Could Anthropic Disrupt the Techbio Companies Built for Pharma/Biotech?
AlSO: The Numbers Behind China's Biopharma Ascent
Everyone is talking about how Anthropic AI lab now designs drugs, hires the AlphaFold Nobel laureate, and ships Claude Science alongside Claude Code. Also, their partnership with Basecamp Research (i.e. EDEN-designed antibiotic peptides 97% active against WHO priority pathogens), integration of Claude Science with Boltz, and so on. There is a real movement.
But despite the obvious impressiveness and importance of this move, the part that Anthropic is addressing is the one that was never the most expensive/complex part of the drug development business, in my opinion.
Designing a promising molecule has been getting cheaper for a decade, as well as target selection. That is not where drug discovery programs fail, generally speaking. Drug programs fail in toxicity and unexpected systemic effects on body, lack of efficacy, in manufacturing, in failing to enroll enough/right patients, in trials that fail because the biology was misjudged or the population was selected in a sloppy trial design (lack of biomarkers, etc.).
As far as I can tell, Anthropic has limited clinical apparatus, no manufacturing, no regulatory track record, and, likely, no answer yet to "what do you do if you find something that works?" Yes, sure, they can design drugs really fast, but then what? How does their model differentiate against later stages, where the role of AI is surprisingly small at the moment?
Claude Science can probably move "target to shortlist in minutes," and so it compresses the cheapest, fastest, most-solved stage of the pipeline. It is certainly a milestone, certainly impressive, but have they solved drug discovery with it? Probably not yet.
Now, what does it mean for the AI-native biotechs, the likes of Iambic, Recursion, Insilico Medicine, OWKIN, Isomorphic Labs, Cradle, NOETIK, Xaira, SandboxAQ, etc.)?
Well, their moat was never the model alone, I think. It is this:
→ Proprietary data generated in-house (e.g., Recursion's phenomics screens, Insilico's chemistry-plus-clinical loop, Owkin's federated hospital access, etc).
Anthropic doesn't seem to have this yet. It rents it (e.g., Basecamp's BaseData, PacBio/Ultima sequencing in the Trillion Gene Atlas). The players who own their data-generation flywheel keep that edge (for now).
→ Wet-lab-to-model feedback loops. The ones who've vertically integrated experiment and prediction still have the tight loop Anthropic says it's trying to build by running its own program.
→ Clinical pipelines, optionality to pivot programs fast, for those who do have a pipeline.
Where Anthropic does compete with them, and this might be the real pressure, is on general reasoning as commodity infrastructure.
If Claude Science does a considerable % of what a top/mid-tier computational biology platform can do, available to every paid subscriber, the AI-biotechs lose their "we have special AI" pitch to pharma. Their story has to become "we have special data and validation," which is a harder, more capital-intensive sell, but leading players are doing it alright.
That being said, I do see real pressure from Anthropic’s competition for the following situations:
1) new AI drug discovery companies
2) pureplay companies that sell only AI-enabled research tools or services.
Those will have to build a defensible moat real quick.
The Numbers Behind China’s Biopharma Ascent
A new comprehensive report by Information Technology and Innovation Foundation (ITIF), a top US think tank for policymaking, makes the case that China is on track to challenge U.S. leadership in biopharma within a decade. The report is a policy argument, urging a U.S. response, but here let’s focus on the underlying data.
First of all, what is interesting is approval time for human trials in China fell from 501 days to 87. Patient enrollment at Chinese tertiary hospitals runs 5–10x higher than at U.S. academic medical centers, and per-patient costs are lower—a Phase I trial there is about 43% cheaper and over 50% shorter than in the U.S.
Net effect: Chinese firms can go from discovery to first-in-human in roughly half the global average time. Speed and cost, not just science, are the edge.
The output numbers have caught up to the process. China’s share of clinical trials for the most innovative drugs jumped sixfold in a decade to 30%, nearly level with the U.S. at 33%.
It now accounts for 31% of the global drug pipeline. Value-added pharmaceutical output grew roughly 13-fold since 2002, to ~$187 billion.
Three Chinese firms now sit among the world’s 20 largest pharma pipelines, led by Jiangsu Hengrui Pharmaceuticals at #12.
China has also overtaken the U.S. in highly cited biotech publications—nearly 800 top-decile papers in 2024 versus 112 for the U.S.
The deal wave is where Western pharma is voting with real money, though.
Out-licensing deals from China grew 31x since 2015 (5 to 157 deals), with value up 54x to $135.7 billion last year—and another $60 billion in Q1 2026 alone. Average upfront payments more than tripled to $172 million.
The marquee examples: AstraZeneca paid CSPC $1.2 billion upfront for weight-loss assets; Bristol Myers Squibb committed up to $15.2 billion to Hengrui across 13 programs; Pfizer struck multibillion-dollar oncology deals with 3SBio and Innovent... and so on.
China is now the leader in specific frontier modalities too—over 42% of the global antibody-drug-conjugate pipeline, and it overtook the U.S. in oncology research output in 2024.
The report is measured about the limits, though.
China still holds only ~4.8% of the global biotech market and ~7.5% of global pharma sales. Much of the ecosystem rests on state subsidies (one study found 99% of China’s top R&D-spending firms received them), and FDA reluctance to approve drugs on China-only trial data remains a barrier to reaching Western markets.
So, the lead is in inputs and velocity more than in commercialized, globally approved products—for now...
Also glad to see BioPharmaTrend cited in the report.
Anyway, worth a read for anyone tracking where drug development is moving in China and how it affects the global life science market.
The refinement I'd add is that "data" and "validation" serve very different roles in that phrase, and the gap between them is where most of the value lies. Proprietary data is necessary and increasingly common. Validated data, calibrated to the biology you're actually drugging, is the rare, capital-intensive part, and it's the only thing that survives the stages Anthropic can't touch: tox, efficacy, patient selection.
Which sharpens @Bengüsu's build-vs-partner point nicely. You can rent a model, and soon everyone will. You cannot rent a validated loop for your specific biology, the thing that tells you whether the data predicts the clinic. That is what a small player with real data and tacit knowledge actually owns, and it's the leverage to set terms before the big labs generate their own.
It also makes the China section the sharper story: speed and enrollment scale are a validation advantage as much as a cost one, more shots and faster readouts, and that compounds exactly where model access doesn't.
Great read. The China angle is gold.