetted research institutions and file INDs on a rolling basis; the agency estimates clarified Phase 1 CMC expectations alone could save 6–12 months.

🔹A companion draft guidance shifts first-in-human dose selection toward QSP modelling and away from animal toxicology.

Leave a comment

⚡In partnership with SYDRA

Most AI drug-discovery companies begin with a target and use algorithms to optimize molecules around an assumption. SYDRA reverses the logic.

Our proprietary AI selects and generates novel chemistry; whole-organism lifespan assays reveal which molecules actually affect aging biology; and only the phenotype-proven winners advance into aged-mouse studies, human-cell target deconvolution and disease positioning.

Starting from six million molecules, we identified five significant lifespan hits, advanced two lead programs into late-life mouse pilots, and created a new generative chemistry cohort now entering synthesis. We don’t use AI to decorate a target hypothesis. We let living biology decide which AI discoveries deserve to become medicines.

SYDRA is now raising a CHF 2.6 million pre-seed round to accelerate lead programs toward pharma partnering.

A Thing To Know This Week

In vivo CAR-T, and why everyone is buying it

Conventional CAR-T extracts a patient’s T cells, engineers them in a facility to recognise a cancer target, and infuses them back. It works, at several hundred thousand dollars per patient, over weeks, at specialist centres only.

In contrast, in vivo CAR-T does the engineering inside the body: inject a lipid nanoparticle or targeted viral vector that reprograms T cells where they already live. No extraction and no manufacturing slot, a body becomes, basically, its own bioreactor for the therapy. If it works, a cell therapy becomes almost as simple as a regular injection.

That “if” is what eighteen months of dealmaking has been pricing on the level of strategic M&As.

AstraZeneca, AbbVie and Gilead each bought a platform in 2025; Lilly bought two in early 2026, for up to $7B in total. Most of these assets are preclinical — pharma is arguably buying delivery technology on the bet that the biology is proven and only the logistics are mostly unsolved.

Interestingly, Johnson & Johnson appears to be more cautious. J&J’s $3.5 billion deal with Sail Biomedicines serves as the textbook definition of an "option-first" structural hedge. Rather than acquiring an in vivo company outright at a massive premium like others, J&J structured a massive option agreement that secures early platform access while shifting early clinical risk entirely onto the partner.

Share

Strategic Signals…

🔗 DeepMind dismantled the AlphaFold team — and it matters less than the headline suggests.

🔗 Ramy Farid called AI in drug discovery “nonsense” in 2024. In July he shipped an AI co-scientist and said he couldn’t be more pleased to be wrong about AI in the past.

🔗 “Forward deployed scientist” is becoming a real job title — Chai, Phylo, Lila and Periodic Labs are all hiring it.

🔗 China's share of first drug launches rose from 3.3% to 28.7% between 2004 and 2024 while Europe's fell from 26.7% to 8.5%, per a new analysis. US is still leading the pack but declined from 45.9% to 37.8%.

That was last week, and have a great one ahead!

Forward this to a colleague who should be tracking this space,

Cheers!

— Andrii

Share

Read also:

Could Anthropic Disrupt the Techbio Companies Built for Pharma/Biotech? (Also: The Numbers Behind China’s Biopharma Ascent)

Is the Future of AI Drug Discovery Hybrid?

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

Cancer as a Data Problem: What AI Is Doing in Oncology

Also, if you're at Drug Discovery Chemistry in San Diego this week, our board advisor Andrew Lozoniuk is there and happy to chat!

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

Agents at AACR 2026

At the American Association for Cancer Research annual meeting this year, out of ~9,600 accepted abstracts roughly 1,100 (1 in 8) are AI-related, according to Miraei AI.

Within that: ~160 reference LLMs, generative AI, or agentic systems; ~140 involve multimodal approaches; ~225 cite clinical validation or deployment language. The Miraei team’s read is that AI in oncology is shifting from isolated proof-of-concept models to embedded operational systems.

The leaderboard of AI-related abstract affiliations at AACR 2026, split by academic institutions and commercial entities:

AACR will host a dedicated “Agentic AI in Cancer” session: MD Anderson will debut “Charles,” a self-critical agentic drug discovery analyst built around traceability and hallucination mitigation. MSK will show an MCP-enabled AI agent in its genomics platform automating multimodal analysis at petabyte scale. AstraZeneca (the most-represented biopharma in the AI corpus with ~10 abstracts) will present an agentic system for RNA-seq pipeline automation. (AstraZeneca also acquired Modella AI earlier this year, whose Judith agent automates pathology image analysis workflows.)

Foundation models were still a distinct thread. Bioptimus delivered three abstracts including two late-breakers—H-optimus-1 for computational histopathology and M-Optimus-1, a multimodal model unifying H&E imaging, bulk and single-cell RNA-seq, and spatial transcriptomics. A UCSD–Lunit collaboration will present a foundation model of cancer genotype predicting therapeutic response.

Around 225 abstracts use language suggesting clinical validation or deployment, not just modeling accuracy on retrospective data. A separate “LLMs in the Clinic” session (~30 abstracts) will focus on infrastructure problems: trial matching, EHR extraction, pathology report abstraction, patient message triage. A University of New Mexico study reported cancer patients preferred ChatGPT-generated responses to physician-authored ones in a blinded comparison.

This tracks with what we covered in our February deep dive on AI in oncology. The pattern across ~1,100 abstracts is the same shift we described there: from standalone models to infrastructure. Agentic systems managing multi-step workflows, LLMs doing clinical plumbing, foundation models trained at institutional scale. Commercial actors (Tempus, Labcorp, Lunit, Natera, BMS) are showing operational work; the startup layer (Bioptimus, Data4Cure, Keiji AI, EXoPERT) is landing late-breaking slots.

AI in the pipeline

A few recent moves worth noting across clinical trials, pharma infrastructure, and AI-designed therapeutics.

🔹 Massive Bio published a prospective study in ESMO Real World Data and Digital Oncology with 3,804 cancer patients, 17,000+ oncologist-confirmed trial matches, 4x faster matching (120-to-30 min per patient), outperforming zero-shot GPT-4 and GPT-4o.

🔹 CRO Fortrea released an AI suite for clinical workflow automation, part of CEO Anshul Thakral’s turnaround strategy since taking over in June 2025.

🔹 Tempus expanded its collaboration with Gilead with enterprise-wide access to Tempus’s Lens platform for oncology R&D, continuing the pattern of large pharma outsourcing data infrastructure to specialized AI/RWE companies.

🔹 Astellas exercised its option to license a Dyno Therapeutics AAV capsid for skeletal muscle gene delivery, following Roche’s CNS capsid license in January 2025 — making Dyno the first company to license AI-designed capsids for both CNS and muscle ($15M fee plus milestones and royalties).

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

Daniel Strasser, Executive Director and Therapeutic Area Biomarker Head at Novartis, posted a tracking that puts the pace of AI-pharma deals in perspective.

• Between 2021 and 2024, top pharma signed 2–4 AI deals per year. In 2025: 15. At Q1 2026 pace, the year is tracking toward ~24 — a 12x increase in five years.

• Combined potential deal value across 34 tracked partnerships exceeds $78B. All top-10 pharma like Lilly, Novartis, Roche, Sanofi, AstraZeneca, J&J, Novo Nordisk, Takeda are in with billion-dollar-scale commitments.

• NVIDIA alone ($4.4T) is worth more than all top-10 pharma combined ($3.5T), and the AI-pharma pure-plays signing these deals collectively sit around $23B.

Strasser's question is—which side captures the value?

Cell reprogramming in the clinic

Longevity raise—Life Biosciences (co-founded by David Sinclair) closed an $80M Series D for the Phase 1 trial of ER-100—reportedly the first partial epigenetic reprogramming therapy to receive FDA IND clearance. ER-100 uses AAV2 vectors encoding three Yamanaka factors and an oral small-molecule switch, targeting retinal ganglion cells in optic neuropathies.

Q1 2026 was strong for longevity biotech overall ($3.7B across 49 deals, 56% YoY). Competitors remain largely preclinical:

• Altos Labs (~$3B, stealthy)

• Retro Biosciences ($1B+ Series A, clinic-stage autophagy)

• NewLimit ($130M Series B, liver)

Life Bio’s differentiator is clinical specificity, though the sector still has to prove it can produce credible aging biomarkers alongside disease-specific efficacy.

Europe’s largest independent biopharma raise?

Jeito Capital closed Fund II at over €1B (~$1.2B). The fund targets 15-to-20 clinical-stage investments at up to €150M each, addressing a funding tier where European options have historically been thin.Fund I (€534M, 2021) exits include Eyebiotech (Merck, $1.3B) and Hi-Bio (Biogen, $1.15B).

For context: between 2015 and mid-2025, EU biotech startups attracted €25B in venture capital versus €219B in the US, and 66 of the 67 EU companies that went public over the past six years listed on foreign exchanges.

🔹 A digital therapeutic for negative symptoms of schizophrenia—Click Therapeutics got $50M Series D from Boehringer Ingelheim plus full commercial rights for CT-155. Phase III CONVOKE met its primary endpoint (p=0.0003, Cohen’s d = –0.36). Click already has two authorized digital therapeutics (migraine, major depressive disorder) and 63 patents.

🔹 The OpenAI Foundation announced $100M+ in initial grants for Alzheimer's research across five tracks: causal mapping (Arc Institute), AI-assisted drug design (Institute for Protein Design + Mass General Brigham), open datasets (EvE Bio), biomarkers (UCSF), and off-patent treatment testing (Harvard). David Baker's IPD team says they've already engineered molecules that engage and degrade Alzheimer's-relevant targets using AI protein design models. The off-patent track is notable: lithium orotate and the shingles vaccine both have suggestive evidence but no private-sector incentive to fund proper trials. More grants expected through 2026.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 Neuropacs received De Novo classification from the FDA for a diffusion MRI–based AI diagnostic aid that helps differentiate atypical Parkinsonian syndromes (MSAp, PSP) from Parkinson’s disease. The classification establishes a new regulatory category “Parkinsonian syndrome diagnostic aid,” and is the first device in it. The tool draws on 15+ years of research and a prospective multicenter study across 21 centers (Parkinson Study Group, published in JAMA Neurology). Neuropacs recently closed a $1M seed round.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Can it deliver? Quantum computing is drawing pharma bets. Amgen has worked with Quantinuum since ~2018 and invested in its $300M round in 2023—building competence now for utility that’s 5–10 years out. Novo Holdings is assembling a portfolio (Sparrow Quantum, Phasecraft) and says it’s “confident tangible quantum advantage for defined applications will be achieved before 2030.” VC in quantum hit $3.8B in 2025. Merck KGaA’s Thomas Ehmer offered the counterpoint: the field is “always three years away,” and whether the killer app justifies advance competence-building remains open.

🔹 Miltenyi Biomedicine’s CAR-T drove three autoimmune diseases into simultaneous remission in a single patient—AIHA, antiphospholipid syndrome, and immune thrombocytopenia, all B-cell–driven and previously treatment-resistant. Eleven months out remission holds. Kyverna Therapeutics is likely first to an autoimmune CAR-T approval (stiff-person syndrome, FDA submission expected H1 2026).

Subscribe now

Cover: Antique celestial map illustration with mythological constellations and star charts from an early 19th century astronomy book, published in London in 1822. iStock

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

Cancer as a Data Problem: What AI Is Doing in Oncology

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

The CRO intelligence layer remains unclaimed

Reuters reported that CRO stocks (IQVIA, Medpace, Charles River) have dropped sharply since Anthropic launched AI agents in February. The authors’ conclusion is that the market is overreacting, AI can’t replace patient recruitment and site execution, CROs will be broadly fine.

The near-term read is probably right, but the longer-term question is more interesting: what happens when the design layer of trials (protocol optimization, site selection, patient matching) gets commoditized by AI tools that sponsors can run themselves?

As noted recently, strategic CROs sell execution and intelligence bundled together. Unbundle that, and they’re competing on operations and logistics alone, which is a different kind of business that’s priced differently.

There’s also a second angle: if AI lowers the intelligence barrier, a new class of leaner, tech-native CROs could assemble trial infrastructure on demand, more platform than services firm. This structural shift is explored in our 2023 BiopharmaTrend analysis of the CRO industry, though agentic capabilities at the time were still early. Nobody is cutting CRO spend yet. But “no evidence of cuts” is not the same as “no shift in leverage.”

Agentic AI in drug discovery is already delivering value, but not where the hype points

📝 A new review in Drug Discovery Today covers eight case studies from companies including Coincidence Labs, Human Chemical, Potato, Kiin Bio, Augmented Nature, onepot, Plex Research, and Convexia. Some reported specific quantitative benchmarks, not just “we used AI and it was faster.”

The most convincing gains are in the tedious middle: literature synthesis, protocol generation, assay design. Potato’s Tater agent took the design cycle for a qPCR assay from literature review through to executable lab automation code from 1-4 months to under two hours. Empirical validation was still needed, but the bottleneck it removes is the coordination tax between “we know what assay we need” and “here’s a draft protocol ready for the bench.”

Note: there’s missing cost data: every case study reports time savings and none report what the agentic infrastructure costs to build and maintain.

The authors flag that current benchmarks capture whether an agent got the right answer but not whether the reasoning behind it was sound. And a separate evaluation from Princeton and Cornell suggests the problem runs deeper: across 14 AI agent systems, agents that could solve a task often failed on repeated attempts under identical conditions. Bigger models didn’t reliably fix this.

Our read: the real value right now is compressing the overhead between steps that already work on their own, not autonomous science (yet). We went deeper on where agents are actually being deployed, what’s breaking, and what alternatives look like in our recent deep dive:

➕ Fay Lin at GEN also surveyed agentic platforms now on the life sciences market after NVIDIA GTC: Kosmos, LabOS, Latent-Y, Dyno Psi-Phi, and others.

Share

Is AI replacing radiologists?

The “AI replacing radiologists” discourse resurfaced this week after NYC Health + Hospitals CEO Mitchell Katz said AI could replace a significant portion of radiology work—initial AI reads, radiologist review of flagged abnormals. The Stanford-Harvard NOHARM study showed top LLMs outperforming generalist physicians on clinical safety, and the numbers look good in controlled settings.

Bo Wang, Chief AI Scientist at University Health Network (Canada’s largest research hospital network), offered a corrective from deployment experience:

The accuracy is real in narrow tasks. But NOHARM found 76.6% of AI errors were omissions = things the model never flagged. In a hospital, a missed finding propagates: downstream physicians trust the AI read, the patient waits, the window closes. (One caveat: NOHARM evaluated LLMs on clinical recommendations across ten specialties, not imaging-specific AI, though the omission pattern maps to radiology concerns.)

No hospital system has solved the accountability question either. When an AI-assisted diagnosis causes harm, the liability chain between physician, hospital, and vendor has no established framework. Which is not regulatory delay but “...a fundamental gap in the infrastructure for AI-in-medicine.”

In Wang’s view, here’s what’s actually happening: AI is reshaping the radiology job, not eliminating it. Routine reads get faster, time shifts to complex cases and clinical correlation. The capability question is nearly answered, while the deployment question has barely been asked.

