The 19th Annual Symposium of the Institute of Chemical Biology and Drug Discovery (ICB&DD), “Drug Discovery & AI: Advances and New Directions,” attracted a broad audience and provided an opportunity to learn about and discuss the current state and the future of drug discovery and development in light of the breathtaking advances in artificial intelligence (AI).
The symposium shed light on the impact that AI has started to have on drug discovery and the significance of integrating AI methods with fundamental theory and methods of molecular biology and physical sciences to generate interpretable AI-driven discoveries in pharmacology.
The symposium, held at the Charles B. Wang Center, was organized by event chair Ivet Bahar, director of the Laufer Center for Physical and Quantitative Biology, and co-chair Dima Kozakov, professor of Applied Mathematical Sciences and Laufer Center faculty (currently at Oden Institute for Computational Engineering and Sciences, UT Austin). It was sponsored by the Office of the Vice President for Research, the Renaissance School of Medicine, the College of Arts and Sciences Department of Chemistry, Hoffman and Baron LLP, and Chembio Diagnostics Systems Inc.
In the opening session, Bahar welcomed attendees and gave a brief history of the importance of artificial intelligence in modern science. Stony Brook Executive Vice President and Provost Carl Lejuez gave opening remarks, which highlighted the importance of multidisciplinary entities on campus such as ICB&DD and its long-lasting record of attracting some of the best faculty to the SBU scientific community. Iwao Ojima, director of the ICB&DD and distinguished professor in the Department of Chemistry, followed with an overview of the institute, its history and mission.
AI has impacted various areas of biology and biomedicine, including structural biology and personalized medicine, and its impact on drug discovery is yet to be established. Yet, several talks by distinguished speakers highlighted notable accomplishments enabled by novel AI methods, signaling that AI has already begun to accelerate computer-aided drug discovery and facilitate the design of novel therapeutic interventions.
Read more about the talks and poster sessions on SBU News.