Artificial intelligence
Listen to this in-depth discussion on how AI can help identify end-to-end data weaknesses, as well as broader implications regarding the inevitability of human interaction, with guests from GSK, IQVIA, Exelixis and DataHow.
Both the White House and Congress have proposed legislation for the appropriate use of AI while the FDA continues to serve as the gatekeeper for patient privacy and safety.
In this deep dive, BioSpace examines how small, medium and large companies are using artificial intelligence and machine learning to enhance their drug discovery efforts.
This is part one of a discussion focused upon data bias, accuracy, access and the future of AI in drug development. Topics explored are ROI, human bias, data challenges, data management plans, and human expertise.
The biopharma industry is moving toward using AI to try to determine how well a given person would perform in a role, with applications that go beyond recruiting.
More and more companies are turning to artificial intelligence for drug safety prediction, but as with any new application of AI, experts urge caution.
High multiplexed patient-centric assays could reduce patient burden
New platforms are emerging to help biopharma companies fill their human studies more efficiently, but barriers remain to their successful implementation.
A Discussion with IQVIA’s Michelle Gyzen Sr. Director, Regulatory Affairs and Drug Development Solutions
AI and machine learning could transform drug discovery, but first, practitioners must overcome ethical challenges en route to medicines for all.
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