AI clinical operations partnerships keep stacking

🔹 Bristol Myers Squibb and Faro Health announced a multi-year deal to apply AI across clinical trial design and protocol workflows. Faro structures protocols into standardized, machine-readable formats and benchmarks them against datasets like Tufts CSDD, with work spanning both early- and late-phase programs. Faro is not an isolated instance—this year BMS also partnered with Evinova on trial design and with Microsoft on AI-based patient identification.

🔹Tempus reports that its ALERT trial, conducted with Medtronic across 35 U.S. hospitals, showed that AI-driven alerts embedded in EHRs improved detection and treatment of severe heart valve diseases. The study had 765 clinicians, over 2,000 echocardiograms, and used Tempus’s “Next” to analyze echo reports in real time with NLP and notify clinicians about high-risk findings.

🔹 OpenEvidence partnered with Tandem to connect real-time, AI-driven clinical decision support with automated prescription and insurance workflows. OpenEvidence functions as a clinical search layer, synthesizing evidence from sources like NEJM, JAMA, and Cochrane to support treatment decisions at the point of care, with over 1 million daily consultations in the U.S. Described as “ChatGPT for doctors,” OE raised $250M at a $12B valuation this year and generates over $100M in annual revenue, in part through ads embedded in the platform.

AI in the pipeline layer

🔹 Boehringer Ingelheim is expanding its collaboration with OpenProtein.AI to push AI-driven antibody discovery further into its development workflows. The pairing of a large pharma with deep therapeutic pipelines and a startup built around protein foundation models is becoming a common pattern.

🔹 Infinimmune and Merck entered a discovery and development partnership—Infinimmune will use its platform to screen human immune cells and identify naturally occurring antibodies, then refine them with AI tools. Merck gains exclusive commercialization rights, with potential milestone payments up to $838M across multiple undisclosed disease targets.

🔹 Evotec, Germany-based drug R&D company operating a large network of partnered R&D platforms, appointed Ashiq Khan as chief commercial officer, bringing AI and robotics experience from previous roles at Iktos and Schrödinger. The hire is part of Evotec’s broader transformation plan announced last month, which named commercial execution as a core focus.

🔹 Insilico Medicine partner TaiGen Biotechnology achieved first-subject enrollment and dosing in the Phase 1 trial of ISM4808—an oral HIF-PHD inhibitor for CKD-related anemia discovered with Insilico’s generative AI platform for small-molecule design in under three months (from the December 2025 in-licensing). Another data point for Insilico’s growing list of partnered programs moving into clinic.

🔹 Enveda Biosciences reported early clinical data from its Phase 1b trial of an oral candidate discovered via the company’s AI platform, in moderate-to-severe atopic dermatitis. Nine patients treated at 800 mg daily for 28 days showed rapid reductions in disease severity and itch within the first week, with improvements continuing after treatment cessation. No serious adverse events were reported. ENV-294 is a non-degrading stabilizer (LOCKTAC) showing biomarker activity across Th1, Th2, and Th17 pathways—broader modulation than single-cytokine-axis therapies. Enveda plans Phase 2a trials in atopic dermatitis and asthma, with Phase 2b targeted for mid-2026.

🔹 Lantern Pharma, the AI-driven oncology company known for its RADR AI platform, is joining the agentic wave with withZeta.ai—a multi-agentic co-scientist platform for rare cancer drug discovery that autonomously queries proprietary knowledge bases, clinical trial databases, and molecular libraries. The company will demo the platform at an investor briefing on April 9.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

Pharma went on a $25.5B, eight-day acquisition spree. Six pharmaceutical companies signed acquisitions worth up to $25.5B by the start of this month, including two $5B+ upfront deals disclosed on the same Tuesday morning: Eli Lilly’s $6.3B bet on Centessa Pharmaceuticals’ orexin drug candidates and Biogen’s acquisition of Apellis Pharmaceuticals. For context, there were a total of seven deals of that magnitude in all of 2025.

Across March, biopharmas lined up 10 acquisitions worth up to $31.5B, per Endpoints News. Eight included contingent value rights or milestone payments—a dealmaking structure that has become more common in recent years. Year-to-date, Endpoints has tracked up to $48B in total potential deal value across 19 biopharma acquisitions. Société Générale tallied $126B in total deal value for all of 2025, well above the 10-year average of $85B. If the current pace holds, 2026 could surpass it.

🔹 Blackstone has collected $6.3B for its latest life sciences fund, which has already committed roughly $2B over the past year for an ADC at Merck, an anti-TL1A at Teva-partnered Sanofi, and other deals. The fund invests in approximately 3% of deals it evaluates, targeting therapies with $1B+ peak sales potential.

🔹 Anthropic acquired Coefficient Bio, a stealth biotech AI startup, for $400M in stock. Coefficient Bio was founded eight months ago by Samuel Stanton and Nathan C. Frey, both from Genentech’s Prescient Design group. The team of roughly 10 people was using AI for drug discovery planning, clinical regulatory strategy, candidate identification, and biomolecule modeling. As Jonah Probell of Lexi Ventures noted, the deal generated a reported 38,513% paper IRR for Dimension, the VC firm that backed them. Anthropic’s head of Healthcare & Life Sciences Eric Kauderer-Abrams stated the goal rather plainly: Anthropic wants a meaningful share of all life science work globally to run on Claude. The team is expected to join Anthropic’s health and life sciences unit.

🔹 Generare, a Paris-based techbio building a discovery platform around microbial DNA, raised €20M in a Series A co-led by Alven and daphni. The company identifies biosynthetic gene clusters in microbial genomes, expresses them in lab systems, and characterizes the resulting molecules, reporting over 200 previously uncharacterized small molecules per cycle versus an industry baseline of ~45. Most screening libraries draw from an estimated 3% of accessible chemical space, and Generare is betting that new chemistry from unexplored microbial genomes, not just more data from known chemistry, is what AI-driven drug discovery needs. The team of ~25 aims to scale output to 2,000+ molecules by 2027. Founded in 2023 by Guillaume Vandenesch and Vincent Libis.

🔹 Scala Biodesign, an Israeli computational protein design platform, raised $16M in a Series A led by Grove Ventures, joined by TLV Partners, Deep Insight, and the Israel Innovation Authority. The platform combines LLMs, physics-based modeling, and evolutionary data to help clients design and optimize proteins for biologic, enzyme, antibody, and vaccine therapies. It aims to become routine infrastructure across the full development pipeline rather than a one-off discovery tool.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

The EMA just issued its first draft qualification opinion for virtual control groups as a New Approach Methodology.

Context is rather narrow: rat dose-range finding studies, non-GLP, replacing concurrent control groups with virtual comparators built from historical data. It’s a narrow starting point, but it sets a regulatory blueprint for every study design where live controls exist by convention rather than scientific necessity.

Stefano Gaburro, who leads the Pistoia Alliance Minimal Metadata Set Working Group, noted that the real bottleneck was never the algorithm, but the metadata. Inconsistent annotation across institutions prevented historical control data from being pooled and reused. Pistoia’s MNMS framework, notes Stefano, was built specifically to create the data infrastructure that virtual control groups require. A cross-pharma proof of concept with five companies, using 24/7 home cage monitoring data, is ongoing. The EMA consultation runs until May 12, 2026.

Around the same time, Joseph Wu and colleagues published a review in Cell on NAMs for drug discovery, framing the evolution from 2D stem cell systems through 3D organoid models to AI-driven in silico platforms. The review argues that the next 30 years of drug development will see animal models transition from a central role to a supporting one, following the 3Rs principle, replaced increasingly by human-centric NAMs powered by multi-omics data and AI pipelines. Between the EMA opinion and this review, the regulatory and scientific architecture for reducing animal use in drug development is being built in parallel.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Bone marrow by the moon—NASA’s Artemis II mission is carrying AVATAR (A Virtual Astronaut Tissue Analog Response)—organ-on-chip devices containing bone marrow cells from crew members to study how deep space radiation and microgravity affect human health during the approximately 10-day lunar journey.

Bone marrow was selected for its radiosensitivity and centrality to immune function. The battery-powered payload, developed by Space Tango, will maintain automated environmental controls during flight. Upon return, Emulate researchers will use single-cell RNA sequencing to compare flight samples against ground-based controls. NASA has extended organ-on-chip viability to six months minimum to enable observation of long-term disease and treatment responses.

Share

🚀 A New Kid on the Dura

Epia Neuro launched from San Francisco this week with a minimally invasive brain-computer interface designed to help stroke survivors regain motor function by reading what the brain intends to do and translating that into movement.

The founder is Michel Maharbiz, who previously built iota Biosciences, a bioelectronics startup later acquired by Astellas. The team spans engineering and neuroscience, with backgrounds in both research and clinical system development.

Stroke is the entry point: roughly 690,000 cases annually in the U.S., with around 60,000 patients potentially eligible for device-based intervention. Epia plans first-in-human demonstrations with the Department of Neurosurgery at Lenox Hill Hospital.

The technical differentiator is a read/write architecture where the device can both record brain signals and deliver stimulation, spanning cortical and deeper brain regions. This contrasts with earlier generations of primarily read-only BCIs. The implant is placed within the skull without penetrating brain tissue via a roughly one-hour surgery. Onboard algorithms adapt to each patient’s activity patterns over time, with wireless recharging and upgradeable architecture built in for long-term use.

Early on, the device supports rehabilitation, reinforcing intended movements through feedback and stimulation while recovery is still possible. As recovery plateaus, it shifts into an assistive role, driving wearable external devices for tasks like gripping objects. The company is also signaling longer-term ambitions in cognitive decline, Parkinson’s, and neuropsychiatric conditions.

The BCI landscape we’re tracking is moving fast. Just last month we covered how Neuracle’s minimally invasive device became the first commercially approved BCI in China, followed by increased funding activity:

• StairMed raised $73M for its robot-inserted flexible electrode system;

• Gestala raised $21M for a non-invasive ultrasound-based platform.

• In the U.S., Merge Labs (backed by Sam Altman) raised $252M for ultrasound-based BCIs

• Nia Therapeutics received FDA breakthrough device designation for an AI-guided memory loss BCI

• Neuralink, the largest actor, plans high-volume production and a near-fully automated implantation workflow in 2026 following a $650M Series E.

We covered the broader neurotech landscape in our Neurotech Review here.

Subscribe now

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

Cancer as a Data Problem: What AI Is Doing in Oncology

GTC 2026 brought that energy straight into life sciences. NVIDIA CEO Jensen Huang's keynote framed agentic AI as the next platform shift, and the life sciences sector seems to be taking that literally. Agents are now everywhere you look: IQVIA rolled out over 150 of them across clinical and commercial workflows, Insilico added one for translational biology, Latent Labs has one designing antibodies from text prompts, and NVIDIA itself unveiled a full surgical robotics stack.

We now have two top pharma companies in an apparent compute arms race within the same quarter. Roche's 3,500+ Blackwell GPUs positioned as the largest announced pharma GPU footprint, right on the heels of Lilly‘s LillyPod supercomputer and its $1B co-innovation lab with NVIDIA announced at JP Morgan.

Startups are matching the energy: Xaira, backed by nearly $1 billion in funding, has now launched a 4.9-billion-parameter virtual cell model, Earendil, since our note of their plans for a ~$500M IPO last week, pulled in $787 million for AI-driven biologics, and the overall VC wave into AI-native bio keeps building. Speaking broadly of AI-native startups, Huang pointed to ~$150 billion in venture funding flowing their way last year.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 Roche launched its own large-scale AI computing hub for drug discovery, development, and manufacturing after buying 2,176 Blackwell GPUs (bringing its total capacity above 3,500), supporting model training, biological data analysis, lab-linked workflows, and factory digital twins.

🔹 AI reasons about protein function — Arc Institute researchers introduced a multimodal model for protein function prediction that combines protein embeddings with language-model reasoning, beating prior public benchmarks, generating step-by-step biological explanations, and earning preference over curated annotations in 79% of expert comparisons.

🔹 At GTC, UCL and partners unveiled what they describe as a first hybrid quantum-GPU biomolecular simulation pipeline, combining quantum hardware with 120 H100 GPUs to model a major drug-target protein class at realistic biological scale.

🔹 Xaira Therapeutics launched a 4.9-billion-parameter AI virtual cell model that predicts cellular responses to genetic perturbations, trained on 25.6 million perturbed single-cell transcriptomes and reported to generalize to unseen biological contexts.

🔹 Latent Labs, after coming out of stealth last February, launches an AI agent that designs therapeutic antibodies from text prompts in hours, reporting ~67% success with nanomolar affinities.

🔹 At GTC 2026, NVIDIA launched Proteina-Complexa, a generative protein binder design model accepted as an oral presentation at ICLR 2026, built on Proteina (ICLR 2025) and extending it to full atomistic binder design with inference-time compute scaling. Novo Nordisk, Manifold Bio, and Viva Biotech participated in wet lab validation. Other announcements also included a surgical robotics stack: Open-H (700+ hours of surgical video), Cosmos-H (synthetic surgical data generation), GR00T-H (vision-language-action model for clinical robotics), and Rheo (a simulation framework).

🔹 IQVIA launched a unified AI platform to support clinical, commercial, and real-world decision-making, with 150+ deployed agents, and 100+ AI patent filings.

🔹 Open-source protein design workflow — Dyno Therapeutics unveiled an open-source agentic AI suite for protein binder design that pairs generative models with lab-trained predictive filters.

🔹 Agentic AI for translational biology — Insilico Medicine launched a new AI analysis agent for therapeutic discovery that lets biologists use natural language to run multi-omics and bioinformatics workflows, drawing on 140+ scientific skills and 1,000+ tools.

🔹 To fix the experimental bottleneck, Arctoris opened a new biophysics center in the UK to generate drug-binding and protein-quality data at scale for AI-driven discovery.

🔹 Building a massive genomics dataset for AI — Basecamp Research launched a Trillion Gene Atlas to collect genomic data from 100+ million species, aiming to expand biological training data for AI models through global sampling.

🔹 AlphaFold adds protein interaction context — the AF database now includes 1.7 million predicted homodimer structures from an initial 30 million candidates, expanding beyond single proteins to capture how identical protein pairs may interact across 20 key organisms.

🔹 Automated labels can quietly worsen medical AI bias — Researchers found breast tumor segmentation models do far worse on younger patients for qualitative reasons, and training on machine-generated labels can amplify the disparity by ~40% while biased benchmarks can hide the damage.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 Earendil Labs raised $787 million to scale AI-driven antibody and biologics discovery, expand teams, and advance a pipeline of 40+ programs, including one program ready for Phase 2 and multiple regulatory filings planned for 2026-2027.

🔹 Neuracle‘s commercial approval triggered a funding wave across China’s BCI sector: Shanghai-based StairMed raised ~$73M for its robot-inserted flexible electrode approach, while Gestala pulled in $21M just two months after launch for a non-invasive ultrasound BCI platform.

🔹 Verily raised $300M and became an independent company, using the capital to expand its AI-ready health data platform, consumer health tools, and clinical/research agents while Alphabet shifts to a minority stake.

🔹 Rivia raised €13M to build AI agents for clinical trial operations, expanding its unified data platform to proactively flag risks, anomalies, and enrollment issues in regulated trial workflows.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Nia Therapeutics received FDA Breakthrough Device status for an AI-guided brain implant aimed at memory loss after traumatic brain injury, with a study reporting a 19% recall improvement by detecting poor memory-encoding states and delivering targeted stimulation.

