AI agents in biomedical research
Harvard University
Abstract:
LLM-based agents are increasingly used in biomedical research pipelines, for literature synthesis, data analysis, hypothesis generation, and clinical decision support. This talk provides an overview of how these systems work and where they break. We cover the core architectural components of single and multi-agent systems, as well as current evaluation benchmarks and failure mechanisms specific to biomedical applications. The talk may serve as a practical guide for developing and evaluating these systems, with consideration of failure modes most consequential in biomedical settings.
Biography:
Maha Shady is a postdoctoral fellow in the Van Allen Lab at the Dana Farber Cancer Institute. She completed her PhD in Biomedical Informatics at Harvard Medical School in 2025. Her dissertation focused on the development of computational models to understand cancer initiation and to create precision oncology frameworks for clinical decision support. She is generally interested in the development of domain-informed computational models for biological discovery and precision medicine, with a focus on both machine learning and mechanistic models.