
Applying Data Science and Artificial Intelligence to Managing Biomedical Portfolios
Andrew Lo, MIT professor of finance, delivers lecture 18 of 18.642, Topics in Mathematics with Applications in Finance, arguing that financial engineering can be redirected at problems like rare disease treatment and the energy transition. He explains how pooling many high-risk, long-duration projects into a single diversified portfolio, modeled on megafunds built for gene therapy research, lowers the risk profile enough to attract institutional capital that would never back a single biotech bet. He extends the same logic to fusion energy financing, walking through how data science and AI tools help estimate success probabilities and correlations across large numbers of scientific projects. The eighty-one minute session mixes portfolio theory with real financing structures, showing students how quantitative methods developed for Wall Street can be repurposed to fund medical and energy breakthroughs that conventional venture capital considers too risky or too slow to pay off.