🔹 Brain activity restored after deep freezing — researchers in Germany revived key functions in vitrified mouse brain slices after storage at up to −150 °C for as long as seven days, preserving neuronal firing, metabolism, and synaptic plasticity.

🔹 ReVision Implant won FDA Breakthrough Device status for a brain-stimulation visual prosthesis designed to restore functional vision in blindness beyond the retina, with planned surgical testing in October 2026.

🔹 Mind typing nears everyday speeds — Massachusetts General Hospital researchers enabled two people with paralysis to type on a standard digital keyboard using brain implants that decode imagined finger movements, reaching 22 words per minute with low error after training on just 30 sentences.

🔹 “No, we haven’t uploaded a fly yet”—scientists push back on viral claims of a digital fruit fly, arguing the demo stitched together existing brain and body models with pre-programmed behaviors, falling far short of true whole-brain emulation.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 FDA pushes shift beyond animal testing, issuing draft guidance to validate non-animal methods like organoids, lab models, and simulations for drug safety testing, aiming to replace animal studies with more predictive human-relevant data and speed clinical development.

🔹 NIH committed $150M investment in human-based research to reduce reliance on animal models, framed around its Complement-ARIE program.

🔹 arXiv’s move out of Cornell—Science reports it will become an independent nonprofit on July 1, 2026.

🚀 A New Kid on the Block

(Emerging startups with a focus on technology)

Former GSK AI Leaders Launch Stealth Oncology Startup — Shane Lewin and Nick Peterson, who both recently left GSK after six years building the pharma giant’s AI/ML and research data infrastructure, have co-founded Clockwork Bio (Lewin as CEO, Peterson as CTO).

The stealth-mode startup is building an AI-native platform for preclinical oncology drug discovery, arguing that conventional pipelines designed around heritable genetic targets fail for cancer, where disease is driven by epigenetic regulation, cell signaling, and lineage switching.

Their approach combines active learning, AI-based phenotyping, and emerging modalities to force cells between healthy and diseased states in vitro while learning the underlying biology at scale.

No funding or team details disclosed, formal product launch expected later in 2026.

Share

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

Cancer as a Data Problem: What AI Is Doing in Oncology

Caveat: the science of personalized oncogenomics isn't new, and the AI mostly helped a non-specialist navigate tools that already exist. This still required serious money and a lab willing to help, but the tooling is getting faster and more navigable even for non-specialists.

Meanwhile, Google’s diagnostic AI ran pre-appointment patient interviews at a real clinic—100 patients, no safety incidents, accuracy allegedly on par with primary care doctors. OpenFold Consortium now released its full training pipeline with datasets, weights, and training code.

On the money side: an AI-driven protein engineering startup Earendil is reportedly eyeing a Hong Kong IPO that could raise up to $500M. Breakout Ventures closed $114M for early-stage neuroscience and biomedical AI. Seemay Chou launched Radial, a $500M effort aimed at the scientific data infrastructure that AI tools depend on but nobody wants to fund. And Owkin spun out its diagnostics work as Waiv with $33M for oncology stratification.

Elsewhere: China cleared the first minimally invasive BCI for everyday home use. Researchers published a molecule-level simulation of a full bacterial cell cycle. Also—arXiv is separating from Cornell to go independent and is looking for a CEO.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 A pet owner used AI to build his dog a custom cancer vaccine and it worked. After surgery and chemo failed, an Australian engineer used ChatGPT to map a treatment plan, AlphaFold to identify tumor targets, and eventually convinced a university lab to manufacture a personalized mRNA vaccine in under two months.

🔹 Microsoft launched Copilot Health, a dedicated health companion that pulls together wearable data, medical records from 50,000+ US providers, and lab results into one place.

🔹 An AI doctor’s assistant just passed its first real-world test. Google‘s diagnostic AI conducted pre-appointment patient interviews at a real clinic—100 patients, zero safety incidents, and its diagnostic accuracy matched that of primary care doctors.

🔹 The OpenFold Consortium released the complete OpenFold3 training pipeline—datasets, weights, training and inference code—making this biomolecular complex prediction system fully reproducible and extensible and not just inference-accessible. Antibody-antigen prediction remains an open frontier and a stated 2026 priority.

🔹 AI beats specialists at rare disease diagnosis. A Nature-published agentic system integrating 40+ clinical and genomic tools outperformed experienced physicians, with traceable, evidence-linked reasoning; over 500 institutions signed up since its July 2025 launch.

🔹 Structural confidence scores don’t predict cellular function. A 12,000-design CAR-T binder benchmark found only 5.9% of AI-generated designs worked (rising to 10.6% with basic sequence filters) while standard metrics (pLDDT, ipTM, Rosetta) had near-zero predictive power. The core failure: RFdiffusion’s helix-heavy backbones combined with ProteinMPNN’s bias toward lysine/glutamate produce sequences that stall ribosomes in cells. The one top-performing team folded designs in full CAR context rather than isolation.

🔹 Weeks of compute compressed into hours. Schrödinger says it uses Google Cloud GPUs to screen billions of compounds in a single weekend.

🔹 A living cell, simulated molecule by molecule. Researchers built a complete 4D whole-cell model of a minimal bacterium covering gene expression, DNA replication, metabolism, and division across a ~100-minute cell cycle. Each simulated cell is unique due to stochasticity, and the model correctly predicts doubling time, ribosome counts, and daughter-cell variability.

🔹 Asimov Press published a beginner-accessible walkthrough on computational antibody design using BoltzGen.

🔹 BigHat Biosciences benchmarked 30+ protein language models for antibody design with wet lab validation and found that model choice matters less than how one uses it, and that even a few hundred experimental datapoints outperforms any zero-shot approach.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 AI drug discovery startup Earendil (combining generative protein engineering with wet lab work to develop biologics) is reportedly eyeing a Hong Kong IPO that could raise up to $500M, following Insilico Medicine‘s successful listing there last year. Partnerships with Sanofi, Wuxi XDC, and Wuxi Biologics already in place.

🔹 Breakout Ventures raised $114M for its third fund, targeting early-stage neuroscience and biomedical AI: lab automation, computational chemistry, and AI-powered research tools. Early bets include a lab robotics startup; their track record includes a $300M Halozyme acquisition and the first FDA-cleared rapid sepsis diagnostic.

🔹 DeepMind and MIT alumni raised $13.5M to build a platform that connects ideas across scientific fields, proposes testable hypotheses, and runs simulations before experiments.

🔹 Using salmonella to fight cancer. Salspera is raising $91M to fund a phase 3 trial of an engineered salmonella strain that delivers an immune-boosting signal directly into tumors, previously showing reduced tumor burden and improved survival in metastatic pancreatic cancer. A two-person team, an orphan drug tag, and a Nasdaq listing on the horizon.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 First invasive BCI for paralysis cleared for everyday use in China—a minimally invasive implant that sits above the motor cortex has been cleared for everyday home use in paralyzed patients, translating imagined hand movements into a robotic glove.

🔹 Large gene insertion without the toxicity. Massachusetts General Hospital researchers developed a genome editing approach using circular single-stranded DNA donors to achieve kilobase-scale gene integration, avoiding the immune response triggered by the double-stranded DNA donors traditionally required for large insertions.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 The internet’s preprint library is going independent. arXiv—the free platform hosting 2.7 million scientific papers that the entire AI and life sciences research world depends on—is separating from Cornell University to become an independent nonprofit, and is hiring its first CEO at ~$300K. The academic community’s main worry is that independence means paywalls eventually follow.

🔹 UK bets £500M on homegrown AI. The government’s new Sovereign AI fund launches April 16, with life sciences as a priority sector.

🔹 A Middle Eastern shipping lane could empty American pharmacy shelves. Nearly half of U.S. generic prescriptions come from India, which depends on the Strait of Hormuz for 40% of its crude oil—a key input for drug manufacturing. Current stockpiles give 30–60 days of buffer, but a prolonged closure would hit generics hardest, as thin margins leave little room to absorb rising fuel and petrochemical costs.

🚀 A New Kid on the Block

(Emerging startups with a focus on technology)

🔹 Owkin spun out its diagnostics arm as Waiv with $33M in fresh funding, focused on AI-powered patient stratification tests for oncology—both in clinics and clinical trials.

🔹 AI in science is only as good as the infrastructure beneath it. Researcher Seemay Chou launched Radial, a $500M organization focused on modernizing how scientific data is generated, shared, and built upon—the “unglamorous” infreastucture and tools AI needs to deliver real value. Early projects include better methods for capturing protein dynamics.

Subscribe now

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

Foundational and open source: Arc Institute published its Evo 2, a 40B-parameter genomic foundation model that can generate and analyze DNA sequences, in Nature, while French Raidium released an open-source foundation model for reading CT and MRI scans.

Meanwhile, a Neuralink co-founder pulled in $230M for a rice-grain-sized retinal implant, researchers uploaded a full fruit fly brain connectome into a simulated body and got it to move, and Japan approved the first iPSC-derived therapies for heart failure and Parkinson's.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 AI boosts drug manufacturing — Eli Lilly, led by CIO Diogo Rau, used AI-powered digital twins of its factories to optimize production and defect detection for its blockbuster GLP-1 drugs, enabling significantly higher output of its diabetes and weight-loss treatments.

🔹 Open-source radiology foundation model — Raidium released Curia-2, an open-source AI model for analyzing CT and MRI scans that detects ~200 radiological findings and achieved 88.6% accuracy on 3D imaging benchmarks, with a 2B-parameter version available on Hugging Face.

🔹 Generative AI for DNA design — Arc Institute, Stanford University, and NVIDIA published Evo 2 in Nature, a 40B-parameter open-source genomic foundation model that can generate and analyze DNA sequences, with experiments showing AI-designed sequences can alter chromatin accessibility in living cells.

🔹 Automating protein lead optimization — Dutch company Cradle released the CRADLE-1 framework on bioRxiv, a machine-learning system that automates protein lead optimization across modalities (antibodies, enzymes, peptides, vaccines, gene-editing systems), achieving ~90-95% success in meeting target product profiles in validated campaigns.

🔹 On-premise AI for drug discovery — Liquid AI and Insilico Medicine released a 2.6B-parameter foundation model designed to run on private pharmaceutical infrastructure, enabling tasks like molecular design, ADMET prediction, and retrosynthesis while keeping sensitive data on-premise.

🔹 AI-designed anemia drug enters clinic — Insilico Medicine announced that its AI-discovered oral therapy for chronic kidney disease–related anemia has begun Phase I trials after first patient dosing by TaiGen Biotechnology, following a licensing deal for Greater China rights in December 2025.

🔹 Cloud access to robotic labs — Ginkgo Bioworks launched Ginkgo Cloud Lab, a web-based platform where researchers can submit natural-language experiment protocols that AI agents translate into automated workflows executed on robotic lab infrastructure with 70+ instruments.

🔹 AI-enabled nanobody discovery — MindWalk Holdings launched the B Cell Llama platform, combining llama-derived VHH nanobody discovery with AI-guided candidate selection to develop bispecific antibodies and cell therapies, supported by a peer-reviewed study showing enhanced potency and cross-variant activity.

🔹 AI-driven small-molecule discovery — Ono Pharmaceutical expanded its collaboration with Congruence Therapeutics to discover small-molecule drugs for neurology and immunology using AI models that analyze dynamic protein structures and identify hidden binding pockets.

🔹 Dynamic AI models for biology — Sentinal4D, led by Chris Bakal, is developing AI systems trained on time-resolved 3D imaging of living cells to model cell behavior and drug responses, addressing limitations highlighted by Eli Lilly CEO Dave Ricks and AstraZeneca bioinformatics director Ming Tang that current AI relies mostly on static biological data.

🔹 AI smart goggles for labs — Stanford University and Princeton University researchers developed LabOS, an AI-powered smart-goggle system using NVIDIA vision-language models that watches scientists’ hands during experiments and guides protocols in real time to prevent mistakes and help novices perform like experts.

🔹 AI “virtual pharma” study — Stanford University researchers simulated a virtual drug company using ~37,000 AI agents to analyze 56,000 clinical trials, finding that drugs targeting cell-type-specific genes are 48% more likely to reach market and show 32% fewer adverse events.

🔹 Self-driving lab discovers new lipid designs — Researchers in a Cell study developed the LUMI-lab autonomous system that combines robotics and AI to explore 221,000 lipid candidates for mRNA delivery, discovering brominated lipid structures that improved delivery efficiency and achieved ~20% in vivo CRISPR editing in lung cells, with the platform’s code and hardware released open source.

🔹 FDA-cleared AI for early stroke detection — Harrison.ai received FDA clearance for an AI system that analyzes routine non-contrast brain CT scans to flag early signs of ischemic stroke and prioritize urgent cases for faster clinical review. Also: Harrison.ai expanded its imaging AI platform by adding AIRAmed, Koios Medical, Lunit, and Nanox AI, enabling hospitals to access multiple AI tools for X-ray, CT, MRI, mammography, and ultrasound through a single vendor-neutral infrastructure.

🔹 Amazon Web Services launched Amazon Connect Health, a suite of AI agents that automate tasks like patient identity verification, appointment scheduling, clinical note generation, medical coding, and summarizing patient histories for clinicians.

🔹 Generalist medical AI model — Harvard researcher Pranav Rajpurkar and collaborators introduced MedVersa in NEJM AI, a multimodal foundation model that analyzes medical images and clinical text to generate diagnoses and reports, outperforming several specialized systems and reducing radiology reporting errors and time in clinical tests.

🔹 AI for rare disease diagnosis — Nature study reports that the DeepRare agentic AI system integrates 40+ medical and genomic analysis tools to diagnose rare diseases with traceable reasoning, reportedly outperforming experienced physicians and attracting registrations from 500+ medical institutions since July 2025.

🔹 AI agents for bioinformatics infrastructure — recently launched Phylo introduced Biomni, an AI research agent that lets scientists run large-scale bioinformatics pipelines and models like AlphaFold using natural language while orchestrating GPU-heavy HPC workloads, massive datasets, and asynchronous jobs in specialized research environments.

AI, Generally:

🔹 Autonomous AI research loop — Andrej Karpathy open-sourced an AI agent that autonomously modifies training code and runs ~100 machine-learning experiments overnight on a single GPU using a fixed 5-minute evaluation loop, demonstrating how agentic systems can iteratively improve models with minimal human input through a simple Markdown-defined research strategy.

🔹 Limits of current AI reasoning — On the a16z podcast, Vishal Misra and Martin Casado discuss how modern deep learning systems optimize for Shannon entropy (statistical pattern prediction) but lack Kolmogorov-style causal mechanism discovery, arguing that current AI cannot generate Einstein-level scientific theories because it cannot extend its hypothesis space or perform counterfactual causal reasoning.

🔹 AI discoveries humans may not understand — Asimov Press highlights the emerging “legibility problem,” where increasingly autonomous AI systems could generate scientific discoveries beyond human comprehension, raising concerns about whether humans will be able to interpret, validate, or apply AI-generated knowledge.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 Retinal implant for vision restoration — Science Corporation, founded by Max Hodak (Neuralink co-founder), raised $230M Series C (total $490M) to commercialize a rice-grain–sized retinal implant that converts infrared signals from smart glasses into electrical stimulation, restoring partial vision in patients with degenerative eye diseases.

