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The promise and challenges of relying on AI for drug development

Clearly articulated principles can guide the direction of technological advancements like AI-enabled drug discovery.
Illustration of a woman in a lab
The use of AI in drug discovery has the potential to bring novel medicines to patients more efficiently and more predictably. | iStock/DrAfter123

The use of artificial intelligence in drug discovery, when coupled with new genetic insights and the increase of patient medical data of the last decade, has the potential to bring novel medicines to patients more efficiently and more predictably.

Watch a discussion of the promise and potential pitfalls of relying on AI in bringing life-saving drugs to market — and an exploration of questions of justice and equity in drug research and access.

Our speakers are Russ Altman, Stanford professor of bioengineering, genetics, medicine, and biomedical data science, in conversation with Kim Branson, global head of AI and machine learning at GSK. Jack Fuchs, MBA ’91, an adjunct lecturer who teaches “Principled Entrepreneurial Decisions” at Stanford School of Engineering, moderated and explored how clearly articulated principles can guide the direction of technological advancements like AI-enabled drug discovery.