Harvard Conference Explores AI in Quantitative Genomics

Experts gathered at Harvard Medical School to discuss using artificial intelligence to combine genomic and clinical data for disease prediction.

Updated on Nov. 5, 2026 in Biotech

Modern glass-and-brick research building facade on a Boston medical campus under soft overcast autumn light, with a russet tree in the foreground. — Experts gathered at Harvard Medical School on Oct. 29-30 to discuss using artificial intelligence to combine genomic and clinical data for disease prediction. AI Illustration. Upload story photo >

Harvard T.H. Chan School of Public Health hosted the Program in Quantitative Genomics conference on Oct. 29-30. About 15 leading experts from genomics and clinical research presented to 130 participants.

Why it matters

The conference highlighted efforts to integrate genomic, molecular, clinical, and lifestyle data into a unified patient view using AI. Such approaches aim to improve disease prediction and treatment decisions in Boston's major medical research community.

The event drew about 15 speakers from genomics and clinical research to a gathering of 130 participants over two days. Specific clinical outcomes or validated results from the presented AI models were not reported.

The players

Harvard T.H. Chan School of Public Health

The Boston-based public health school of Harvard University, known for research in epidemiology, biostatistics, and genomics.

Xihong Lin

A Harvard professor of biostatistics who organized the conference and leads research in statistical genetics and genomics.

Eric Xing

A computer scientist affiliated with Mohamed bin Zayed University of Artificial Intelligence and Carnegie Mellon University who spoke on generative AI models of a virtual cell.

Sylvia Plevritis

A Stanford University researcher who discussed combining multiscale modeling with multimodal AI to improve lung cancer outcomes.

Marinka Zitnik

A Harvard Medical School researcher who presented on human-AI co-science and AI agents for treatment recommendations.

The details

Organized by biostatistics professor Xihong Lin, the conference was held at Harvard Medical School's Joseph B. Martin Conference Center. Presentations covered generative AI models of a virtual cell, multiscale modeling for lung cancer outcomes, AI agents for immunotherapy and rare disease treatment, and kidney disease, drug discovery, and AI safety.

Oct. 29-30, 2025: Program in Quantitative Genomics conference held at Harvard.

The Big Picture

The conference reflects Harvard's quantitative genomics program focusing on AI-driven integration of multimodal health data. It places Boston's academic medical institutions at the center of efforts to apply machine learning to clinical prediction.

The AI approaches discussed could eventually inform how clinicians combine genetic and clinical records when making treatment choices. Patients are not directly affected by the conference itself, which presented research rather than approved care.

The takeaway

Combining genomic, clinical, and lifestyle data with AI is a major research direction in biomedicine. Readers interested in its progress can follow academic conferences and peer-reviewed publications from institutions such as Harvard and Stanford.