🔹 AI-driven microbiome modeling —Outpost Bio raised $3.5M pre-seed to build a “lab-in-the-loop” platform combining automated microbiology experiments with machine learning to model and predict changes in the human microbiome.

🚜 Market Movers

(News from established pharma and tech giants)

🔹 Tempus AI expanded a multi-year collaboration with Merck to use multimodal clinical and molecular datasets with AI analytics to identify oncology biomarkers, study treatment resistance, and guide precision medicine drug development.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Living neurons play video games — Cortical Labs demonstrated that ~200,000 lab-grown human neurons connected to microelectrode arrays can learn to play the video game Doom by translating game visuals into electrical stimulation and using neural activity to control in-game actions, highlighting early progress toward biological computing systems.

🔹 Embodied whole-brain emulation — reports how Eon Systems demonstrated a connectome-derived digital model of the entire fruit fly brain (~125k neurons, ~50M synapses) controlling a physics-simulated body to generate multiple behaviors, marking a milestone toward scalable brain emulation and future mouse- and human-scale digital brains.

🔹 First iPSC therapies approved — Cuorips and Sumitomo Pharma received Japan’s first approval for induced pluripotent stem cell–derived treatments targeting heart failure and Parkinson’s disease, marking the first commercialization of iPSC regenerative therapies.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 Leadership change at FDA biologics division —Vinay Prasad, director of the FDA’s Center for Biologics Evaluation and Research, will leave the agency at the end of April after a contentious tenure overseeing vaccines and gene therapies, with FDA Commissioner Marty Makary confirming a search for his successor.

Subscribe now

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

A newly launched U.S. brain health clinic network also raised $80M to bring psychiatric and neurological care, FDA-regulated clinical trials, and an AI-based coordination platform under one roof, combining in-person services with research infrastructure, with one site named after the late Dr. Nolan R. Williams, known for co-developing the FDA-cleared neuromodulation system.

According to the latest report, China biopharma licensing is no longer “cheap”. Generate:Biomedicines went public, raising $400M in its IPO and debuting at a valuation above $1B, though shares traded down after listing. Also, IQVIA said it will buy selected Charles River discovery assets to add in-vitro capabilities and a machine-learning small-molecule platform to its offering.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 Pharma-scale AI compute — Eli Lilly brought online its in-house AI supercomputer in Indianapolis with 1,000+ GPUs delivering ~9,000 petaflops, built to train biology/chemistry/genomics foundation models and support drug discovery and clinical development using ~700 TB of genomics data.

🔹 Shared standards for AI in biology — the international BEACON consortium, coordinated by the open-science nonprofit Conscience, launched to unify benchmarking across AI-driven disease biology and small-molecule discovery via community challenges, shared datasets, and an open validation platform, with a public debut at a Barcelona symposium on March 18–19, 2026.

🔹 Community-built AMR datasets — The Align Foundation and Google DeepMind launched a global effort to define AI-ready antimicrobial-resistance datasets and evaluation benchmarks.

🔹 Privacy-preserving ADMET modeling — Lundbeck, Orion, Recursion, Servier, and another drugmaker put ~80% of their internal ADMET data into a federated-learning network run by Apheris to improve absorption/metabolism/toxicity prediction without sharing raw proprietary datasets, initially for small molecules.

🔹 Scaling tissue AI models — Bruker and Noetik expanded their partnership to generate larger spatial single-cell human tissue datasets (building on 3,500+ patients) to train foundation models for translational and therapeutic use.

🔹 AI spots early diabetes tissue signals — Researchers at the German Center for Diabetes Research trained explainable deep-learning models on gigapixel pancreas slides from living donors to distinguish type 2 diabetes and pinpoint subtle structural changes (islet cell patterns, nerve fibers, and fat–islet proximity) that may serve as biomarkers.

🔹 AI to speed clinical trials — Evinova signed clinical-development AI partnerships with Astellas and AstraZeneca (after BMS) to use shared operational data to optimize trial design and execution, claiming ~5–7% cost savings per study.

🔹 AI planning for brain drug delivery — Brainlab and Precision NeuroMed partnered to build an AI-enabled planning platform for direct brain infusion to standardize patient-specific delivery, starting with recurrent glioblastoma and expanding to other CNS diseases.

🔹 Bo Wang, SVP and Head of Biomedical AI at Xaira Therapeutics, argues that diffusion models may be better suited than autoregressive models for biological foundation models, because biology (proteins, gene expression, regulatory DNA) is inherently bidirectional and high-dimensional rather than sequential like language. Separately.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 China licensing prices surge — Evaluate data show average upfront payments in Western–China biopharma licensing jumped 230% from $52M (2022) to $172M (2026 YTD) as deal volume and total upfront value rose, signaling China assets are no longer “cheap.”

🔹 Big AI-protein IPO, rough debut — Generate Biomedicines priced 25M shares at $16 to raise $400M to fund AI-designed protein medicines, led by two Phase 3 severe-asthma trials (~1,600 patients), although the stock fell ~21% after trading, valuing it at ~$1.61B (February 27th).

🔹 AI + in-vitro scale-up IQVIA will buy selected Charles River discovery assets for ~$145M (plus up to $10M), adding five in-vitro sites and a machine-learning small-molecule platform backed by 20+ years of data linked to 100+ clinical-trial molecules; closing Q2 2026.

🔹 No-code AI modeling for bench scientists — Tamarind Bio raised $13.6M Series A to scale a cloud platform used by ~100 biotechs (including “8 of the top 20 pharmas”) that lets lab teams run 200+ AI and simulation models for protein and small-molecule research without command-line or infrastructure setup.

🔹 Digital-cell models expand into immunology — Turbine raised $25M Series B to scale its AI “virtual cell” platform beyond oncology, launching an immunology collaboration with an undisclosed top-10 pharma and building on prior work with AstraZeneca, after supporting 30+ partner discovery programs.

🔹 Funding for organ-targeted gene delivery — BreezeBio raised $60M Series B to advance non-viral, tissue-targeted nanoparticle delivery and push its first genetic-medicine programs toward the clinic, starting with IND-enabling work in type 1 diabetes.

🔹 Recursion reported a $4M progress payment from Sanofi (total $134M to date) and $754M cash extending runway to early 2028, while saying the joint immunology-oncology small-molecule portfolio could grow to up to 15 programs. Separately, recent filings show NVIDIA sold its Recursion shares by Dec. 31, 2025 while ARK bought more.

🔹 Quantum-chemistry drug discovery funding — Ten63 Therapeutics raised $45M led by Chugai Venture Fund and the Gates Foundation to advance a quantum-chemistry-based small-molecule discovery model aimed at “undruggable” oncology targets, including MYC, starting with cervical cancer.

🔹 Record ALS research push — U.S. Congress approved a record $315M for ALS research in 2026.

🔹 AI deal for genetic epilepsy targets — Angelini Pharma struck a multiyear partnership with Quiver Bioscience worth up to $120M in milestones (plus royalties) to use AI-driven genomics and safety modeling to identify new therapies for rare pediatric genetic epilepsies.

🔹 DMD gene therapy launch in Japan — Sarepta’s Duchenne gene therapy began commercial sales in Japan (via Chugai/Roche) for ambulatory children 3 to <8 years, triggering a $40M milestone payment to Sarepta.

🚜 Market Movers

(News from established pharma and tech giants)

🔹 Pfizer and gene editing — Pfizer exercised its option for global rights to Beam’s liver-targeted in vivo base-editing program (from a $300M upfront collaboration with up to $1.05B milestones), while Beam also disclosed a $500M Sixth Street loan extending runway into mid-2029.

🔹 Big CAR-T buyout — Gilead agreed to buy Arcellx for $7.8B ($115/share + $5 CVR) to take full control of a BCMA CAR-T for relapsed/refractory multiple myeloma under FDA review with a Dec. 23 decision date.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Organoid-informed gene therapy enters clinic — Mahzi Therapeutics dosed the first patient in a Phase 1/2 trial of an AAV9 gene-replacement therapy for Pitt Hopkins syndrome (TCF4 mutations), enrolling ~12 participants across five sites in the U.S., Israel, and Spain.

🔹 Protein degradation via polymer “bridges” — Northwestern researchers created protein-like polymers that bind hard-to-drug cancer drivers and recruit the cell’s disposal machinery to degrade them, showing selective target removal and tumor-growth slowing in mouse models.

🔹 Single-molecule proteomics debuts — Nautilus unveiled its Voyager benchtop at US HUPO 2026 to map up to 10B intact proteins/proteoforms per run.

🔹 Rett gene therapy fast-tracked — Neurogene’s one-time Rett syndrome gene therapy received FDA Breakthrough Therapy status based on interim Phase 1/2 functional improvements, with registrational trial dosing expected to finish in Q2 2026.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 FDA one-trial default draws caution — FDA made a single pivotal trial the default for approvals beyond oncology/rare disease, but experts warn the change may mostly shift discretion and increase sponsor risk without clearer guidance. See how this could affect AI-enabled evidence packages in our recent coverage “FDA Shifts Drug Approval Policy: What Does This Mean for AI-Enabled Therapies?”

🔹 AI pathology distribution in the EU — Epredia signed an EU distribution deal to add Mindpeak’s on-prem AI image-analysis modules to its digital pathology offering.

🚀 A New Kid on the Block

(Emerging startups with a focus on technology)

🔹 AI-enabled brain health clinics — Salma Health launched with $80M Series A (Mubadala Capital and ARCH) to build an integrated U.S. network combining psychiatry/neurology care, FDA-regulated trials, and an AI care-coordination platform, starting with clinics in San Diego, Orange County, Fremont, and Berkeley.

Subscribe now

New AI-Native Biotechs: 2026 Watchlist

We’ve updated our AI-Native Biotechs Watchlist with fresh context on the FDA’s newly formalized “one pivotal trial” default and its explicit emphasis on mechanistic, real-world, and model-based “confirmative evidence” around that study. In the article’s framing, that shifts more weight onto things like validated biomarkers, external controls, real-world evidence, and computational work such as modeling, in-silico simulations, and synthetic comparators.

We scan a batch of newly launched startups built around those computational capabilities, spanning areas like RNA design, biomolecular modeling, regulatory DNA engineering, data imputation, lab automation, and structure-based drug discovery, with company-by-company notes on what each is building and what it reports so far.

AI-Native 2026 Watchlist

Why AI Won’t Automatically Accelerate Clinical Trials

Asimov Press just published a response to Dario Amodei’s “trials will take one year” speculation, arguing that better drug design does not automatically compress clinical trial timelines (Ruxandra Teslo with Asimov Press, Feb. 27, 2026). The piece separates two variables that often get blurred: whether a candidate works (trial success rate) versus how long it takes to run the experiment once it starts (trial speed).

It spends most of its time on why speed is bounded by things like recruitment, site operations, shipping logistics, regulator requirements, and biology itself, including the time it takes to observe endpoints.

The most concrete illustration is osteoporosis: despite a strong preclinical model (the ovariectomized rat) and high Phase III success reported as 83.7%, the author argues the field still struggles because Phase III trials tend to be enormous (10,000–16,000 participants), long (three to five years), and costly ($500M to $1B), largely due to fracture reduction being a slow, low-frequency endpoint.

The article also points to a 2015 oncology R&D analysis linking surrogate endpoint acceptance to investment patterns, and it frames better surrogate endpoints and regulatory process changes as the real levers, with AI helping “at the margins” via drafting, site selection, matching, and data workflows. It proposes a CTN-like approach (Australia’s Clinical Trial Notification framework) as an example of how early-phase work might move faster than the U.S. IND default, while still keeping safety oversight.

Read

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

Separately, a new benchtop sequencer announcement from San Diego kept the “falling sequencing costs” thread in view, which we framed in our recent ‘genomic watchpoints for 2026’.

We also saw a fresh Y Combinator entrant building an agentic drug platform on Google DeepMind’s Cell2Sentence single-cell foundation model, and compiled a short “New AI-Native Biotechs” list for a quick scan of new launches.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 Insilico Medicine shared its new ACS Central Science “Prompt-to-Drug” paper, outlining a “pharmaceutical superintelligence” architecture that orchestrates agentic AI plus automated labs to turn simple prompts into drug candidates—positioned as a foundation for its $100M partnership with Lilly.

🔹 Deep Origin and Arctoris were selected for the UK ARIA AI Scientist program to build an AI-enabled autonomous scientist for endometriosis, combining Deep Origin’s computational drug discovery with Arctoris’ robotic lab to iteratively plan, run, and analyze experiments with minimal manual input.

🔹 Flatiron launched AI-powered prostate cancer datasets spanning ~400,000 patients across the US, UK, and Germany.

🔹 Integrated Biosciences added Tony Wu (xAI co-founder) to its Scientific Advisory Board to strengthen its optogenetics-chemistry-AI platform for discovering small-molecule therapies for age-related diseases.

🔹 UK-based Bioptic published a paper on an agentic AI system for drug asset scouting that analyzes scientific, regulatory, and corporate sources to flag partnership targets and competitive risks, and reports early pharma BD adoption with a public specialty therapeutics company using it for diligence and portfolio intelligence.

🔹 Tran et al. (Science, Feb 2026) introduced MULTI-evolve, a lab-in-the-loop ML method that uses protein language models plus targeted double-mutant testing to learn mutation interactions and quickly design stronger multi-mutation proteins, delivering big gains across APEX enzymes, dCasRx, and an anti-CD122 antibody in fewer iteration cycles than traditional directed evolution.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 PitchBook expects biopharma VC to keep recovering in 2026 (report PDF), but in a more cautious, selective way: money is concentrating into fewer, bigger rounds for more proven, later-stage drug assets rather than early platform bets (2025 deal value: $33.8B; median early-stage round: $27M, up 77%).

🔹 After announcing upcoming Phase 3 data from its psilocybin trials in treatment-resistant depression, Compass Pathways launched a proposed $150M public offering, with an option for underwriters to purchase up to an additional $22.5M.

🔹 Korsana Biosciences emerged from stealth with $175M raised to advance its brain-shuttle platform, including lead Alzheimer’s candidate KRSA-028, a shuttled anti-amyloid beta antibody partnered with Paragon Therapeutics, with plaque-clearance data expected in late 2027.

🔹 Innovacell, a Tokyo-based cell therapy company, plans to IPO on the Tokyo Stock Exchange on Feb. 24, 2026, aiming to raise about ¥14.17B (~$92M) to support its Phase 3 program and build manufacturing/commercial infrastructure.

🚜 Market Movers

(News from established pharma and tech giants)

🔹 Unnatural Products (UNP) signed a research collaboration and licensing deal with Novartis to develop AI-designed macrocyclic peptide therapeutics for historically “undruggable” targets (with potential cardiovascular applications), with UNP eligible for up to $100M upfront/pre-IND, up to $1.7B in milestones, plus tiered royalties.

🔹 BostonGene and Daiichi Sankyo struck a strategic collaboration to use AI-driven multimodal “digital twin” analytics (multi-omics + histopathology) to support precision ADC development.

🔹 Merck and Mayo Clinic formed an R&D collaboration to combine Mayo’s de-identified multimodal clinical/genomic data and platform tools with Merck’s AI/ML capabilities to accelerate AI-enabled drug discovery and precision medicine, initially focusing on IBD, atopic dermatitis, and multiple sclerosis.

