4.4 Article

Minimal PK/PD model for simultaneous description of the maximal tolerated dose and metronomic treatment outcomes in mouse tumor models

Journal

CANCER CHEMOTHERAPY AND PHARMACOLOGY
Volume 88, Issue 5, Pages 867-878

Publisher

SPRINGER
DOI: 10.1007/s00280-021-04326-x

Keywords

Metronomic chemotherapy; Computational oncology; Pharmacokinetics; Pharmacodynamics

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The study proposed a simple model that can describe both metronomic chemotherapy and maximum tolerated dose regimens, and validated its efficacy through experimental data.
Purpose Metronomic chemotherapy (MC) is a promising approach where, in contrast to the conventional maximal tolerated dose (MTD) strategy, regular fractionated doses of the drug are used. This approach has proven its efficacy, although drug dosing and scheduling are often chosen empirically. Pharmacokinetic/pharmacodynamic (PK/PD) models provide a way to choose optimal protocols with computational methods. Existing models are usually too complicated and are valid for only a subset of drug schedules. To address this issue, we propose herein a simple model that can describe MC and MTD regimens simultaneously. Methods The minimal model comprises tumor suppression due to antiangiogenic drug effect together with a cell-kill term, responsible for its cytotoxicity. The model was tested on data obtained on tumor-bearing mice treated with gemcitabine in ether MTD, MC, or combined (MTD + MC) regimens. Results We conducted a number of tests in which data were divided in various ways into training and validation sets. The model successfully described different trends in the MTD and MC regimens. With parameters obtained by fitting the model to MTD data, the simulations correctly predicted trends in both the MC and combined therapy groups. Conclusion Our results demonstrate that the proposed model presents a minimal yet efficient tool for modeling outcomes in different treatment regimens in mice. We hope that this model has the potential for use in clinical practice in the development of patient-specific chemotherapy scheduling protocols based on observed treatment response.

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