Abstract

Swarm learning opens new opportunities for collaboration and innovation in clinical research where all members of the swarm have equal rights. Only algorithms and parameters are shared – with no central authority. Swarm creates many new opportunities in clinical research to develop new therapeutics, epidemiology, genetics research and more. This session will unlock swarm principals, challenges and opportunities in clinical R&D driving wider adoption of its application(s) in the health domain. Key learnings will include: Understanding the differences between federated machine vs swarm learning The technical, policy and application barriers when it relates to transferring significant amounts of data The steps and frameworks needed to drive wider understanding and adoption of the technology in clinical R&D The pharma perspective: where does Swarm AI offer new solutions yet to be introduced to the drug development process

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