Evidence for
better drugs

We use AI and population scale data to provide predictive evidence on clinical efficacy. We de-risk development and increase the likelihood of success.
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We are witnessing a Cambrian explosion of biomedical data.

Yet, we still cannot answer the most basic medical questions for the vast majority of diseases: who gets sick in the first place? What characterizes people once they are diagnosed? Who continues to get complications? These answers are necessary to develop safe and effective drugs. We integrate billions of data points of human-centric data to provide answers in silico and at scale. Our platform generates actionable evidence to de-risk development and increase the likelihood of success.

Embed predictive evidence across all stages of the pipeline.

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Target discovery

Identify the effective targets with evidence from thousands of subclinical phenotypes and natural genetic experiments.

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Target validation

Validate established targets across thousands of subclinical phenotypes and clinical endpoints in silico, before investing in clinical trials.

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Stratification biomarkers

Inform clinical development with powerful biomarkers to stratify patient populations, validate MoA hypotheses and select the right patients.

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Prognostic enrichment

Identify high risk individuals with subclinical phenotypes to prognostically enrich clinical trials reducing failure risk and cost.

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