Doxorubicin PK/PD modeling in multiple myeloma: towards in silico trials

TL;DR

This paper introduces a simulation tool to optimize doxorubicin treatment for multiple myeloma by modeling drug behavior and effects in cells.

Contribution

A transparent, mechanistically linked PK/PD model for doxorubicin in multiple myeloma, enabling in silico treatment optimization.

Findings

A PK model for doxorubicin was developed and validated using in vitro data from multiple myeloma cells.

A PD model was created to simulate the drug's effects on cell growth and death based on concentration.

The combined PK/PD model allows simulation of various treatment protocols to explore their outcomes.

Abstract

Doxorubicin (DOXO) is a well-known chemotherapy drug, which is widely used in the treatment of Multiple Myeloma (MM), a treatable but not curable type of blood cancer. Here, we propose a pharmacokinetics and pharmacodynamics (PK/PD) simulation environment, aimed at facilitating the optimization of DOXO treatment regimens in MM treatment. The resulting model has a transparent mechanistic structure, which facilitates its use and interpretation. The simulator was developed using a combination of experimental and modeling techniques, starting from in vitro PK/PD experiments conducted on MM cells. In our previous work, we carefully developed a PK model for DOXO in MM cells by fitting experimental data. We now devise a PD model from in vitro data investigating the effect of different concentrations of DOXO on cell growth and death in MM cell populations. The PK model is extended to enable a clear mechanistic link between the PK and the PD models, hence providing a complete PK/PD simulator. We show how the mathematical model can be exploited to simulate different DOXO administration protocols with different dosages, repetitions and exposure times, thus, making it possible to explore the effect of a wide range of treatment protocols easily.

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