Join Us March 4 for AI in the Drug Discovery Landscape
Wednesday, March 4, 2026, at 1:00-2:30 p.m., eastern time, US. (12:00-1:30 p.m., central time / 11:00-12:30 mountain / 10:00-11:30 pacific)
The Technology in Education Caucus (TEC), Medical Informatics Caucus, and Pharmacy and Drug Information (PDI) Caucus are excited to host this timely webinar.
This 90-minute webinar with a talk and informal Q&A will be led by Anne Brown, associate professor with the University Libraries/Department of Biochemistry at Virginia Tech, affiliate faculty member in the Academy of Integrated Science, and a Data Science Fellow. Anne Brown, PhD, will discuss the evolving drug discovery landscape and its intersection with data science, Artificial Intelligence (AI), and Machine Learning (ML) practices. She will provide an overview of the drug discovery landscape, highlighting key tools librarians can recommend, along with important caveats and emphasis on good data science principles in an era of machine learning and generative AI. Real-world examples will illustrate success and failures, including challenges such as predatory journal publishing practices and controversies around data availability, such as the decision of the journal Nature to publish pseudocode for AlphaFold3.
Dr. Brown will connect these issues to core librarian roles—supporting researchers with citation guidance, critical appraisal, grant proposals, and publishing—including equipping participants with strategies to help patrons evaluate research quality and navigate ethical considerations related to the use of AI in research. The goal is to foster informed conversations and empower librarians to integrate these insights into their existing outreach and support activities.
Share your questions for Anne Brown, PhD, ahead of the webinar.