Drugs in R&D (Sep 2019)

Prediction of Drug–Drug Interactions Between Opioids and Overdosed Benzodiazepines Using Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation

  • Beihong Ji,
  • Shuhan Liu,
  • Ying Xue,
  • Xibing He,
  • Viet Hoang Man,
  • Xiang-Qun Xie,
  • Junmei Wang

DOI
https://doi.org/10.1007/s40268-019-00282-3
Journal volume & issue
Vol. 19, no. 3
pp. 297 – 305

Abstract

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Abstract Background Researchers have long been interested in the potential drug–drug interactions (DDIs) between opioids and benzodiazepines. However, much remains unknown concerning the interactions between these two drug classes. The objective of this work is to study the mechanism underlying the DDIs between opioids and benzodiazepines from the perspective of their pharmacokinetic (PK) interactions. A PK interaction occurs when two drugs are metabolized by the same cytochrome P450 enzymes and is one of the most common reasons for DDIs. Methods We quantitatively predicted the DDIs between three opioids (fentanyl, oxycodone and buprenorphine) and four benzodiazepines (alprazolam, diazepam, midazolam and triazolam) using a physiologically based pharmacokinetic (PBPK) modeling approach. A set of PBPK models was first constructed for these common opioids and benzodiazepines using SimCYP software, and the DDIs between them were then explored at various dosages. Results Our simulation results suggested there were no PK interactions between normal doses of opioids and benzodiazepines; but weak interactions can be expected with the combination of opioids and overdosed benzodiazepines. Particular attention should be given to the combination of fentanyl and overdosed alprazolam since a PK interaction can be observed between them. Conclusion Our results appear to indicate that pharmacodynamics may play a more important role than PKs in causing DDIs between opioids and benzodiazepines. This study also demonstrated that molecular modeling can be a very useful tool to mitigate the problem of “missing metabolic reaction parameters” in PK modeling and simulation.