Dataset Information

PBPK Models for CYP3A4 and P-gp DDI Prediction: A Modeling Network of Rifampicin, Itraconazole, Clarithromycin, Midazolam, Alfentanil, and Digoxin.

ABSTRACT: According to current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidance documents, physiologically based pharmacokinetic (PBPK) modeling is a powerful tool to explore and quantitatively predict drug-drug interactions (DDIs) and may offer an alternative to dedicated clinical trials. This study provides whole-body PBPK models of rifampicin, itraconazole, clarithromycin, midazolam, alfentanil, and digoxin within the Open Systems Pharmacology (OSP) Suite. All models were built independently, coupled using reported interaction parameters, and mutually evaluated to verify their predictive performance by simulating published clinical DDI studies. In total, 112 studies were used for model development and 57 studies for DDI prediction. 93% of the predicted area under the plasma concentration-time curve (AUC) ratios and 94% of the peak plasma concentration (C_max ) ratios are within twofold of the observed values. This study lays a cornerstone for the qualification of the OSP platform with regard to reliable PBPK predictions of enzyme-mediated and transporter-mediated DDIs during model-informed drug development. All presented models are provided open-source and transparently documented.

SUBMITTER: Hanke N

PROVIDER: S-EPMC6202474 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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PBPK Models for CYP3A4 and P-gp DDI Prediction: A Modeling Network of Rifampicin, Itraconazole, Clarithromycin, Midazolam, Alfentanil, and Digoxin.

Hanke Nina N Frechen Sebastian S Moj Daniel D Britz Hannah H Eissing Thomas T Wendl Thomas T Lehr Thorsten T

CPT: pharmacometrics & systems pharmacology 20180907 10

According to current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidance documents, physiologically based pharmacokinetic (PBPK) modeling is a powerful tool to explore and quantitatively predict drug-drug interactions (DDIs) and may offer an alternative to dedicated clinical trials. This study provides whole-body PBPK models of rifampicin, itraconazole, clarithromycin, midazolam, alfentanil, and digoxin within the Open Systems Pharmacology (OSP) Suite. All models w ...[more]

PMID: 30091221

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Project description:During multidrug combination chemotherapy, activation of the nuclear receptor and the transcription factor human pregnane xenobiotic receptor (hPXR) has been shown to play a role in the development of chemoresistance. Mechanistically, this could occur due to the cancer drug activation of hPXR and the subsequent upregulation of hPXR target genes such as the drug metabolism enzyme, cytochrome P450 3A4 (CYP3A4). In the context of hPXR-mediated drug resistance, hPXR antagonists would be useful adjuncts to PXR-activating chemotherapy. However, there are currently no clinically approved hPXR antagonists in the market. Gefitinib (GEF), a tyrosine kinase inhibitor used for the treatment of advanced non-small-cell lung cancer and effectively used in combinational chemotherapy treatments, is a promising candidate owing to its hPXR ligand-like features. We, therefore, investigated whether GEF would act as an hPXR antagonist when combined with a known hPXR agonist, rifampicin (RIF). At therapeutically relevant concentrations, GEF successfully inhibited the RIF-induced upregulation of endogenous CYP3A4 gene expression in human primary hepatocytes and human hepatocells. Additionally, GEF inhibited the RIF induction of hPXR-mediated CYP3A4 promoter activity in HepG2 human liver carcinoma cells. The computational modeling of molecular docking predicted that GEF could bind to multiple sites on hPXR including the ligand-binding pocket, allowing for potential as a direct antagonist as well as an allosteric inhibitor. Indeed, GEF bound to the ligand-binding domain of the hPXR in cell-free assays, suggesting that GEF directly interacts with the hPXR. Taken together, our results suggest that GEF, at its clinically relevant therapeutic concentration, can antagonize the hPXR agonist-induced CYP3A4 gene expression in human hepatocytes. Thus, GEF could be a potential candidate for use in combinational chemotherapies to combat hPXR agonist-induced chemoresistance. Further studies are warranted to determine whether GEF has sufficient hPXR inhibitor abilities to overcome the hPXR agonist-induced chemoresistance.

Project description:BackgroundBuruli ulcer (BU) is a skin neglected tropical disease (NTD) caused by Mycobacterium ulcerans. WHO-recommended treatment requires 8-weeks of daily rifampicin (RIF) and clarithromycin (CLA) with wound care. Treatment compliance may be challenging due to socioeconomic determinants. Previous minimum Inhibitory Concentration and checkerboard assays showed that amoxicillin/clavulanate (AMX/CLV) combined with RIF+CLA were synergistic against M. ulcerans. However, in vitro time kill assays (TKA) are a better approach to understand the antimicrobial activity of a drug over time. Colony forming units (CFU) enumeration is the in vitro reference method to measure bacterial load, although this is a time-consuming method due to the slow growth of M. ulcerans. The aim of this study was to assess the in vitro activity of RIF, CLA and AMX/CLV combinations against M. ulcerans clinical isolates by TKA, while comparing four methodologies: CFU enumeration, luminescence by relative light unit (RLU) and optical density (at 600 nm) measurements, and 16S rRNA/IS2404 genes quantification.Methodology/principal findingsTKA of RIF, CLA and AMX/CLV alone and in combination were performed against different M. ulcerans clinical isolates. Bacterial loads were quantified with different methodologies after 1, 3, 7, 10, 14, 21 and 28 days of treatment. RIF+AMX/CLV and the triple RIF+CLA+AMX/CLV combinations were bactericidal and more effective in vitro than the currently used RIF+CLA combination to treat BU. All methodologies except IS2404 quantitative PCR provided similar results with a good correlation with CFU enumeration. Measuring luminescence (RLU) was the most cost-effective methodology to quantify M. ulcerans bacterial loads in in vitro TKA.Conclusions/significanceOur study suggests that alternative and faster TKA methodologies can be used in BU research instead of the cumbersome CFU quantification method. These results provide an in vitro microbiological support to of the BLMs4BU clinical trial (NCT05169554, PACTR202209521256638) to shorten BU treatment.

Dataset Information

PBPK Models for CYP3A4 and P-gp DDI Prediction: A Modeling Network of Rifampicin, Itraconazole, Clarithromycin, Midazolam, Alfentanil, and Digoxin.

Publications

PBPK Models for CYP3A4 and P-gp DDI Prediction: A Modeling Network of Rifampicin, Itraconazole, Clarithromycin, Midazolam, Alfentanil, and Digoxin.

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