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: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.

Project description:We have reported that the P-gp substrate digoxin required basolateral and apical uptake transport in excess of that allowed by digoxin passive permeability (as measured in the presence of GF120918) to achieve the observed efflux kinetics across MDCK-MDR1-NKI (The Netherlands Cancer Institute) confluent cell monolayers. That is, GF120918 inhibitable uptake transport was kinetically required. Therefore, IC50 measurements using digoxin as a probe substrate in this cell line could be due to inhibition of P-gp, of digoxin uptake transport, or both. This kinetic analysis is now extended to include three additional cell lines: MDCK-MDR1-NIH (National Institute of Health), Caco-2 and CPT-B2 (Caco-2 cells with BCRP knockdown). These cells similarly exhibit GF120918 inhibitable uptake transport of digoxin. We demonstrate that inhibition of digoxin transport across these cell lines by GF120918, cyclosporine, ketoconazole and verapamil is greater than can be explained by inhibition of P-gp alone. We examined three hypotheses for this non-P-gp inhibition. The inhibitors can: (1) bind to a basolateral digoxin uptake transporter, thereby inhibiting digoxin's cellular uptake; (2) partition into the basolateral membrane and directly reduce membrane permeability; (3) aggregate with digoxin in the donor chamber, thereby reducing the free concentration of digoxin, with concomitant reduction in digoxin uptake. Data and simulations show that hypothesis 1 was found to be uniformly acceptable. Hypothesis 2 was found to be uniformly unlikely. Hypothesis 3 was unlikely for GF120918 and cyclosporine, but further studies are needed to completely adjudicate whether hetero-dimerization contributes to the non-P-gp inhibition for ketoconazole and verapamil. We also find that P-gp substrates with relatively low passive permeability such as digoxin, loperamide and vinblastine kinetically require basolateral uptake transport over that allowed by +GF120918 passive permeability, while highly permeable P-gp substrates such as amprenavir, quinidine, ketoconazole and verapamil do not, regardless of whether they actually use the basolateral transporter.

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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