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Predict drug efficacy in pre-clinical models & in individual patients using astrophysics-grade Bayesian AI
Use molecular data from in-vitro models and cancer biopsies to identify biomarkers for solo and combination treatments, accelerate IND submission, and discover novel treatment strategies
Integrate spatial and bulk molecular data to create "digital twins" of patients for synthetic controls and in silico clinical trial simulation to improve probability of drug success through accurate patient selection
Plug-in genomic and clinical data to identify more effective and versatile biomarkers for any therapeutic or expand indications and synergistic combinations of a drug asset
Help us enable biopharma, diagnostics and healthcare industries to discover better ways to overcome cancer.
Our partners leverage Concr advanced predictive modelling across every stage of therapeutic development to create shared value for the benefit of cancer patients.
Our growth is powered by funding and hands-on support from across three continents.
