With the whirlwind development of AI, it can be difficult to keep track of its uses in both research and the market. In this episode of The Chain podcast, host Ben Hackel, Professor of Chemical Engineering & Materials Science at the University of Minnesota, speaks with Enkelejda “Ledi” Miho, Professor of Digital Life Sciences at the University of Applied Sciences Northwestern Switzerland FHNW, who breaks down the current state of AI and its role in drug development. She talks about the opportunities of AI and drug discovery and how digital biomarkers and molecular data are helping with personalized medicine. Miho also discusses the challenges of advancing AI, why having an “adisciplinary” approach is the key to assembling the right team, and how to design studies to be as broadly robust as possible, as well as the advancements of her and her team’s own research.
GUEST BIO
Enkelejda Miho, Professor of Digital Life Sciences, The University of Applied Sciences Northwestern Switzerland FHNW
Enkelejda Miho is a professor of Digital Life Sciences and dean of the master's program in medical informatics at the University of Applied Sciences and Arts Northwestern Switzerland. She is head of the Laboratory of Artificial Intelligence in Health (aihealth.ch). The group’s research focuses on the emerging field of artificial intelligence applied to health. The group uses analytics for personalized medicine, drug discovery and development, and support systems in clinics. She is the founder of the ETH spin-off aiNET.
MODERATOR BIO
Benjamin J. Hackel, Ph.D., Professor of Chemical Engineering and Materials Science, University of Minnesota
Ben Hackel is a professor of chemical engineering and materials science at the University of Minnesota. He earned degrees in chemical engineering from the University of Wisconsin (B.S. 2003, advised by Eric Shusta) and MIT (Ph.D. 2009, advised by Dane Wittrup). He performed postdoctoral research in the radiology department at Stanford University (Sam Gambhir). Since its inception in 2011, the Hackel lab has applied protein engineering technologies to develop physiological, molecular targeting agents for molecular diagnostics and targeted therapy, focusing on oncology and infectious disease.