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, and safety data—information usually kept hidden as valuable trade secrets. She called these…
OpenAI's nonprofit foundation has pledged $40 million to a project aimed at enhancing medical AI systems by amassing data from failed biotech firms. The initiative, known as Data for Public Health, intends to bolster AI's capacity to aid in the creation of groundbreaking medical breakthroughs. The data grants will target the accumulation of information about novel cancer vaccines at the University of North Carolina, Chapel Hill, and will also support a competition centered on predicting drug effects, run by OpenAdmet.
Ruxandra Teslo, a clinical trial policy analyst, proposed the inception of this idea, referring to the data as "biotech's lost archive." Her proposal received a $500,000 grant and will be pursued by 1Day Sooner, an advocacy group advising Teslo. The OpenAI Foundation, which is part of the for-profit OpenAI corporation, anticipates that the increased data availability could catalyze significant advancements in curing diseases.
However, the foundation's leadership and resources are still in the process of scaling up, and the endeavor may prove to be a daunting challenge. Despite the ongoing concerns regarding the potential risks of uncontrolled AI development, OpenAI's foundation remains committed to its mission of ensuring that artificial intelligence benefits humanity.
Written by urgent.news from MIT Tech Review Biotech's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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