This course is the second of two courses that will allow students from graduate programs in life sciences to acquire foundational knowledge for collaborative development and critical evaluation of AI approaches in drug development. This course will emphasize the practical growth of collaborative multidisciplinary skills. The course will apply foundational principles from PCL3107H to an applied setting. Students will participate in co-designing the research questions, research design, and data architecture of authentic projects at the intersection of AI and drug development.

Student teams comprised of students from life science departments and the Department of Computer Science will collaborate to design and articulate the key research design steps required to launch a future collaborative research project. Tutorials will involve co-working sessions facilitated with expert guidance. Students in the life sciences will appreciate the priorities and research approaches of AI data scientists, in order to work together productively and effectively in future projects. Life science students will share their domain-specific scientific expertise and their perspectives about experimental validation with AI data scientists.