Optimal scheduling of low-dose metronomic chemotherapy: an in-silico analysis

Abstract

Low-dose metronomic (LDM) chemotherapy shows promising results in cancer treatment. However, the scheduling of the therapy, including the determination of the optimal biologic dose is usually based on empiricism. This paper contributes to an in-silico analysis targeting parameter optimization of LDM chemotherapy design. The in-treatment tumor growth model used by the analysis formulates tumor proliferation and necrosis, dead tumor cell washout, as well as pharmacokinetics and pharmacodynamics of the administered drug. The model parameters are identified based on mouse experiments. The optimization goal is the minimization of the total amount of drug delivered throughout the full length of the therapy with governing constraints ensuring the efficacy of the treatment. Results show that a clear optimum exists in the scheduling of the treatments, that is, an optimal choice for the rest periods can be done. The optimum is independent of the length of the therapy, and only slightly depends on the parameter sets of the individual patients.