What if AI could help design gene therapies so precise they eliminate chronic pain while leaving other senses completely intact? And what if the secret to treating Parkinson's Disease lies hidden in the genome of a mouse?

In this episode, we explore groundbreaking advances in genetic medicine with Andreas Pfenning, Associate Professor in Carnegie Mellon University's Computational Biology Department and School of Computer Science. Professor Pfenning discusses research in his experimental lab, and how AI is revolutionizing gene therapy by making treatments more targeted while reducing toxic side effects.

The conversation covers Pfenning's work developing precision gene therapies for chronic pain originating in the spine, where AI helps identify exactly which spinal cord cells transmit pain signals while preserving normal touch and movement functions. The episode also explores KGWAS (Knowledge Graph Genome-Wide Association Study), an AI-powered tool developed at CMU in partnership with other research institutions, that helps identify genetic problems that can cause rare diseases or disorders.

Pfenning shares insights from his collaboration on the ambitious Vertebrate Genomes Project, which aims to map genomes from more than 500 vertebrate species. This massive international effort is revealing surprising genetic similarities across species that could unlock new treatments for human diseases including Parkinson's, Alzheimer's, and other neurological disorders.

The discussion also highlights how machine learning is accelerating the path from laboratory discovery to clinical applications, with promising results already emerging in Parkinson's disease treatment trials.