Optimization of drug regimen in chemotherapy based on semi-mechanistic model for myelosuppression

[Display omitted] •Three mathematic models are adopted to mimic physiological response of body under chemotherapy.•Simulation results is consistent with clinical data.•Proliferation index affects response rate to different dose schedules.•Model-based prediction of absolute neutrophil counts during chemotherapy is superior to AUC in toxicity management.•The integrated model could offer medical decision support. Based on the latest statistics on trends in cancer incidence and mortality worldwide, cancer burden is growing at an alarming pace. Many anticancer drugs have been proved effective against cancer cells as well as toxic to human tissues, which prevents sufficient doses from being administered to obtain a complete cure. In this paper we build an optimal control model to optimize the scheduling problem along one cycle of chemotherapy treatment using a single anticancer drug etoposide (VP-16). In the model, three mathematic models are adopted to mimic physiological response of body under chemotherapy: (i) Pharmacokinetic model of anticancer drug; (ii) A two-compartment tumor growth dynamic model under the influence of cell-cycle-specific anticancer drugs; and (iii) A semi-mechanistic model for myelosuppression. In this new integrated model clinically relevant objectives are proposed to gain a trade-off between efficacy and toxicity. Simulation results of clinical protocols are consistent with real-life clinical data. Furthermore, we find a new optimal drug regimen which can improve the efficacy without the risk of severe toxicity.