A Physiologically Based Pharmacokinetic Model to Predict the Impact of Metabolic Changes Associated with Metabolic Associated Fatty Liver Disease on Drug Exposure

Elise M. Newman, Andrew Rowland

Research output: Contribution to journalArticlepeer-review

Abstract

Metabolic associated fatty liver disease (MAFLD) is the most common chronic liver disease, with an estimated prevalence of between 20 and 30% worldwide. Observational data supported by in vitro and pre-clinical animal models of MAFLD suggest meaningful differences in drug disposition in MAFLD patients. This study aimed to build a physiologically based pharmacokinetic (PBPK) model reflecting observed changes in physiological and molecular parameters relevant to drug disposition that are associated with MAFLD. A comprehensive literature review and meta-analysis was conducted to identify all studies describing in vivo physiological changes along with in vitro and pre-clinical model changes in CYP 1A2, 2C9, 2C19, 2D6 and 3A4 protein abundance associated with MAFLD. A MAFLD population profile was constructed in Simcyp (version 19.1) by adapting demographic and physiological covariates from the Sim-Healthy population profile based on a meta-analysis of observed data from the published literature. Simulations demonstrated that single dose and steady state area under the plasma concentration time curve (AUC) for caffeine, clozapine, omeprazole, metoprolol, dextromethorphan and midazolam, but not s-warfarin or rosiglitazone, were increased by >20% in the MAFLD population compared to the healthy control population. These findings indicate that MAFLD patients are likely to be experience meaningfully higher exposure to drugs that are primarily metabolized by CYP 1A2, 2C19, 2D6 and 3A4, but not CYP2C9. Closer monitoring of MAFLD patients using drugs primarily cleared by CYP 1A2, 2C19 and 3A4 is warranted as reduced metabolic activity and increased drug exposure are likely to result in an increased incidence of toxicity in this population.

Original languageEnglish
Article number11751
Number of pages13
JournalInternational Journal of Molecular Sciences
Volume23
Issue number19
DOIs
Publication statusPublished - 1 Oct 2022

Keywords

  • liver disease
  • metabolism
  • non-alcoholic fatty liver disease (NAFLD)
  • pharmacokinetic model
  • simulation

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