Cancer Research Horizons partnered with tech-enabled biotech Turbine to develop novel disease positioning and patient stratification strategies for Cancer Research Horizons’ late-preclinical CDC7 inhibitor programme. CDC7 overexpression is correlated with poor survival in a broad range of cancers, but a clear picture is lacking on which patients could be effectively and safely treated by CDC7 inhibition. The collaboration is accelerated by Turbine’s Simulated Cells platform. Simulated Cells leverages AI/ML in addition to large datasets to mimic the molecular behaviours of a cancer cell and its response to genetic or chemical perturbations. Cancer Research Horizons and Turbine will then validate the Simulated Cells-driven hypotheses in vitro and in vivo, to increase the probability of clinical success of the CDC7 inhibitors.

We recently initiated a collaboration with Predictive Oncology that aims to help determine the cancer types and specific patient populations that our potent small molecule inhibitors of glutaminase could most effectively treat. The collaboration will utilise Predictive Oncology’s PEDAL™ platform, which is an AI/ML platform supported by experimentation from an extensive patient-derived tumour sample bank. PEDAL™ makes high-confidence drug response predictions, enabling a more informed selection of drug–tumour type combinations for clinical development, increasing the probability of clinical success by efficiently addressing tumour heterogeneity during preclinical stages.