AI models need more data about biology, and OpenAI is paying to create it

Last year, the clinical trial policy analyst Ruxandra Teslo posted an idea for super-charging medical AI systems: use data from failed biotech companies. By bidding at their bankruptcy proceedings, she proposed, it might be possible to obtain detailed regulatory filings, manufacturing strategies, a…

Résumé

AI needs more biology data

Artificial intelligence (AI) models require vast amounts of high-quality data to make meaningful advances in medicine, particularly in areas like drug development and disease treatment.

According to Morgan Levine, a former vice president at Altos Labs, a company focused on longevity research, data is the biggest bottleneck preventing AI from achieving breakthroughs in biology.

Currently, AI systems lack sufficient information to navigate complex processes such as drug approvals, which are often opaque and involve extensive regulatory filings.

The OpenAI Foundation, the nonprofit parent of OpenAI, has acknowledged this gap and launched an initiative called Data for Public Health to fund the creation of new scientific datasets specifically designed to train AI models in medicine.

The foundation aims to address this shortage by supporting projects that generate or curate biological and medical data, enabling AI to assist more effectively in healthcare.