A Proof-of-Concept Clinical Trial Design for Evolutionary Guided Precision Medicine for Cancer

Oregon Convention Center 

Current Precision Medicine (CPM) matches cancer therapies to consensus molecular characteristics at one or more timepoints. However, it is well-known that cancers contain extensive subclonal heterogeneity and that their subclonal compositions evolve dynamically in response to therapy. Mathematical modeling of this subclonal evolution has the potential to optimize the timing and sequencing of therapies in an even more effective and personalized manner than CPM. Clinical trial designs that test Evolutionary Guided Precision Medicine (EGPM) strategies that may prevent or delay relapse thereby improving outcomes, are needed. We evaluated Dynamic Precision Medicine (DPM), an EGPM, vs CPM in a stratified randomized design with two strata based on whether the patient was predicted to benefit from DPM, using an evolutionary classifier. We present this new proof-of-concept clinical trial design for this purpose and perform computer simulations which show high power, control of false positive rates, and robust performance in the face of anticipated challenges to clinical translation. The design is distinct from biomarker-driven designs of CPM, and can provide a robust evaluation of EGPM.

Precision Medicine

Clinical Trial Design

Tumour Evolution

Oncology 

Biopharmaceutical Section