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Jacob Kimmel
@jacobkimmel
Co-founder & CEO @NewLimit | Interested in aging, machine learning, genomics, the technology production function
加入 April 2008
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this summer @newlimit, we built our first prototype medicine that restores multiple youthful functions in old hepatocytes. rejuvenating old cells across multiple dimensions seems more possible today than just months ago. recent highlights - +3 TF sets that restore function in old hepatocytes, +11 in T cells - +>4000 TF sets tested - 100X improvement in compute efficiency for in silico design of reprogramming payloads - >60% improvement in discoveries/experiment with AI models # restoring youthful function in multiple dimensions the premise of NewLimit is that if we’re able to restore youthful function in old cells, this could treat multiple pathologies that arise with age. this summer, we built a prototype medicine (M0004) that restored function in multiple disease models, demonstrating this thesis in practice for the first time. in these experiments, M0004 made old hepatocytes more resilient to damage from alcohol and more regenerative after surgical injuries. old cells are markedly worse than young cells on both of these axes. these data are still preliminary, but deepen our conviction that it’s possible to restore youthful function across multiple dimensions. # generative design of reprogramming payloads there are ~10^16 plausible reprogramming payloads that might reverse cell age. no matter how clever we are, we'll never test all of them experimentally. we've been building AI models to predict reprogramming effects in silico to prioritize the experiments we run in the real world. given a desired cell state (e.g. young), we use models to generate reprogramming payloads that may be effective. last month, we developed a new algorithm that requires 100X less compute and achieves a >60% improvement in discoveries/experiment vs. a human baseline. we believe this represents one of the first biological discovery systems where AI models now recommend most hypotheses we test. # growing a data corpus performance in our AI models emerges as a result of our unique data corpus. this summer, we ran more Discovery Engine screens than ever before and recorded our first quarter with 0 QC failures. we've found that scaling laws for the performance of our AI models continue to hold in this larger data regime. this phenomenon gives us confidence that investments in our experimental scale & success rates will continue to yield dividends for many years to come. # we're at the beginning all of us @newlimit are excited by the data that now readily emerge from our models and laboratory. alongside our recent fundraising, we’re expanding to build reprogramming medicines across even more therapeutic areas. if you're excited by our mission, reach out to join us for the next chapter.
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