GSK’s new $110M AI deal shows why quality biological data > bigger models

The $110M Deal: GSK and Relation Therapeutics are expanding their partnership. Relation will conduct lab experiments to produce large-scale cellular datasets to train AI models (like their MORGAN platform) for drug target discovery. Public Biological Data Hits a Wall: Unlike LLMs that improve as you feed them more web text, single-cell biological models plateau quickly on public databases (e.g., CZ CELLxGENE, Human Cell Atlas) due to lab noise, differing protocols, and data overlap. The "Lab-in-the-Loop" Model: Relation uses physical perturbation experiments alongside single-cell and spatial transcriptomics to measure exact cellular responses to genetic changes and drugs, feeding clean data directly back into ML models. Proven Concept: Relation has already used this strategy to build Osteomics, a proprietary single-cell bone atlas for studying osteoporosis. Industry-Wide Pivot: Big Pharma (including similar moves by AstraZeneca and Pathos AI) is realizing that clean, specialized, disease-specific data is becoming the ultimate moat in AI drug discovery.