H1 2025 Recap: Key Signals from the Tech+Bio Frontier
A high-signal summary of some of the most important moves and trends shaping biotech and tech-enabled life sciences in the first half of 2025
Hi there! While hiding from the 38 °C heat under my airco—my best friend for this summer—I decided that it is the right time to reflect on an incredibly eventful but also a bit of a rollercoaster tech+bio space in the first half of 2025.
In this issue: Financial Climate & Deal-Making Power Shift — Gene Therapies are a Mixed Bag — AI Drug Discovery is Recalibrating — Big Data & Data Infrastructures Define Leaders — a Year of Next Generation Sequencing — Away from Animal Models — Brain-Computer Interfaces are Having Momentum
Before we dive in, I will be visiting the Aging Research & Drug Discovery Meeting - ARDD 2025, so let’s meet sometime between August 25-29 in Copenhagen!
Financial Climate & Deal-Making Power Shift
So, first things first, what does the market and venture capital space look like now when we enter H2?
I recently read a timely post by Audrey Greenberg, highlighting insights from reports by Endpoints News and DealForma. Biotech’s holding up thanks to big pharma – $98B in deals so far this year, with licensing surging (especially for Phase 2/3-ready programs) and blockbuster M&A like Merck-Verona and Sanofi-Blueprint leading the way.
On the flip side, venture funding has cratered, down 33% QoQ, with early rounds, IPOs, and follow-ons all at multi-year lows.
Also, human data is beating out platform hype, and in this shaky market, strategic M&A looks like biotech’s best path forward – especially with pharma still active, notably in China, which drove 38% of major licensing deals.
Speaking about the geography of biotech VC concentration, there is an interesting new biotech VC report from Nucleate Signal, which maps the top 10 biotech hubs by local investor count—led by San Francisco (1,752), followed by NYC (713), London (488), and Boston (478). Kudos to André Hurtado for pointing me to this post, btw.
The report introduces a new framework classifying cities by investor density × capital retention, grouping them into four types like Resilient Engines (e.g., SF, Boston) and Capital Exporters (e.g., NYC, London). Notably, San Diego, often considered a strong VC hub, is labeled Externally Dependent, raising questions about local reinvestment. The report, "Built from Within", was written by Lauren Stanwicks and Pranita Atri and could be interesting for those of you thinking about biotech investment strategy in H2 and beyond.
Finally, China… of course.
China’s biotech scene made some serious waves in H1 2025, and the industry’s paying close attention. Big pharma didn’t hold back; 14 major licensing deals were signed with Chinese firms, totaling over $18 billion, up from just two last year. Suddenly, a third of all deal value globally is coming from China-based innovation!
Investors are jumping in too: the Hang Seng Biotech Index is up nearly 80%, and 34 Chinese biotechs filed for Hong Kong IPOs in just the first half of the year.
Companies like Akeso and XtalPi made headlines in H1, for instance, with competitive drugs and AI-powered R&D, showing China’s not just catching up, but possibly also setting the pace in some areas.
That being said, there’s a real geopolitical edge to all this. U.S. policymakers are probably starting to worry about biosecurity and data-sharing, so while the business side sees opportunity, there’s growing tension in the background. Bottom line: China’s biotech rise is real, fast, and making the rest of the world take notice... in Europe too.
Gene Therapies, a Mixed Bag
The gene-editing space in H1 2025 was a mix of excitement and caution. On one hand, big players like Eli Lilly doubled down, buying Verve Therapeutics in a $1.3 billion deal after promising CRISPR-based cholesterol data. The global market’s still growing fast, worth around $4.5 billion now and climbing at a 10–14% annual rate as per Bloomberg Law.
But funding has cooled off sharply (as per DealForma/Reuters), dropping from over $8 billion in 2021 to just $1.4 billion in 2024, forcing companies like Editas and Prime Medicine to trim pipelines and cut costs.
At the same time, research progress is real: from the first successful prime editing treatment in CGD, to a baby getting a custom LNP-based CRISPR therapy.
Still, safety concerns loomed large… Sarepta encountered obstacles after multiple patient deaths and FDA intervention, possibly shaking investor confidence in AAV-based delivery.
Overall, it’s a moment of recalibration, so to speak… Plenty of long-term optimism, but with more scrutiny, tighter budgets, and a sharper focus on what actually works.
Now, speaking about the future of gene therapies, I think it will be increasingly shaped by the emerging technologies, like LLMs and other modeling tools. Gene editing is extremely complex and multifaceted, so it is a ripe area for AI models to shine, at least for those that can generalize across datasets and contexts.
Especially interesting to me is a new powerful modeling tool, just published in Nature Biomedical Engineering, which is called CRISPR-GPT. It is an autonomous, language model–driven agent designed to plan and execute CRISPR-based gene-editing experiments across modalities like knockout, base editing, prime editing, and epigenetic editing.
Conceptually, it integrates reasoning, task decomposition, and domain-specific tools to automate the entire experimental pipeline—from guide RNA design to protocol generation and data interpretation. Its architecture uses modular agents to coordinate planning, execution, and user interaction, enabling flexible operation modes (e.g., full automation, guided workflows, or targeted Q&A). Technical tools are invoked as needed, but the core innovation lies in treating biological experimentation as a structured, language-guided problem solvable through iterative agentic reasoning.