SenolyticAI combines machine learning target identification with organs-on-chips validation to accelerate the discovery of next-generation senolytic therapeutics.
ML models trained on transcriptomic and proteomic data identify novel senolytic targets across tissue types - validated on microphysiological systems before animal studies.
Human-relevant organs-on-chips test senolytic candidates against aged tissue analogs, eliminating false positives from animal models that don't recapitulate human aging.
In silico absorption, distribution, metabolism, excretion and toxicity profiling narrows lead candidates before costly wet-lab work - cutting discovery timelines by 60%+.
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