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.
EHR patient recruitment could improve clinical trial matching, but workflow integration, data quality, interoperability, and AI validation remain key challenges.
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Revised FDA draft guidance for generic peptide products updates expectations for ANDAs, impurities, structure, immune response, and biological activity.
Ethical obligations in decentralised clinical trials extend beyond consent and privacy. Sponsors must protect safety, scientific validity, equity, and oversight.
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.
Adaptive clinical trials can improve efficiency, reduce patient burden, and support faster development through structured, evidence-based flexibility.
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.