GenScript

Headlines · 3

1. 4d
   AI pharma's pivotal test: Rentosertib Phase III readout due 2029

   The article reports that Anew Labs, an AI drug-discovery company spun out of ByteDance, raised a $290 million first round at a $1.5 billion valuation, and that Anthropic has reportedly built a wet lab in the San Francisco Bay Area where Claude drives robots to run real biological experiments. It divides the AI pharma chain into three groups — upstream AI technology firms such as Insilico Medicine, midstream CRO/CDMO wet-lab service providers such as GenScript and Twist Bioscience, and downstream pharma companies including Fosun Pharma and Hengrui Pharmaceuticals — and cites brokerage estimates that AI can cut drug-discovery timelines by 70%-90% and total R&D cost by roughly 50%. The decisive test is Insilico's lead asset Rentosertib, whose Phase IIa showed a 98.4 mL mean lung-capacity gain at 60 mg versus a 20.3 mL decline in controls; its China Phase III began in July 2026 with 320 planned participants and top-line data expected in 2029.

   36氪 人工智能 · 🔥 0
2. 6d
   AI drug discovery hits a bottleneck as wet-lab work slows the pace

   An industry commentary argues that AI is already embedded in pharma R&D — literature review, molecule generation and clinical-trial management — but models trained only on public data cannot create a moat, so companies are shifting toward building their own “dry-wet” design-build-test-learn loops to accumulate proprietary data. It notes that Anthropic was reported to have set up a biological wet lab in the San Francisco Bay Area, that Eli Lilly's Lilly TuneLab signed GenScript, Twist Bioscience and Ginkgo Bioworks to supply wet-lab data, and that in the Novo Nordisk breach the leaked proprietary biological and chemical training data amounted to only about 407MB. Citing estimates compiled by Southwest Securities, the piece says AI can cut timelines by 70–90% in discovery, 50–80% in pre-clinical and 50–60% in clinical stages, while stressing that AI remains a hypothesis-generating assistant rather than a decision system, and that success still hinges on whether a target truly causes the disease.

   虎嗅 AI · 🔥 0
3. Oct 10
   AI drug design is flooding Chinese labs with wet-lab work

   Anthropic's Claude designed 1,320 binding proteins against a dozen targets, which Adaptyv Bio and Twist synthesized and tested; 354 were confirmed to bind, a hit rate near 30% versus the traditional 10%–15%. The article argues that as AI pushes the marginal cost of molecular design toward zero, the first orders flow to lab-service providers: GenScript's AIDD revenue doubled year over year in H1 with gross margins about 20 points above its traditional protein-expression business, while XtalPi posted 803 million yuan in 2025 revenue, tripled and its first full-year profit. Meanwhile Washington is trying to pull early-stage R&D and clinical capacity back onshore via HHS's TrialBlazer plan and the BIOSECURE Act.

   MIT科技评论中文 · 🔥 0

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