Salt Lake City, Utah - July 9-12, 2024 – At the 22nd International Conference on Artificial Intelligence in Medicine, the “Artificial Intelligence for Drug Discovery – Development in Pharmaceuticals, Academia, or Jointly in Collaborations” workshop kicked off at the Hilton Salt Lake City Center with a full audience. The event drew experts from leading institutions and industries to discuss the latest advancements in AI applications for drug discovery. It also showcased one of the largest pharma-academia collaborations in the US, attracting many leaders in the field seeking insights on how to initiate, develop, and grow successful partnerships.
Hosted by the Yale-Boehringer Ingelheim Biomedical Data Science Fellowship Program, co-chaired by Drs. Jan Nygaard-Jensen, James Cai, and Katie Zhu, the workshop featured a distinguished lineup of speakers and panelists. These included Dr. James Cai from Boehringer Ingelheim, Dr. Jake Chen from The University of Alabama at Birmingham, Dr. Sidi Chen from Yale, and Dr. Yves Lussier from the University of Utah. Drs. Hongyu Zhao, Mark Gerstein, Anthony Koleske, Christian Haslinger, and Maria Fälth Savitski were instrumental in guiding the program committee.
The event kicked off at 8:00 am with a welcome address by Dr. Katie Zhu of Yale University. This was followed by a keynote presentation by Dr. James Cai, who delved into "AI Opportunities and Challenges in Pharma." Cai's talk addressed how AI is transforming pharmaceutical research and development, highlighted current AI applications and limitations in drug discovery, and discussed the future role of AI in this field.
The workshop then moved into a series of presentations focusing on innovative research in AI for drug discovery:
- Babak Ravandi from Alexion and Northeastern University presented on enhancing protein-protein interaction prediction through topology-driven negative sampling.
- Dhananjay Bhaskar, a Yale-BI Fellow mentored by Dr. Smita Krishnaswamy at Yale and Dr. Gregorio Alanis-Lobato from BI, discussed using geometric scattering on biomedical knowledge graphs for indication expansion.
- Xiayuan Huang, another Yale-BI Fellow mentored by Yale’s Dr. Anita Wang and BI’s Drs. Johann de Jong and Zhihao Ding presented new methods to improve patient representation learning from electronic health records using predicted family relations.
- Chuanpeng Dong, also a Yale-BI Fellow co mentored by Drs. Sidi Chen, Hongyu Zhao, and Di Feng, talked about in-silico prediction of collaborative paralog pairs to identify combination partners in cancer immunotherapy.
After a brief coffee break, the session continued with further insightful presentations:
- Rong Li, a Yale-BI Fellow mentored by Dr. Steven Ma from Yale and Dr. Zuojian Tang from BI, discussed incorporating prior information in gene expression network-based cancer heterogeneity analysis to identify molecular subtypes of cancer.
- Huanhuan Wei, another Yale-BI Fellow mentored by Dr. Xiting Yan from Yale and Dr. Alexandra Popa at BI, explored unraveling tissue microenvironments using integrated spatial transcriptomics and multi-modal data through graph networks.
- Zhe Sun, also a Yale-BI Fellow mentored by Drs. Yize Zhao and Gregorio Alanis-Lobato from Yale and BI respectively, presented on boosting prediction accuracy of cognitive ability by integrating node and network imaging traits for a range of CNS disorders.
Dr. Dylan Duchen’s manuscript was also accepted by the workshop. His work was completed under the guidance of Drs. Steven Kleinstein and Ingrid Braenne.
The workshop concluded with an interactive panel session, moderated by Dr. Katie Zhu. Panelists Drs. James Cai, Jake Chen, Sidi Chen, and Yves Lussier discussed the current state and impact of AI in drug discovery, challenges and limitations, emerging trends, and practical impact. The panelists also shared unique insights from their experiences and offered advice to young researchers interested in AI-driven drug discovery.
Dr. Jake Chen delivered the closing remarks, summarizing the key points of the workshop and discussing the future direction of AI in drug discovery. He emphasized the importance of interdisciplinary collaborations and the ethical considerations of using AI in this field.
The event was a resounding success in fostering collaboration and knowledge exchange among leaders in AI and medicine. Participants and conference organizers expressed enthusiasm for future opportunities to work together and advance the field.
The conference also featured several social events, including a welcome reception and a conference dinner at the Natural History Museum, offering ample networking opportunities for workshop attendees to connect and collaborate. The Yale-BI Biomedical Data Science Fellowship Program also organized a dinner event on July 10 to celebrate program accomplishments and the graduation of three fellows: Dhananjay Bhaskar, Zhe Sun, and Xiayuan Huang. Journal editors, investors, and leaders from other universities joined us for the celebration as well.