Chai Discovery, an OpenAI-backed AI x pharma tool provider, closed multiple pharma “tools” deals around the JPM Pharma conference and its Science team released a podcast with cofounders Matt McPartlon and Neil Patil on what changed. The article cites that Chai Discovery is worth $4B and reports that since June it announced three major additional deals with Lilly, Novartis, and argenx plus an expansion of its Eli Lilly program. It argues that improved structural-to-binding modeling quality has made AI-driven molecule design “good enough to trust,” enabling teams to scale discovery faster and shift iteration toward engineering-style optimization rather than relying on extensive lab trial-and-error.
AMIE advanced from text-based clinical reasoning to a real-time video configuration that can observe non-verbal cues, guide physical examination maneuvers, and deliver diagnostic dialogue. In a randomized OSCE study with 100 scenarios, 300 live consultations, and 30 board-certified primary care physicians, AMIE (Video) was rated on par with PCPs across core clinical competencies and higher than both PCPs and AMIE (Text) for physical observation and examination. This shift changes the system from discarding visual and audio information in text chat to using synchronous audio-visual inputs, with results still limited to simulated patient actors and requiring validation on real patients before real-world use.
CARE-X, a chest X-ray vision-language model, was introduced with auxiliary supervision and DAPO reinforcement learning to support calibrated classification, location grounding, and report generation in one system. It reached 94% overall accuracy on the ReXVQA benchmark (41,007 question–answer pairs) as of August 2026. The work changes radiology VLMs by combining structured, tunable confidence outputs and tool-augmented quantitative measurement with generative reporting rather than relying only on free-text predictions.
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