🔹 GE HealthCare expanded its BARDA partnership by ~$35M to advance AI-powered ultrasound tools for faster trauma assessment and mass-casualty emergency care.

🔹 Scribe Therapeutics and Eli Lilly hit a second milestone in their multi-program in vivo CRISPR collaboration for neurological and neuromuscular disorders, powered by Scribe’s X-Editor (engineered CasX) platform; financial terms weren’t disclosed, but the 2023 deal includes $1.5B+ in potential milestones plus royalties.

🔹 Boehringer Ingelheim has stopped testing and dropped its inhaled gene therapy for cystic fibrosis after an early clinical trial didn’t show results strong enough to keep going, even though it appeared reasonably safe.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Ultima Genomics launched its UG200 Series DNA sequencers and Solaris 2.0 workflows ahead of AGBT today, claiming up to 2x more output and ~50% faster runs than UG100, with shipments starting Q2 2026 and a Solaris 2.0 Max chemistry later in 2026 targeting up to 20B reads per wafer.

🔹 San Diego-based Element Biosciences unveiled a benchtop DNA sequencer that can deliver a whole genome for $100 (allegedly ~half the cost of Illumina’s NovaSeq) intensifying competition as the two companies battle in court over antitrust and patent claims.

🔹 An FNIH Biomarkers Consortium study in Nature Medicine found a “clock model” using a single blood p-tau217 test can predict Alzheimer’s symptom onset about 3-4 years in advance, alongside a new web tool to visualize biomarker trajectories for improved trial planning.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 The FDA is shifting its default drug-approval standard to one well-controlled pivotal trial, with additional “confirmative evidence” (e.g., validated biomarkers, mechanistic data, and real-world evidence) expected to support the application.

🔹 The Pentagon briefly added major Chinese firms (including WuXi AppTec) to its Section 1260H “Chinese military companies” list ahead of an expected Trump-Xi summit, then withdrew the Federal Register filing without explanation, leaving the designations in limbo and adding fresh uncertainty to US-China tech tensions.

🔹 A study tested whether chatbots help beginners do key lab steps needed to make a virus; surprisingly, people with LLM access did not do better than those using the internet alone (about 5% vs ~7% completed all tasks). Forecasters (especially “superforecasters”) had expected a much bigger boost, and after seeing the results they slightly lowered their estimates of near-term biosecurity risk, while noting that a future big jump in AI lab help could still raise risk.

🚀 A New Kid on the Block

(Emerging startups with a focus on technology)

🔹 CellType, a Yale University spinout, joined Y Combinator’s W26 (2026) batch to develop an agentic AI drug platform based on Google DeepMind's Cell2Sentence, a 27B-parameter single-cell foundation model that treats gene expression as a biological language to simulate human biology in silico.

Subscribe now

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

A few things worth prefacing with include Isomorphic Labs’ benchmarking of its drug design engine, Takeda’s multi-year AI drug discovery partnership with Iambic Therapeutics (note: last year, Iambic had early Phase 1 readouts for its AI-designed cancer drug), Generate:Biomedicines filing for an IPO, Lilly’s up to $2.4B Orna Therapeutics deal to enter in vivo CAR-T, and Sanofi’s fast-moving CEO change. To note—the launch of a new startup (backed by a16z/Menlo’s Anthology) and its “integrated biology environment” lab for running biomedical research.

We also had a new contribution piece from ICON plc on how digital health technologies are moving from pilots into core clinical development strategy, plus a short Women and Girls in Science Day roundup focused on prominent women working across the AI and life science stack.

For paid subscribers, we looked at the recent uptick in big pharma deals with China, and the prominence of advanced therapeutic modalities in recent headlines.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 Isomorphic Labs benchmarked its IsoDDE “drug design engine,” claiming it goes beyond AlphaFold 3 by better generalizing on hard protein–ligand cases (incl. cryptic pockets/induced fit) plus stronger antibody-antigen modeling and binding-affinity prediction to help rank pockets and candidates for drug discovery.

🔹 Takeda signed a multi-year AI drug-discovery partnership with San Diego-based Iambic Therapeutics worth up to ~$1.7B in milestones to apply Iambic’s generative small-molecule platform across oncology, GI, and inflammation. Iambic also disclosed a new $20M investment from Ireland’s ISIF (on top of an oversubscribed $100M financing) as it plans to expand engineering hires there.

🔹 Ginkgo Bioworks + OpenAI say a GPT-5-driven autonomous lab ran 36,000 experiments and cut cell-free protein synthesis costs 40% (to ~$422/gram) in a new preprint.

🔹 Terray Therapeutics updated its diffusion-free TerraBind potency model, claiming ~26x faster and lower-cost inference than diffusion approaches (e.g., Boltz-2) while improving correlation to experimental binding data, building on its EMMI platform’s recent Bristol Myers Squibb milestone.

🔹 Insilico Medicine and China Medical System (CMS) teamed up on AI-driven drug discovery in CNS and autoimmune diseases, planning to co-develop at least two programs using Insilico’s Pharma.AI plus CMS’s clinical/regulatory/commercial expertise. Insilico is set to receive R&D funding of “several tens of millions” HKD per program.

🔹 Unlearn will supply AI “digital twin” external comparators for VectorY’s single-arm PIONEER-ALS Phase 1/2 trial of VTx-002, an AAV gene-delivered anti–TDP-43 antibody, to strengthen efficacy readouts where placebo controls are hard to run.

🔹 Google DeepMind’s AlphaGenome authors (YouTube roundtable) explain their Nature-published DNA sequence-to-function model for decoding the 98% non-coding genome, released in June 2025, highlighting long-context (up to ~1M bp) high-resolution TPU breakthroughs and an API to rapidly score variant effects for disease research.

🔹 San Francisco-based Tahoe Therapeutics says it’s building the largest single-cell atlas of cell-chemical interactions by combining INTEGRA automated pipetting with Parse Biosciences’ scRNA-seq and its own AI.

🔹 In Nature Medicine, researchers introduce SleepFM, a multimodal sleep foundation model trained on ~585,000 hours of polysomnography from 65,000+ people that can predict future risk for 130 diseases from a single night (e.g., mortality C-index 0.84, dementia 0.85, MI 0.81).

🔹 Anthropic partnered with HHMI (Janelia/AI@HHMI) and the Allen Institute to embed Claude-powered agents into lab workflows for experiment interpretation, hypothesis generation, and multimodal/omics analysis, with real-world feedback guiding future Claude research versions.

🔹 Inductive Bio won the OpenADMET-ExpansionRx blind challenge with its Beacon ML models, topping 370+ submissions by predicting nine ADMET endpoints on unseen compounds from real discovery programs.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

💰 QuantX Biosciences closes an oversubscribed $85M Series B co-led by LAV and Sanofi Ventures to push its oral STAT6 and IL-17 small-molecule inhibitors toward the clinic, powered by a computational discovery platform that blends physics-based modeling, statistical/AI methods, and high-performance computing to design and optimize drug candidates.

🔹 Pfizer joins Basel-based BaseLaunch as its 7th pharma partner, expanding the incubator’s support network for early-stage biotech creation through Series A. BaseLaunch says its 27 portfolio companies have raised $1B+ collectively, with several already in Phase II.

🔹 Biotech IPOs look to be thawing in early 2026 (e.g., Aktis $318M, Eikon $381M, Agomab $200M), with PitchBook-linked estimates pointing to ~30–35 biotech IPOs in 2026 vs 11 in 2025 as investors favor clinical-stage/product-led stories.

🔹 Colossal Biosciences struck a “nine-figure deal” with the UAE to build a Dubai BioVault and lab at the Museum of the Future, aiming to store genetic material from 10,000+ species (millions of samples) as part of a planned global network of biodiversity “backup” vaults.

🔹 Flagship’s Generate:Biomedicines (an AI/ML-driven protein + antibody design company) filed to pursue an IPO to fund Phase 3 severe-asthma studies of its long-acting anti-TSLP antibody GB-0895.

🚜 Market Movers

(News from established pharma and tech giants)

🔹 Lilly is buying Massachusetts-based Orna Therapeutics for up to $2.4B to enter in vivo CAR-T, using Orna’s circular RNA + lipid nanoparticle platform led by CD19 program ORN-252 for B-cell autoimmune diseases.

🔹 Sanofi is replacing CEO Paul Hudson with Merck KGaA CEO Belén Garijo (interim CEO Olivier Charmeil from Feb 17; Garijo starts Apr 29).

🔹 FDA refused to file Moderna’s mRNA flu shot application over trial design/comparator concerns, and Moderna publicly pushed back while warning it could complicate its combo flu-COVID plans.

🔹 Google DeepMind says Gemini Deep Think plus an agentic “verifier-reviser” workflow (Aletheia) can tackle research-level math/CS/physics problems—reporting progress from IMO/ICPC-level results to papers and case studies where the system iteratively checks, fixes, and sometimes refutes conjectures using literature/web-assisted reasoning.

🧬 Gene Therapy Lane

In vivo cell/gene therapy was a major theme at Advanced Therapies Week in San Diego, with speakers citing easier access vs ex vivo (potentially avoiding lymphodepleting chemo) and pointing to momentum from deals like Lilly’s $2.4B Orna buy and Regeneron-Tessera, though many cautioned investment is running ahead of human data.

Negatives

➖ FDA put Regenxbio’s MPS I (RGX-111) and MPS II/Hunter (RGX-121) gene therapy trials on hold after a child developed a brain tumor found on MRI 4 years post-dose (preliminarily linked to AAV integration/PLAG1 overexpression). The agency also sent a Feb 7 CRL for RGX-121, citing trial design/external control and surrogate endpoint concerns and asking for more/longer controlled data.

➖ Lilly dropped three clinical-stage programs, including Prevail’s GRN gene therapy for frontotemporal dementia for lack of efficacy.

➖ uniQure paused dosing of its AAV gene therapy in the mid- and high-dose cohorts after two patients had asymptomatic Grade 3 liver enzyme elevations that improved with steroids.

Positives

➕ Vertex and CRISPR Therapeutics expect Casgevy to ramp in 2026, projecting ~3x higher sales as more patients move through the infusion pipeline and insurance coverage reaches ~90% of eligible U.S. patients.

➕ Madrigal licensed six preclinical liver-targeted siRNA programs for MASH from China’s Ribo Life Science (and Sweden’s Ribocure) for $60M upfront plus up to $4.4B in milestones, aiming to pair gene-silencing therapies with its THR-β drug Rezdiffra.

➕ Ultragenyx reported UX111 gene therapy shows sustained cognitive/functional benefits in Sanfilippo A with up to ~8.5 years follow-up across two studies, and the company resubmitted its FDA application (previously CRL’d on CMC/manufacturing issues) expecting a ~6-month review.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Northwestern researchers built an advanced human spinal cord organoid injury model and showed their “dancing molecules” supramolecular therapy boosted neurite outgrowth and reduced glial scarring in injured organoids, supporting its translational potential after prior paralysis-reversal results in animals.

🔹 SK bioscience began a Phase 1/2 trial in Australia of GBP511, a UW Institute for Protein Design nanoparticle vaccine that displays pieces of four coronaviruses to target sarbecoviruses (incl. COVID-19), backed by ~$65M from CEPI.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 Next-gen obesity drugs like Novo Nordisk’s CagriSema and Lilly’s triple-agonist retatrutide are showing ~23–30% weight loss in trials—potentially beating Wegovy/Zepbound—but clinicians warn “too much, too fast” loss may raise risks like gallstones and muscle loss.

🔹 The U.S. Department of Energy launched the Genesis Mission Consortium, a public-private partnership to speed AI-driven scientific discovery via working groups on AI models, data standards, HPC/cloud, and robotics/automation, administered by TechWerx (RTI).

🔹 HHS/BARDA and VITAL launched a $100M SMART Prize to spur broad-spectrum small-molecule antivirals for Togaviridae/Flaviviridae viruses (e.g., dengue, Zika, West Nile, chikungunya), with submissions due May 11, 2026.

🚀 A New Kid on the Block

(Emerging startups with a focus on technology)

🔹 Stanford spinout Phylo launched with a $13.5M seed round (a16z + Menlo’s Anthology, with Anthropic) and unveiled Biomni Lab, an “Integrated Biology Environment” that uses agentic AI to run biomedical research workflows across connected tools and databases.

Subscribe now

Women and Girls in Science Day, Seen Through the AI-Life Science Stack

For February 11, the UN-designated International Day of Women and Girls in Science, themed «Synergizing AI, Social Science, STEM and Finance», we put together a quick, tech-forward roundup of women working across the AI and life science interface, spanning research, product-building, and capital decisions.

Featured: Daphne Koller (Founder and CEO, insitro), Alice Zhang (Founder and CEO, Verge Genomics), Suchi Saria (Founder, Bayesian Health; Director, Machine Learning and Healthcare Lab, Johns Hopkins), Regina Barzilay (Professor, MIT CSAIL; AI faculty lead, MIT Jameel Clinic), Jen Asher, Ph.D. (Founder and CEO, 1910 Genetics).

Also: Dr. Najat Khan, PhD (CEO and President, Recursion), Michelle Lee (Founder and CEO, Medra), Dr. Charlotte Bunne (EPFL), Dr. Effy Vayena (ETH Zurich), Dr. Marzyeh Ghassemi (MIT), Dr. Emma Pierson (UC Berkeley), Dr. Finale Doshi Velez (Harvard).

These names are by no means exhaustive and many other women are shaping how AI enters biology and medicine in equally substantive ways. We hope this serves as a small acknowledgment of that work and as encouragement for more women to lead in the sciences.

Company Watchlist: AI for De-Risking Clinical Trials

Clinical development still runs into an asymmetry of only around one in ten drug candidates that enter human testing reaching approval, and Phase II and III failures account for a lot of wasted R&D spend. In this watchlist, we look at AI’s attempt to use more of the signal that existing de-risking methods can leave on the table.

We profiled a few companies to watch in 2026 across three layers of this “de-risking” stack:

• how studies are designed

• how control evidence is assembled

• how trials are run and analyzed operationally

Read

ICON plc on Digital health Tech in Clinical Development

This contribution piece from ICON plc authors Caprice Sassano and Keith Thomas argues that digital health technologies (DHTs) are moving from pilots into core trial strategy, in a context of rising costs and increasingly complex timelines. The authors link that shift to regulators encouraging patient-centric designs and real-world data, and they frame the practical question as less “if” and more “how” DHTs get integrated.

Their concrete example is SV95C, stride velocity 95th centile, described as the first wearable-derived primary digital endpoint used in Duchenne muscular dystrophy trials, captured with an ankle-worn sensor. The authors contrast this with the six-minute walk test as a point-in-time clinic assessment, and they point to the EMA’s 2023 acceptance of SV95C as a milestone for digital endpoints.

Read

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

On the tech side, DeepMind’s AlphaGenome, an AI model built to read long stretches of DNA and predict how even single-letter changes may affect gene regulation, moved into the peer-reviewed record with a Nature publication.

