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In Silico Prediction of Cytochrome P450‐Based Drug‐Drug Interactions in Breast Cancer Treatment Regimens
Author(s) -
Arrighi Scott,
Hernandez Layrette,
Deb Subrata
Publication year - 2020
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2020.34.s1.07142
Subject(s) - breast cancer , pharmacology , paclitaxel , drug , medicine , docetaxel , cancer , drug interaction , concomitant , pharmacokinetics , oncology
Breast cancer is one of the most frequently diagnosed cancers in US. Its treatment regimens are complex as they involve premedications and concomitant medications, and can result in drug‐drug interactions (DDI). There are limited data available on cytochrome P450 (CYP)‐based drug interactions within the breast cancer regimens. The goal of the current study was to predict DDI between the drugs in the breast cancer treatment regimens. Methods Using the National Comprehensive Cancer Network (NCCN) guidelines the treatment regimens for breast cancer were identified. In silico DDI predictions were performed at steady state simulation using DDI module of the GastroPlus software provided by Simulation Plus Inc. The premedication and concomitantly administered drugs were evaluated as combinations with chemotherapeutic agents. Various enzyme inhibition kinetics parameters (e.g., Ki and EC50) required for simulation were obtained from the recent literature. Results Using the simulated and calculated gut and liver unbound perpetrator concentration during the steady state simulation, combinations of drugs showed differential DDI potential. Aprepitant, an antiemetic agent, showed moderate to strong inhibition when used with docetaxel, paclitaxel, abemaciclib and olaparib. In certain cases calculated liver perpetrator concentration showed a stronger inhibitory prediction of chemotherapeutic agents compared to simulated liver perpetrator concentration. Results obtained with netupitant varied from weak to strong inhibitory interactions with chemotherapeutic agents. Conclusions In silico analyses appear to confirm that breast cancer treatment regimens may interact with each other and influence plasma concentrations of chemotherapeutic agents. We conclude that toxicity or therapeutic failure from anticancer agents could be due to interactions within the breast cancer treatment regimens. Support or Funding Information The GastroPlus software 9.5 version was provided by Simulations Plus, Inc. (Lancaster, CA)