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Drug Discovery

56 summarised stories about Drug Discovery, each linking back to the original source. Browse all topics →

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Thursday, 16 July 2026

🔬 The Lab of the Future Should Feel Like a Data Center — Andy Beam & Rafa Gómez-Bombarelli, Lila Sciences

Latent Space 3 months ago 28

Lila Sciences is building an automated laboratory with AI-guided robotics and equipment designed to generate scientific data continuously, creating over 10 trillion experimentally validated scientific reasoning tokens. The company operates a wet lab with integrated instruments connected like a data center, achieving results such as a 2,500x speedup in gas sorption measurement and generating candidate electrocatalysts that outperformed expert-designed alternatives. This approach aims to develop a general scientific reasoner capable of solving problems across biology, chemistry, materials science, and drug discovery by treating the lab as an infinite data generation mechanism.

Our approach to bioresilience

Google DeepMind 3 months ago 33

Google DeepMind and Isomorphic Labs announced a joint bioresilience program to prevent misuse of AI models in biological contexts while enabling their use for disease prevention and response. Over the past 12 months, the organizations advanced more than 15 partnerships with government bodies and biosecurity groups to implement safeguards across prevention, detection, and response activities. The program makes AI systems like AlphaFold and the IsoDDE drug design engine available to trusted partners to accelerate vaccine design, improve pathogen surveillance, and help detect outbreaks faster than traditional methods.

Cell Cinema enables label-free 3D imaging of living cell states for model training

precigenetics.com 3 months ago 13

Precigenetics has developed Cell Cinema, a label-free imaging system that tracks living cells over time by converting their chemical-spatial states into high-dimensional token vectors, enabling AI models to learn from live cell response trajectories rather than only terminal endpoint data. The system measures how melanoma cells respond to ferroptosis induction and targeted therapy through time-indexed observations of the same living cell, producing a cells-by-time-by-features tensor that preserves response history. This approach aims to enable AI models to predict drug responses and toxicity in living human-relevant cells before clinical trials, shifting drug discovery from terminal assays to conditional trajectory prediction on instrumented living systems.

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