Also, a joint report involving 14 pharma companies offered a snapshot of where generative AI is already being used in R&D, highlighting what governance and validation questions are still unresolved. Market-wise, there were early signs of thawing sentiment in the UK, with some biotechs reportedly reopening the IPO conversation and pointing to Nasdaq as a 2026 target.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 DeepMind’s AlphaGenome now peer-reviewed in Nature — first unveiled in June 2025, AlphaGenome is now published, reporting its ability to predict regulatory effects of non-coding variants across long DNA regions, aiding rare disease research and synthetic DNA design.

🔬 Japanese Chugai discontinued its only AI-optimized antibody after Phase 1, but reaffirmed confidence in its in-house Malexa platform, aiming to embed AI across discovery and operations.

🔹 Digital health tech moves from pilot to core — In a new ICON article on our main website, Caprice Sassano and Keith Thomas explore how digital health technologies—like wearables and sensors—are reshaping clinical trials, offering faster timelines, richer real-world data, and growing regulatory acceptance of digital endpoints.

🔹 Pharma roundtable assesses GenAI in R&D — A joint report in Science Direct from 14 pharmaceutical companies outlines current uses of generative AI in research and development, including document drafting and statistical programming, and examines future directions, governance, and validation needs.

🔹 AI boosts cancer detection while reducing workload — In a Swedish trial of ~100,000 women, combining AI with one radiologist improved breast cancer screening by detecting ~29% more cancers and reducing reading workload by ~44%, with similar false-positive rates and fewer aggressive interval cancers after 2 years.

🔹 AI modeling targets early kidney disease — BioMed X and the Barbados government launched a project to model early diabetic kidney disease using deep molecular profiling and AI, aiming to build a population-specific digital African twin to improve biomarker discovery and personalized care.

🔹 Unlearn debuts AI workspace for clinical trial planning — releasing a new AI tool to streamline early trial design by linking precedent data, benchmarks, and simulations in a single workflow to support faster, evidence-based decision-making.

🔹 Simplified AI pipeline wins protein binder design challenge — a 180-line method using Boltz-2 loss and unified folding/ranking reportedly outperformed traditional multi-stage workflows in the Adaptyv Nipah binder competition, suggesting simpler.

🔹 AI-ready proteomics targets Parkinson’s protein — Nautilus, Weill Cornell–Qatar, and the Michael J. Fox Foundation launched a $1.6M program to develop a single-molecule assay for alpha-synuclein proteoforms to improve early diagnosis and treatment of PD.

🔹 Oath Surgical partners with Nvidia to power AI-driven surgery centers — Oath Surgical will use Nvidia’s AI infrastructure to enhance its outpatient surgery platform, enabling real-time analysis of surgical data and automating documentation across its growing network of ambulatory centers.

🔹 AI accelerates CRISPR control — Researchers from Monash and Melbourne used AI to design synthetic anti-CRISPR proteins that rapidly and precisely inhibit Cas13a activity.

🔹 NVIDIA and Innophore launched CavitOmiX, an AI platform predicting drug interactions and repurposing opportunities at scale.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 Biopharma M&A shifts toward platforms and vertical integration — Bain’s 2026 report highlights four trends reshaping pharma dealmaking: focus on owning the value chain, next-gen obesity drugs, ADC-driven oncology deals, and strategic alliances with China’s maturing pharma pipeline.

🔹 AstraZeneca signs $18.5B obesity drug deal with China’s CSPC — One day after pledging $15B in China by 2030, AstraZeneca agreed to pay CSPC $1.2B upfront and up to $17.3B in milestones for ex-China rights to eight obesity drug programs, following a separate $5.3B AI-driven drug discovery deal in 2025.

🔹 Eli Lilly has teamed up with Seamless Therapeutics to develop gene therapies using recombinase enzymes, aiming for precise gene insertion without CRISPR, marking a major step in post-CRISPR editing strategies.

🔹 Insilico signs $120M cardiometabolic drug deal with Qilu Pharma — Insilico will apply its Pharma.AI platform to design small molecules, while Qilu leads development and commercialization; also, Insilico nominated AI-designed GIPR antagonist for obesity as a preclinical candidate.

🔹 AI-native Formation Bio licenses drug from China — Formation Bio acquired ex-Greater China rights to a miR-124-targeting small molecule from Jiangsu Chia Tai Feng Hai, aiming to rival Abivax in inflammation, with a Phase 1 trial planned for 2026 and up to $500M in milestones.

🔹 UK-based Automata raised $45M in Series C and formed a strategic partnership with Danaher to scale its AI-native lab automation platform

🔹 Flagship Pioneering’s Repertoire Immune Medicines signed a partnership with Eli Lilly worth up to $1.9B to develop targeted autoimmune therapies using its immune mapping platform, joining earlier deals with BMS, Genentech, and Pfizer.

🚜 Market Movers

(News from established pharma and tech giants)

🔹 Sanofi drops mRNA seasonal flu vaccine program citing strategic refocus, though it remains committed to mRNA for pandemic strains and continues to grow its vaccine business with recent acquisitions.

🔹 Merck ends $30B acquisition talks with Revolution Medicines after failing to agree on price, though future talks or competing bids remain possible as key trial data is expected this year.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 FDA greenlights first human trial of epigenetic reprogramming — Life Biosciences, co-founded by David Sinclair, received FDA approval to test a gene therapy aiming to partially reset the epigenome in patients with vision loss, marking a major milestone for the longevity field.

🔹 Organoid models in rare disease research — iXCells and Rosebud Biosciences partnered to integrate AI-driven organoid platforms with iPSC technology.

🔹 Synthetic phages engineered to fight superbugs — NEB and Yale developed a fully synthetic system to create bacteriophages targeting drug-resistant P. aeruginosa, streamlining customization and accelerating therapeutic development using Golden Gate Assembly.

🔹 Organoids reveal shared autism pathways — Using brain organoids from 70 patient-derived stem cell lines, UCLA and Stanford researchers showed that diverse autism-linked mutations converge on common molecular pathways during early brain development, highlighting potential targets for future therapies.

🔹 Chinese startup launches noninvasive brain-computer interface using ultrasound — Gestala aims to treat conditions like chronic pain and depression by stimulating the brain with focused ultrasound, eventually developing wearable devices to both read and modulate brain activity without implants.

🔹 Soft 3D transistors mimic neural tissue for bioelectronics — Researchers at the University of Hong Kong developed the first soft, 3D hydrogel-based transistors capable of hosting living cells, offering a breakthrough in integrating electronics with biological systems for future medical and neurotechnology applications.

🔹 Neuralink expands BCI trials to 21 participants — Neuralink’s brain-computer interface, Telepathy, is now being tested by 21 people with paralysis, enabling thought-based control of cursors, robotic arms, and typing up to 40 WPM, as the company prepares hardware upgrades and broader clinical rollout.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 British biotechs are showing renewed interest in public listings, with some eyeing Nasdaq in 2026 after a years-long IPO freeze, driven by strong M&A, rising investor optimism, and supportive policy shifts.

Subscribe now

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

On the healthcare AI side, OpenEvidence, with its “ChatGPT for doctors”, raised again and is now being priced around a $12B valuation. In Europe, against a tense global backdrop at Davos, Ursula von der Leyen announced “EU-Inc.” as a push toward a single, digital-first company setup across member states, a corporate-structure project that founder and investor groups have been publicly pushing since 2024.

AI drug developer Insilico Medicine got another FDA IND for a brain-penetrant NLRP3 program, also rolling out “Science MMAI Gym,” a training and evaluation framework it says can tune general LLMs for pharma R&D, pitched as a membership offering for external partners. A bit earlier, another gen-AI drugmaker Absci released an antibody design model built to iterate with rapid wet-lab feedback.

Hi! This is BiopharmaTrend’s weekly newsletter, Where Tech Meets Bio, where we explore technologies, breakthroughs, and cutting-edge companies.

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe now

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 Isomorphic Labs and J&J join forces on AI drug discovery — Alphabet-backed Isomorphic Labs partnered with Johnson & Johnson to apply AI to multi-modality drug design, targeting hard-to-drug diseases. Isomorphic now expects to begin human trials of its AI-designed drugs by the end of 2026, a year later than previously planned.

🧬 Basecamp Research reportedly achieves programmable gene insertion — In a preprint, the UK-based biotech describes an AI model, EDEN, developed with Nvidia and trained on 9.7T biological tokens, that enables targeted insertion of large DNA sequences into the human genome. The team reports lab data showing >90% tumor clearance using CAR T cells modified with this approach, and high success rates designing novel antimicrobial peptides. EDEN is presented as a potential advance beyond current CRISPR-based editing limits.

🔹 Insilico Medicine expands AI drug discovery push with $66M CNS deal and new LLM training platform — Insilico partnered with Hygtia to co-develop an AI-designed brain-penetrant NLRP3 inhibitor for neurodegenerative diseases, while also launching Science MMAI Gym to transform general LLMs into pharma-grade scientific engines.

🔹 Recently, Absci debuted new antibody design model, targeting hard-to-drug proteins — Absci launched Origin-1, a protein design model using rapid wet-lab validation to tackle elusive targets like GPCRs, with clinical trials underway for hair loss and endometriosis and a two-year, low-cost development cycle.

🔹 Europe launches €60M LIGAND-AI project for drug discovery — a 5-year, EU-funded initiative led by UCL, Pfizer, and the Structural Genomics Consortium brings together 18 partners across 9 countries to advance AI-driven drug design.

🔹 Tempus launches AI tool to guide cancer test decisions — Following its $81M acquisition of Paige AI, Tempus unveiled Paige Predict, an AI-powered pathology tool that analyzes tissue slides to predict biomarker presence, optimizing molecular test selection across 16 cancer types.

🔹 Lantern Pharma received its third orphan designation for LP-284, this time for soft tissue sarcomas, expanding its AI-driven oncology pipeline targeting DNA repair deficiencies in rare and aggressive cancers.

🔹 Following its $200M Series C early this year, Soley Therapeutics published research introducing its “Live Cell Dynamics” platform—a machine learning-powered, label-free imaging approach that captures how cells dynamically respond to drug stress over time.

🔹 SF-based Elucidata launches AI Lab to tackle edge-case failures in biomedical AI — Aiming to address out-of-distribution data issues in drug discovery and diagnostics, Elucidata’s new AI Lab will develop tools to detect and operationalize rare biological signals.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 “ChatGPT for doctors” raises $250M at $12B valuation — OpenEvidence secured a $250M Series D to expand its AI-powered medical search engine, now used in over 10,000 U.S. care centers and supporting 18M monthly consultations by 40% of physicians.

🔹 UK backs autonomous lab research — The UK’s ARIA agency awarded ~£500K each to 12 teams (incl. Lila Sciences) to develop AI scientists that can autonomously design, run, and analyze lab experiments.

🔹 BIOMAKERS raises $8M to scale AI oncology platform — The San Francisco company secured funding to expand its AI-driven precision oncology infrastructure and clinical-genomic dataset across 20+ countries, supporting drug and diagnostic development.

🔹 Florida-based Neuropacs secured over $1M in seed funding to expand its MRI-based AI platform for diagnosing Parkinson’s and related disorders, aiming for broader clinical adoption.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 Aspect Biosystems and Novo Nordisk expand partnership for 3D-printed diabetes implants — Vancouver-based Aspect gained access to Novo’s stem cell and immune-shielding tech to develop implantable pancreatic tissue, advancing a potential type 1 diabetes cure using its AI-driven bioprinting platform.

🔹 Scribe Therapeutics to trial one-time CRISPR therapy for high cholesterol — will begin Phase 1 trials in mid-2026 for a gene-silencing therapy targeting PCSK9, aiming to durably lower LDL cholesterol without cutting DNA.

🔹 Biomimetic brain model matching animal learning — MIT, Dartmouth, and Stony Brook researchers built a biologically realistic digital brain model that learned a visual task like lab animals and uncovered overlooked neurons tied to errors, offering a new tool for understanding cognition and testing neurotherapeutics.

🔹 Teitur to use NeuraLight’s digital biomarkers in Parkinson’s trial — Teitur will integrate NeuraLight’s eye-movement-based brain function measures, powered by computer vision and neural signal analysis, to track drug impact on neural circuits in its upcoming TT-P34 trial.

🔹 Gut neurons and epithelial cells team up to drive immunity — New research in Nature shows TRPV1+ sensory neurons activate tuft cells to trigger parasite expulsion and tissue remodeling, revealing a neuroimmune circuit uncovered by Weill Cornell and Allen Institute researchers.

🔹 a16z: Genetic ‘Surgery’ May Need New Rules — In a case likened to a medical moonshot, a baby with a rare mutation was cured using a bespoke gene-editing therapy tailored to his DNA. a16z’s Jorge Conde argues for a new regulatory framework, akin to CLIA labs for diagnostics, that treats such precision genetic interventions as customizable procedures, not one-size-fits-all products, to unlock access for ultra-rare disease patients.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 Von der Leyen announced ‘EU-Inc.’ to unify startup rules across Europe — At Davos, the European Commission unveiled EU-Inc., a long-awaited initiative to create a single, digital-first corporate structure enabling companies to register in 48 hours and scale across borders, aiming to close the tech gap with the U.S. and China.

🔹 EU launches FAST‑EU pilot to speed up clinical trial approvals — Starting 30 January 2026, the initiative will streamline multi-national trial assessments as part of broader EU efforts to strengthen clinical research and prepare for the upcoming EU Biotech Act.

🔹 FDA and EMA align on AI standards in drug development — U.S. and European regulators issued joint guidance on responsible AI use across the drug lifecycle, emphasizing data integrity, traceability, and auditability, especially in manufacturing and quality oversight.

🔹 FDA proposes new pathway for individualized genetic therapies — a multi-author editorial in Molecular Therapy supports the FDA’s proposed framework for customized genetic treatments, advocating for standardized, platform-based development of therapies like ASOs and gene editors to treat ultra-rare mutations, with shared data infrastructure to accelerate collective learning.

Subscribe now

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 AI revives stalled drug program — Takeda is embedding AI across drug discovery after Boston AI partner Nabla helped rescue a failing preclinical antibody.

🔹 ByteDance challenges AlphaFold with new protein folding model — The TikTok maker’s SeedFold builds on AlphaFold 3 and sets new benchmarks on FoldBench, inheriting an AlphaFold3-style architecture while widening the Pairformer and introducing linear triangular attention.

🔹 Tahoe Therapeutics, Arc Institute, and Chan/Zuckerberg’s Biohub have partnered to create the largest open dataset for virtual cell modeling, combining 120M single-cell profiles and 225K drug-patient perturbations for AI models of cellular behavior and treatment response.

🔹 Recursive Language Models reframe AI reasoning limits — Bo Wang (Xaira Therapeutics, UHN) highlights how Recursive Language Models (RLMs) challenge the belief that long-context AI reasoning is just a memory problem, instead enabling scalable, structured thinking by programmatically decomposing tasks rather than ingesting more data (an approach his team is testing in clinical trial applications).

🔹 Industrializing tissue replacement — Cambridge-based Cellino and Polyphron partner to combine AI-driven iPSC manufacturing with autonomous tissue engineering to scale personalized regenerative therapies through end-to-end, reproducible production systems.

🔹 Natera partners with NVIDIA to train large-scale foundation models on longitudinal oncology datasets for improved diagnostics, immunotherapy prediction, and biomarker discovery with high-performance AI infrastructure.

