BMS and NVIDIA Build Pharma’s AI Supercomputer
BMS and NVIDIA are building a powerful pharma AI factory using advanced supercomputing, AI models, and scientific data to accelerate drug discovery.
“The pharma industry is beginning to look at biological age as a surrogate endpoint to improve clinical trials."
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BMS and NVIDIA are building a powerful pharma AI factory using advanced supercomputing, AI models, and scientific data to accelerate drug discovery.
FDA oncology clinical trial guidance targets restrictive eligibility criteria, covering performance status, washout periods, medications, and laboratory values.
Read about how Throne Science is advancing passive health monitoring with AI-powered sensing that automatically captures daily toilet habit data.
“This is one of the riskiest industries there is because you're dealing with human lives, you're dealing with experimental protocols, and you're dealing with regulatory bodies where you might not get another shot at that clinical trial."
Revised FDA draft guidance for generic peptide products updates expectations for ANDAs, impurities, structure, immune response, and biological activity.
AI-designed bacteriophages show how genome models could create new antibacterial therapies while forcing pharma to rethink biological AI governance and biosecurity.
WHOOP and Natural Cycles show how wearable health data is moving into regulated digital health, creating new opportunities for women’s health and pharma.
RNA biosensors for diabetes could allow earlier diagnosis and better personalised care. Explore the power of AI monitoring and next-generation molecular diagnostics.
Learn how AI in pharmaceutical GMP manufacturing is improving quality, data integrity, predictive maintenance, and regulatory compliance in modern drug production.
Google SensorFM was pretrained on over one trillion minutes of wearable data. Discover what this AI foundation model could mean for digital health and pharma.
See how Anthropic's Gates Foundation partnership and Long-Term Benefit Trust could lead the way in shaping responsible AI governance across healthcare innovation.
LLM-assisted rare disease re-assessment improves genomic analysis, increasing diagnostic yield and supporting clinician-led precision medicine and possibly drug development.