The Bottom Line: AI system Co-Scientist dramatically accelerates aging research: researchers can analyze screening data in days instead of six months. The system has already identified over 20 new genetic candidates for reversing cellular aging, several of which have been experimentally validated.
Bioscientists Omar Abudayyeh and Jonathan Gootenberg are using the AI system Co-Scientist to address two central challenges in aging research: identifying relevant genetic pathways and analyzing large amounts of data from genetic screening experiments.
The two researchers conduct extensive genetic screenings that turn thousands of genes on or off and measure cellular responses. The goal is to find genetic changes that move cells out of senescence – a state marked by damage and associated with aging – into a more youthful state, particularly in tissues such as skin, hair, and muscle.
Co-Scientist supports the research team on two levels. First, the system generates new hypotheses: when searching scientific literature for factors that could reverse aging processes, Co-Scientist analyzed tens of thousands of publications and ultimately proposed over 20 new, promising genetic factors to test. Laboratory studies confirmed several of these hypotheses – the factors recommended by the AI actually caused cells to adopt a younger state with improved overall function.
Second, Co-Scientist significantly accelerates data analysis. After large screening experiments, researchers must interpret the enormous amounts of data and identify promising research directions. This analysis – connecting test results with years of scattered specialist literature – normally requires up to six months. With Co-Scientist as an analysis tool, this work is reduced to just a few days.