🔹 Leadership moves in AI-Driven biotech — Novo Nordisk appointed Anja Leth Zimmer as its first Chief AI Officer; BioMarin named Arpit Davé as Chief Digital and Information Officer, and Rune Labs tapped former Tempus executive Amy Gordon Franzen as CEO to lead expansion of its AI neurology platform.

🔹 CytoReason launches LINA, an NVIDIA-powered AI agent built on computational disease models to generate reproducible analyses and insights.

Subscribe now

🚜 Market Movers

(News from established pharma and tech giants)

🔹 Google expands medical AI suite with imaging and speech models — releasing MedGemma 1.5 for high-dimensional medical imaging and MedASR for speech recognition, alongside a $100K Kaggle hackathon centered on open-source clinical AI development.

🔹 Pfizer taps SF-based Gordian Bio’s in vivo and ML platform for obesity targets — to screen gene targets in visceral fat using its in vivo mosaic platform and Pythia machine learning engine to identify therapeutic interventions for obesity with tissue-specific precision.

🔹 BMS taps Immunai’s AI to decode immune responses — Bristol Myers Squibb partners with US-based Immunai to analyze clinical trial data using its AI-powered immune atlas; Immunai now provides free single-cell multi-omic profiling to Mount Sinai, Weill Cornell, and Massachusetts General Hospital.

🔹 Illumina launches Billion Cell Atlas for AI drug discovery — launching the first phase of a 5-billion-cell CRISPR perturbation dataset, partnering with AstraZeneca, Merck, and Eli Lilly to train AI models and validate genetic drug targets across hard-to-treat diseases.

🔹 Insilico Medicine brings AI drug discovery model to Microsoft platform — integrating its Nach01 foundation model with Microsoft Discovery to enable scalable, AI-native workflows for molecular design and predictive analysis in drug discovery.

🔹 JPM 2026: CEOs of Novo Nordisk, BMS, and Pfizer lay out their bets — Novo Nordisk’s Mike Doustdar called 2026 a “year of price pressure,” citing the Trump administration’s GLP-1 pricing deal and growing competition. Bristol Myers Squibb’s Chris Boerner previewed 10 potential product launches by 2030, with 11 key readouts expected this year. Pfizer’s Albert Bourla reaffirmed the company is “all in on obesity,” with 10 late-stage trials planned for Metsera assets and strong expectations from the growing cash-pay market.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 Nearly $1B in new biotech VC funds launch globally — Andreessen Horowitz commits $700M to U.S. biotech innovation with a focus on AI applications, while Germany’s BioNTech and Penn back a $50M fund for Pennsylvania startups, and France’s Servier launches a €200M fund targeting European oncology and neurology firms.

🔹 Denmark’s Novo Nordisk Foundation will invest ~$856M over nine years into BioInnovation Institute to expand life sciences and AI-driven startups across Europe, scaling its support beyond Denmark and into quantum and reproductive health.

🔹 AstraZeneca acquires Boston’s Modella AI to embed foundation models and AI agents across its global cancer pipeline for biomarker discovery, pathology analysis, and trial design through multimodal data integration.

🔹 OpenAI acquires health records startup Torch for reported $100M — Torch built a “medical memory” that unifies fragmented health data for AI use. Its four-person team joins OpenAI to support ChatGPT Health, a new initiative aimed at helping users analyze and manage personal health through the chatbot.

🔹 Nuclera extends Series C to $87M for antibody engineering platform — UK- and US-based company raises an additional $12M to expand its eProtein Discovery system with full-format antibody expression and validation, aiming to generate high-quality datasets for AI-driven biologics discovery.

🔹 $80M for AI-driven protein interaction drugs — New York-based Proxima raises $80M to develop proximity-based medicines using generative AI and structural proteomics to design small molecules that modulate protein-protein interactions; backed by DCVC, Nvidia, and Roivant.

🔹 Boston/Tel Aviv-based Converge Bio raises $25M to expand generative AI systems trained on DNA, RNA, and protein sequences, enabling pharma clients to design antibodies and optimize protein yield with integrated predictive and physics-based validation.

🔹 Juvena Therapeutics secures $33.5M Series B to progress its tissue-restorative biologics pipeline and AI discovery platform, backed by Bison Ventures, Eli Lilly, and others, amid ongoing Phase 1 trials for muscle regeneration.

🔹 $50M to scale human cell programming — UK-based bit.bio secures $50M Series C to expand its ioCells platform for drug discovery and toxicology, generating AI-ready human cell data to reduce animal testing and improve preclinical model accuracy.

🔹 Lux Capital raises $1.5B for frontier tech and AI — NY-based Lux Capital closes its largest fund to date amid a weak VC market, doubling down on AI, defense, and deep tech after early wins with Anduril, Hugging Face, and Recursion, and Auris Health, which sold to J&J for up to $6B.

🔹 UK-based Allos secures $5M to apply Causal AI to the redesign of hard-to-genericize small-molecule drugs.

🔹 Avenue Biosciences secures $5.7M to scale its AI-enabled platform that modulates the secretory pathway using engineered signal peptides, improving yield and manufacturability of complex therapeutic proteins.

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 MIT spotlights biotech’s leap into personalized and regenerative medicine — In its Ten Breakthrough Technologies (2026), MIT Technology Review highlights advances like personalized base editing in infants, embryo genetic scoring, and gene “resurrection,” signaling a shift toward bespoke gene therapies, AI-integrated biology, and deeper manipulation of human development and disease.

🔹 Vascularized retinal organoids achieve full light-signal transmission. Researchers at University Hospital Bonn and partners integrated endothelial cells into retinal organoids, enabling nutrient flow, boosting ganglion cell survival, and—for the first time—establishing functional light pathways from photoreceptors to optic nerve cells in vitro.

🔹 CurifyLabs debuts 3D printer for scalable drug compounding that enables faster, modular preparation of personalized medicines in pharmacies

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 China’s biotech VC diverges on exits, incentives, and scale — a new BridgeCross Bio piece dissects how China’s life science venture ecosystem differs from the West, drawing on perspectives from firms like Sofinnova Partners, Sunstone Life Science Ventures, Apricot Capital, and a top Chinese VC; key themes include RMB fund dominance, founder resistance to M&A, and why Western VCs remain cautious despite China’s speed and scale.

🔹 Big Pharma eyes M&A surge as patents expire. With nearly $180B in drug revenues set to go off patent by 2028, major pharma companies are ramping up dealmaking, fueled by regulatory clarity, surging biotech stocks, and pressure to replenish pipelines, setting the stage for a wave of large-scale acquisitions in 2026.

🔹 JPM shifts from megadeals to meetings — Despite no major announcements, the 2026 J.P. Morgan Healthcare Conference remained packed with biopharma networking, as companies increasingly drop news before the event or pivot toward smaller conferences, possibly reflecting a broader evolution in how and where the industry communicates.

🚀 A New Kid on the Block

(Emerging startups with a focus on technology)

🔹 Merge Labs emerges with $252M to develop non-invasive brain-computer interfaces — Backed by OpenAI, Bain Capital, and Gabe Newell, the startup is building ultrasound-based neurotechnology as an alternative to implanted BCIs. A spinoff from Forest Neurotech, Merge aims to interpret and modulate brain activity via blood flow dynamics, with AI foundation models aiding in signal interpretation.

🔹 Tahoe Therapeutics and Alloy Therapeutics form a new company to develop antibody-drug conjugates targeting novel tumor antigens discovered via Tahoe’s AI-powered single-cell platform, combining target discovery with Alloy’s ADC engineering and venture creation infrastructure (namely, 82VS).

Reality Check on AI Antibody Design

We recently read a head-to-head analysis comparing several of the current de novo antibody design models: Nabla Bio’s JAM-2, Chai Discovery’s Chai-2, Absci’s Origin-1 (built on Boltz), and the Baker Lab’s RFAntibody.

Traditional antibody discovery still largely means immunizing mice, waiting for an immune response, generating hybridomas, and screening thousands of candidates. That process typically takes 12–24 months, and many programs never produce a viable lead.

In short, JAM-2 and Chai-2 come out ahead overall, with relatively small differences between them. JAM-2 looks stronger on reported hit rates and affinities across many targets, while Chai-2 stands out on structural validation and target breadth. But the more interesting point is how much better all of these systems look compared with what was considered state of the art roughly a year ago, both in speed and in the likelihood of getting binders at all.

There is particular emphasis on GPCRs, which account for about 34% of approved drugs but are almost exclusively targeted by small molecules rather than antibodies. JAM-2 reports low-nanomolar binding to CXCR4, but Chai-2 reports a CXCR4 antibody with measurable agonist activity based on downstream signaling assays—“to design an antibody that not only finds its target but also induces a specific functional response represents capability that simply didn’t exist before.”

Highlights

• Hit rates at 39%

• Weeks-long timelines vs 12-24 months traditionally

• AI-designed antibody with GPCR-activating activity (a first)

• KRAS mutant discrimination at the single-amino acid level

That said, the analysis is explicit about the limits of what’s been shown so far:

• No in vivo data. None of the platforms report mouse PK, xenograft studies, or other in vivo proof of concept.

• Immunogenicity remains untested. The designed CDRs are novel, and anti-drug antibody risk is unknown. Clinical data is still years away.

• Manufacturing is unvalidated. There is no public evidence yet of large-scale CHO production for these designs.

• Access is limited. JAM-2, Chai-2, and Origin-1 are proprietary, while RFAntibody is open but requires thousands of designs per target.

• Hit rate does not equal a drug. Affinity maturation, epitope tuning, and format engineering remain largely downstream work.

The expectation is that the next meaningful milestones are in vivo data and IND-enabling work, rather than further gains in raw hit rates. At least one group signals that those steps may be approaching, but for now that’s still prospective.

How AI Brings Drug Testing Closer to Human Biology

In her latest column on rare diseases at BiopharmaTrend, our regular contributor Louise von Stechow, PhD, examines how drug testing is gradually shifting away from animal models toward more human-relevant, technology-driven approaches, with AI playing an increasingly visible role. Drawing on examples from toxicology, ADME, and disease modeling, she outlines why animal studies often fall short in predicting human outcomes, particularly in rare and multisystem disorders where suitable models are limited or absent.

Advanced human cell systems, organoids, and organ- and patient-on-chip platforms can capture patient-specific biology, but remain labor-intensive and reductionist. AI models are increasingly layered on top of these systems and historical clinical data to scale predictions, flag toxicity risks such as liver or cardiac injury, and support ADME and dose modeling in ways that are difficult to achieve with animal studies alone.

Von Stechow situates these technical developments in a changing regulatory and industrial context, where agencies in the US and EU are beginning to accept non-animal methods in defined settings, and both public initiatives and biotech companies are investing in computational and hybrid alternatives to traditional preclinical testing. The overall picture is one of incremental change, with AI and human-based models used to focus animal studies where they are most informative.

The full column, with detailed case studies and examples, is available on our website here.

2026 Biotech & Clinical AI Reports

Two reads that came across our desk recently: one is Benchling’s 2026 Biotech AI Report, which is based on data from 100 biotech and biopharma organizations already using AI in R&D and is trying to separate “daily driver” use cases from the stuff that still stalls out on data and workflow friction. The other is ARISE’s State of Clinical AI Report 2026, positioned as an annual synthesis of what is holding up in real clinical settings and what is not, with an emphasis on evaluation quality.

Benchling: 2026 Biotech AI Report

Benchling posits this as a November 2025 survey of about 100 biotech and pharma orgs actively using AI in R&D, and explicitly says it is not meant to represent “general industry sentiment,” but a view into AI front-runners in the U.S. and Europe.

A few takeaways:

• The earliest “wins” are workflow-native use cases with data that is comparatively clean and easy to sanity-check. They call out literature review (76% adoption), protein structure prediction (71%), scientific reporting (66%), and target identification (58%).

• Adoption drops in more complex, regulated, or harder-to-validate domains like generative design, biomarker analysis, and ADME. The report points to data being scattered, incomplete, and hard to validate as a core limiter.

• Their “planned growth” list leans toward more integrated systems, including workflow orchestration, manufacturing optimization, multimodal models, and “co-scientists.”

• They claim AI is becoming a default interface for scientists, reporting 89% using copilots or reasoning tools as a first stop for interrogating and synthesizing data.

• On org design, they report internal upskilling as the top talent source (67%), versus hiring from tech (21%).

• On impact, they report that 50% “report faster time-to-target today” and 56% “expect cost reductions within two years,” explicitly tying the latter to scaling automation and agentic workflows.

• On what breaks pilots, they state the number one reason AI pilots fail is challenges with data quality.

ARISE: State of Clinical AI Report 2026

ARISE describes itself as an interdisciplinary research network, founded in 2024 as a collaboration between clinicians and researchers across multiple academic medical centers, focused on evaluating clinical AI through real-world studies, open benchmarks, and reproducible methods. In their positioning, the State of Clinical AI Report 2026 is framed as an inaugural annual synthesis that pulls together the current deployment landscape, the state of evaluation quality, and what kinds of evidence they think should come next.

Context

According to ARISE, AI is already embedded across healthcare, with 1,200+ FDA-cleared tools and 350,000+ consumer apps contributing to a $70B market, while only a minority of these systems have undergone peer-reviewed evaluation.

Among 691 FDA-cleared AI/ML medical devices cleared between 1995 and 2023, more than 95% went through the 510(k) pathway, which relies on equivalence to existing devices, including devices the report characterizes as sometimes being cleared on suboptimal evidence.

ARISE adds that FDA device summaries frequently lack key study details, reporting that about 50% omitted study design, 53% did not include sample size, and fewer than 1% reported patient outcomes. They also report that 95% of summaries did not include demographic data and 91% did not include bias assessments, and they frame these gaps as relevant to safety and equity in real-world use.

The report’s six key themes are:

• Models made major leaps in actionable prediction and autonomous clinical reasoning, but the “jagged frontier” persists, including brittleness around uncertainty.

• Real-world task evaluation is positioned as a prerequisite for trustworthy clinical AI, with a push beyond traditional QA-style benchmarks.

• A shift from better models to better systems, including methods like multi-agent orchestration, multimodal models, and reasoning fine-tuning, with trade-offs.

• Workflow design matters as much as model capability, with explicit attention to failure modes, automation bias, and deskilling risk.

• Patient-facing AI is treated as its own category, where outcome measurement and safeguards are central and patients are not assumed to provide oversight.

• The report argues the time for context-specific prospective trials is now, noting that randomized prospective trials have already started and framing 2026 as the next wave of evidence.

JPM Takeaways: Less Deals, More Assets

While usually serving as a platform to announce large deals, this time, the defining themes were about biotech plans to grow in a newly established environment: disciplined business development, a reopening IPO window, evolution of GLP-1s, and AI growing into core R&D strategy. Overlaying everything was a louder political and regulatory backdrop, including vaccines, labeling decisions, and intensifying concern about keeping pace with China.

M&A is on hold, but IPOs are back

Even though JPM was full of “we’ve got money to spend” talk, it stayed pretty light on splashy M&A deals. Business leaders said they’re interested and actively scouting assets, but between tough valuation expectations and ongoing uncertainty, most teams are still holding back from announcing major deals.

