Pathos

Model clinical trials and identify oncology patient populations using multimodal health data

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You can use Pathos to improve clinical trial planning and drug development for precision oncology. The system combines millions of multimodal oncology records, including genomics, transcriptomics, medical imaging, and longitudinal patient outcomes, with biological modeling. You can simulate trial scenarios using computational agents to understand mechanisms of response and resistance. By finding specific patient subgroups most likely to benefit from experimental therapies, teams can select optimal trial cohorts, reduce failure rates in early-stage oncology trials, and accelerate the progression of clinical programs.

What Pathos does

Simulate clinical trial patient cohortsMap patient genomics to treatment response dataIdentify predictive biomarkers for cancer therapiesAnalyze longitudinal patient health outcomesCorrelate medical imaging with multiomic tumor profilesAssess biological mechanisms of drug resistanceConnects millions of multimodal oncology records across genomics, imaging, and clinical outcomesSimulates thousands of clinical trial scenarios using automated agentsIdentifies patient subgroups most likely to respond to candidate cancer therapiesAnalyzes causal mechanisms behind treatment response and drug resistanceIntegrates transcriptomics and longitudinal real-world patient evidenceInforms clinical trial execution decisions using real-time predictive models