Google DeepMind Co-Scientist 加速逆转细胞衰老研究，数据分析从六个月缩至几天

Two of the biggest bottlenecks in aging research are deciding which genetic pathways to test and making sense of the vast data those experiments produce. Biologists Omar Abudayyeh and Jonathan Gootenberg are using Co-Scientist to help them blast through both.

Their lab runs huge genetic screens that flip thousands of genes on or off then reads how cells respond to these changes. The goal is to find changes that push cells away from senescence – a damaged state linked to aging – and toward a youthful state in tissues such as skin, hair, and muscle.

Co-Scientist is helping on two fronts. First, it generates leads. When the team asked it to trawl the scientific literature for factors that might reverse aging, it scanned tens of thousands of papers, considered a multitude of hypotheses, and ultimately proposed more than 20 novel, plausible genetic factors to test. Lab tests validated a couple Co-Scientist’s hypotheses, with its recommended factors successfully driving cells into a younger state with improved overall function.

Second, Co-Scientist speeds up the follow-through. Once the team has results from a big screen, they have to figure out what the enormous amount of data might mean, and which directions are worth pursuing next. That kind of analysis – trying to connect test results to years of scattered scientific literature – can take a researcher up to six months. Having Co-Scientist analyse their screening data alongside the literature, that work is slashed to just a few days.