Where things did feel different was capital markets: IPO planning is creeping back into the conversation. Immunology biotech Agomab and eye-focused startup SpyGlass filed right as JPM was wrapping up, after one of the largest IPOs in three years earlier this January by Aktis Oncology. Meanwhile, Mirador raised $250M Series B while hinting at a possible IPO later this year—framing the raise as a runway to run several programs at once.

Patent-cliff pressure motivates to deepen the bag

Big Pharma stuck to the basics: “we can execute launches and we’ve got a deep pipeline”—with the patent cliff pressure crawling in the background. J&J’s CEO announced a dozen upcoming launches, including its oral IL-23 blocker icotrokinra, and Roche reiterated its goal of delivering up to 19 new medicines by 2030.

BMS, meanwhile, put a spotlight on six assets it thinks could become multi-billion-dollar products—covering neuroscience (Cobenfy), anticoagulation (milvexian), pulmonary fibrosis (admilparant), oncology (pumitamig), plus two oral agents for myeloma. The subtext was clear: companies are trying to stack the deck now with more differentiated, high-value programs to fuel the next growth wave.

GLP-1 is still on top of the world, generics are incoming

The topic of obesity dominated the conference. Pfizer CEO Albert Bourla said the market could hit $150B a year by 2030, which explains why the competitive heat isn’t letting up. But the chatter is getting more nuanced: Novo Nordisk’s CEO even gave some credit to telehealth players selling compounded weight loss drugs for figuring out what price-sensitive patients will actually pay—basically a nod that distribution and affordability are turning into a real fight. On this wave Sandoz pitched the first generic Ozempic—an early hint that “what happens after exclusivity?”. Regulators were part of the story too: the FDA asked companies to drop the suicidal-thought warning from GLP-1 labels.

Regulatory turbulence is rising as the “race against China” becomes explicit

Politics and regulation had a bigger footprint than usual. Sanofi’s CEO pointed to a tougher White House stance on vaccination, and the FDA’s move to add a febrile seizure warning for certain flu vaccines in young kids was a reminder of how fast labels can change. On the flip side, the FDA also signaled it may loosen some manufacturing requirements for gene and cell therapies to help ramp production—good news operationally for advanced-therapy developers.

Meanwhile, execs kept calling for reforms to stay competitive with China, even as China-linked licensing keeps rolling. AbbVie’s $650M upfront deal with RemeGen for a solid tumor treatment and Novartis’ $50M upfront radiopharmaceutical license captured that push-pull: lots of strategic anxiety, but plenty of deal-making anyway.

AI is moving to platforms

AI is turning into an everlasting JPM theme. Lilly and Nvidia’s five-year +$1B partnership stood out here - the Bay Area AI co-innovation lab will become the first facility of its kind, planned to restructure every R&D aspect from discovery and development to manufacturing and commercial work.

Takeda struck a similar tone, talking about an AI-first approach to drug discovery across its assets—shaped in part by its Nabla collaboration and stalled drug program revival. And Proxima (formerly VantAI) added to the momentum by raising $80M to scale its AI-driven proximity-therapeutics platform. Net takeaway from the week: companies are increasingly treating AI as core competitive infrastructure.

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology

If this newsletter is in your inbox, it’s because you subscribed, or someone thought you might enjoy it. In either case, you can subscribe directly by clicking this button:

Subscribe

First things first, we’re pleased to share that our Board Advisor, Andrii Lozoniuk, is in San Francisco for JPM2026 starting today. Andrii will be on the ground throughout the week tracking deal flow, strategic signals, and early-year sentiment across biotech and pharma, with a short roundup to follow in the newsletter.

If you’re in SF and would like to connect, reach out to Andrii directly or email us at info@biopharmatrend.com to set up a time.

An Endpoints tally put the first full week of January at roughly $2.3B in new private biotech capital, with public follow-ons and an IPO pushing the combined total to about $4.9B heading into JPM. In parallel, 2025 closed with healthcare private equity at a record ~$190B in deal value.

Early 2026 deal flow is already heavy, spanning Servier’s €1B+ AI partnership with Iktos, Lilly’s up to $950M InduPro collaboration and its $1.3B Nimbus obesity pact, plus M&A led by Lilly’s $1.2B Ventyx buy and Amgen’s up to $840M Dark Blue acquisition. The biggest potential headline sits above the confirmed deals. Financial Times reported Merck is in talks to buy Revolution Medicines for up to $32B.

On the big-tech and healthcare side, OpenAI launched ChatGPT Health, and Anthropic used the JPM week to roll out Claude for Healthcare.

Historical note

JPM’s rush week has deep roots. The event started in 1983 as a small Hambrecht & Quist healthcare investor meeting at the Westin St. Francis with about 20 presenting companies and roughly 200 attendees, initially centered on biotech.

Its scope widened after H&Q was acquired by Chase in 2000 and Chase was acquired by J.P. Morgan in 2001, bringing the conference under the J.P. Morgan umbrella and expanding the mix to pharma, startups, payers, and non-profits.

Over time, JPM has served as a sentiment barometer as well as a deal-stage, including visible inflection points like the early-2000s genomics boom and a more muted 2009 meeting amid the financial crisis. Last year’s conference reflected heightened security concerns, uncertainty around incoming U.S. policy shifts, and increasing attention to Chinese assets.

Early signals

A few sentiments are coming through consistently in conversations at JPM today: companies are openly scanning for assets across stages, “cheap China” is part of the comparison set but not the only axis, and there’s a clear emphasis on deal quality and fit over price alone. That said, day one has been heavier on intent and positioning than on fresh signatures, with more deal talk than deal announcements so far.

Two anchors could help interpret the broader flow of headlines this week and onwards. One is the patent cliff, with nearly $300B in revenue expected to lose exclusivity by the end of the decade, keeping lifecycle management, partnering, and selective M&A high on agendas. The other is the obesity race, where pressure around oral candidates, next-gen GLP-1s, and differentiation continues to shape R&D prioritization and capital deployment.

With that context set, here are the past week’s and today’s developments through our usual, more granular lens.

🤖 AI x Bio

(AI applications in drug discovery, biotech, and healthcare)

🔹 Manas AI, launched last January by LinkedIn’s Reid Hoffman and Siddhartha Mukherjee with $24.6M, just announced a partnership with Schrödinger to integrate physics-based modeling into its AI platform for discovering small molecules, biologics, and RNA therapies.

🔹 Post-IPO, Insilico Medicine advances AI-designed gut-targeted drug into Phase II for ulcerative colitis, aiming to repair the intestinal barrier with a PHD inhibitor developed using its generative AI platform. Also, Insilico says it nominated a preclinical small-molecule candidate with Hisun just 8 months after launching their AI-driven discovery collaboration.

🔹 Tahoe, Arc Institute, and CZI’s Biohub partner to create largest virtual cell dataset, generating 120M cells and 225k perturbations to fuel open-source AI models simulating drug response and disease biology.

🔹 Owkin partners with NVIDIA to scale AI agents for biology, advancing its reasoning model on patient data and launching Pathology Explorer with Anthropic’s Claude to support drug discovery and diagnostics.

🔹 DrugCLIP debuts as a post-AlphaFold AI model, screening protein-small molecule interactions up to x10 million faster than docking by embedding structures and chemistry in a shared space, with a database of 500M compounds.

🔹 Boston-based Somite AI rebrands as Cellular Intelligence to pursue a universal virtual cell signaling model, scaling its microfluidics platform to over 1M conditions to map how signal sequences guide cell fate.

🔹 1910 releases AI model PEGASUS that generates cell-permeable macrocyclic peptides with high polarity, addressing a key barrier in peptide drug development.

🔹 Dyno Therapeutics unveils Dyno-yp2, an AI-designed AAV capsid showing >94% brain transduction and 80-fold liver detargeting in TfR-humanized mice, advancing CNS gene therapy delivery.

🔹 Following its $130M Series B and unicorn $1.3B valuation, Chai Discovery partners with Eli Lilly to train custom AI for biologics design, integrating its antibody generation platform with Lilly’s proprietary data.

🔹 BigHat Biosciences expands its collaboration with Eli Lilly to develop generalizable AI models for antibody drug discovery, using high-throughput wet lab data to improve early-stage candidate selection.

🔹 Freenome teams up with NVIDIA to scale AI for early cancer detection, using accelerated deep learning to enhance blood-based tests and develop an open-source foundation model for cell-free DNA analysis.

🔹 Lantern Pharma launches AI Center of Excellence in India to scale its RADR drug discovery platform, expand beyond oncology, and industrialize multi-agent AI for global biopharma partners.

🔹 Medable launches AI agent to automate trial master file processing, aiming to cut manual work and speed up clinical trial operations.

🔹 Danish biotech Genmab partners with US-based Anthropic to deploy Claude-powered agentic AI tools to accelerate data analysis and document generation in clinical development.

🔹 AI to guide dual-action cancer therapy — US-based BostonGene partners with Ottimo Pharma to apply multiomic AI models for patient selection and clinical acceleration of a first-in-class PD-1/VEGFR2 immuno-oncology antibody.

Subscribe now

🚜 Market Movers

(News from established pharma and tech giants)

🔹 Bayer partners with Amsterdam-based Cradle in 3-year deal to deploy generative AI for antibody discovery and jointly advance machine learning tools to speed biologics development.

🔹 OpenAI launches ChatGPT Health and ChatGPT Healthcare, consumer and clinical tools built on GPT-5.2 for personalized guidance and hospital use, now live in major U.S. health systems (early access).

🔹 Anthropic follows with Claude for Healthcare, a HIPAA-ready clinical and consumer AI tool unveiled at JPM26, enabling health data integration, admin support, and medical reasoning across U.S. systems. The company also added a ClinicalTrials.gov connector to Claude, enabling structured AI access to over 500k trials for protocol drafting, and more.

🔹 UK’s Basecamp Research, with NVIDIA and Microsoft, launches AI models for precise gene insertion, enabling new gene and cell therapies and designing antimicrobials against drug-resistant bacteria.

🔹 Schrödinger integrates Eli Lilly’s $1B AI platform into LiveDesign, giving drug developers access to molecular design models for small molecules and antibodies starting in Q1 2026.

🔹 Eli Lilly integrates its AI platform with Benchling, giving over 1,300 biotechs access to drug discovery models for small molecules and antibodies via secure federated learning.

🔹 MIT and Microsoft researchers create an AI model to design nanoparticle-bound peptides that signal cancer-linked enzyme activity, enabling low-cost, at-home urine tests for early diagnosis.

💰 Money Flows

(Funding rounds, IPOs, and M&A for startups and smaller companies)

🔹 NVIDIA and Lilly to launch $1B AI drug discovery hub in South San Francisco to co-develop next-gen biology and chemistry models by linking automated labs with AI systems.

🔹 Servier signs €1B+ multi-target AI drug discovery deal with Iktos, tapping its generative design and robotic synthesis platform for small-molecule programs in oncology and neurology.

🔹 Eli Lilly signs up to $950M deal with US-based InduPro to develop AI-guided multispecific cancer therapies using a membrane protein mapping platform to improve tumor targeting and reduce toxicity.

🔹 GSK signs $50M+ deal with Noetik for AI-driven virtual cell models to simulate tumor biology in lung and colorectal cancer.

🔹 After raising over $290M in Hong Kong’s largest biotech IPO of 2025, Insilico Medicine signs up to $888M oncology deal with Servier, combining AI-driven drug discovery with Servier’s clinical development to advance small-molecule cancer therapies.

🔹 Hippocratic AI raises $141M Series B at $1.6B valuation, launching a healthcare agent app store and acquiring Grove AI to expand into life sciences, now partnering with 23 health systems and backed by investors like Kleiner Perkins, a16z, and NVIDIA.

🔹 insitro to acquire Israel-based CombinAbleAI to launch TherML, a unified AI platform for designing small molecules, oligos, and biologics.

🔹 US-based Soley Therapeutics raises $200M Series C to advance its AI-powered cell stress sensing platform and move two first-in-class oncology drugs toward clinical trials.

🔹 RNA biotech goes public — China-based Ribo Life Science raises over $230M in a heavily oversubscribed Hong Kong IPO to advance its siRNA pipeline targeting cardiometabolic and renal diseases.

🔹 BioNTech and UPenn launch a $50M seed fund to back early-stage therapeutics, diagnostics, and AI drug discovery startups emerging from Penn research, aiming to boost innovation beyond mRNA.

🔹 Servier launches €200M VC arm — French pharma Servier establishes Servier Ventures to invest in early-stage European biotech startups in oncology and neurology, expanding its dealmaking strategy through minority stakes.

🔹 Targeting all EGFR forms — US-based EpiBiologics, a Genentech spinout, raises $107M Series B to advance its first-in-class protein-degrading antibody for lung and head-and-neck cancers, aiming to overcome mutation-specific resistance with a broader EGFR approach.

🔹 Scaling spatial biology — US-based Vizgen raises $48M to expand global access to its spatial multi-omics platform, accelerate product innovation, and scale manufacturing for single-cell research tools.

🔹 American biotech Locus Biosciences awarded $3.3M from NIH, with up to $28M total, to run a clinical trial of its AI- and synthetic biology-powered bacteriophage therapy for drug-resistant pneumonia in ICU patients.

🔹 Finnish startup Avenue Biosciences raises $5.7M to scale its AI-driven platform for high-throughput protein engineering, aiming to ease manufacturing of complex biologics.

Share

⚙️ Other Tech

(Innovations across quantum computing, BCIs, gene editing, and more)

🔹 In Alzheimer’s drug search, Novoron wins $2.5M NIH grant to develop an AI-assisted human brain organoid platform that screens drugs targeting tau spread in more realistic brain models.

🏛️ Bioeconomy & Society

(News on centers, regulatory updates, and broader biotech ecosystem developments)

🔹 AI takes over routine prescribing — Utah pilots AI-only prescription renewals via startup Doctronic, co-led by a UCSF surgeon, marking a US first in automating clinical decisions without physician input for chronic care management.

🔹 FDA issues draft guidance endorsing Bayesian methods in clinical trials, aiming to speed drug development by enabling more flexible designs and efficient use of prior data, especially in rare and pediatric diseases.

🔹 FDA approved 46 new drugs in 2025, with oncology leading (35%) and strong showings in bispecifics, ADCs, and RNA; first-in-class standouts and modest sales forecasts highlight a shift toward focused, mid-scale innovation.

🚀 A New Kid on the Block

(Emerging startups with a focus on technology)

🔹 MIT spinout Boltz launches with $28M and Pfizer deal, aiming to democratize biomolecular AI with open-source models and a hosted discovery platform for drug design and protein engineering.

🔹 CRISPR’s first one-patient success becomes a company as Aurora Therapeutics launches with $16M to scale custom gene editing for rare diseases, founded by Jennifer Doudna and Fyodor Urnov after their therapy for “Baby KJ.”

🔹 Relation partners with Deerfield to launch joint NewCos, advancing AI-discovered therapeutic targets from its lab-in-the-loop platform into drug development through a shared translation model.

🔹 Topos Bio emerges from stealth with Topos-1, an all-atom foundation model for intrinsically disordered proteins, aiming to unlock drug discovery for ~40% of the human proteome missed by tools like AlphaFold.

Subscribe now

Read also:

Three Big Ideas in Aging Research That Could Shift the Therapeutic Landscape

AI Protein Design: Platforms, Specialists, Modular Tools

The ‘Holy Grail’ of Digital Biology