Causal Bio builds ODE-based signaling pathway models to identify why targeted therapies fail — PD-efficacy disconnects, resistance emergence, combination response — before the next trial.
Trial data, biomarker readouts, and clinical context reviewed to identify mechanistically plausible failure modes.
Pathway models calibrated against literature-derived constraints spanning multiple biological contexts.
Simulations across genotypic and phenotypic contexts identify where biology diverged from the drug's intended mechanism.
Resistance hypotheses, combination response, and patient stratification with mechanistic justification.
Rohit Nandakumar is a computational biologist trained at Carnegie Mellon University. Causal Bio's platform was built from the ground up — pathway topology, ODE architecture, calibration pipeline, and constraint validation — as a unified system for oncology drug response modeling. The approach is deliberately mechanistic: signaling networks modeled as dynamic systems, not static interaction databases.
Retrospective analysis on past programs with unclear mechanistic explanations, or prospective prediction for active programs before the next trial decision.
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