Scientific Reports (Feb 2023)

In vitro to clinical translational pharmacokinetic/pharmacodynamic modeling of doxorubicin (DOX) and dexrazoxane (DEX) interactions: Safety assessment and optimization

  • Hardik Mody,
  • Tanaya R. Vaidya,
  • Sihem Ait-Oudhia

DOI
https://doi.org/10.1038/s41598-023-29964-4
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 11

Abstract

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Abstract Despite high anticancer activity, doxorubicin (DOX)-induced cardiotoxicity (DIC) limits the extensive utility of DOX in a clinical setting. Amongst various strategies explored, dexrazoxane (DEX) remains the only cardioprotective agent to be approved for DIC. In addition, altering the dosing regimen of DOX has also proved to be somewhat beneficial in decreasing the risk of DIC. However, both approaches have limitations and further studies are required to better optimize them for maximal beneficial effects. In the present work, we quantitatively characterized DIC as well as the protective effects of DEX in an in vitro model of human cardiomyocytes, by means of experimental data and mathematical modeling and simulation (M&S) approaches. We developed a cellular-level, mathematical toxicodynamic (TD) model to capture the dynamic in vitro drug-drug interaction, and relevant parameters associated with DIC and DEX cardio-protection were estimated. Subsequently, we executed in vitro-in vivo translation by simulating clinical PK profiles for different dosing regimens of DOX alone and in combinations with DEX and using the simulated PK profiles to drive the cell-based TD models to evaluate the effects of long-term, clinical dosing regimens of these drugs on the relative cell viability of AC16 and to determine optimal drug combinations with minimal cellular toxicity. Here, we identified that the Q3W (once every three weeks) DOX regimen with 10:1 DEX:DOX dose ratio over three cycles (nine weeks) may offer maximal cardio-protection. Overall, the cell-based TD model can be effectively used to better design subsequent preclinical in vivo studies aimed for further optimizing safe and effective DOX and DEX combinations to mitigate DIC.