A Comprehensive Whole-Body Physiologically Based Pharmacokinetic Drug-Drug-Gene Interaction Model of Metformin and Cimetidine in Healthy Adults and Renally Impaired Individuals.


Journal

Clinical pharmacokinetics
ISSN: 1179-1926
Titre abrégé: Clin Pharmacokinet
Pays: Switzerland
ID NLM: 7606849

Informations de publication

Date de publication:
11 2020
Historique:
pubmed: 26 5 2020
medline: 22 9 2021
entrez: 26 5 2020
Statut: ppublish

Résumé

Metformin is a widely prescribed antidiabetic BCS Class III drug (low permeability) that depends on active transport for its absorption and disposition. It is recommended by the US Food and Drug Administration as a clinical substrate of organic cation transporter 2/multidrug and toxin extrusion protein for drug-drug interaction studies. Cimetidine is a potent organic cation transporter 2/multidrug and toxin extrusion protein inhibitor. The objective of this study was to provide mechanistic whole-body physiologically based pharmacokinetic models of metformin and cimetidine, built and evaluated to describe the metformin-SLC22A2 808G>T drug-gene interaction, the cimetidine-metformin drug-drug interaction, and the impact of renal impairment on metformin exposure. Physiologically based pharmacokinetic models were developed in PK-Sim The established physiologically based pharmacokinetic models adequately describe the available clinical data, including the investigated drug-gene interaction, drug-drug interaction, and drug-drug-gene interaction studies, as well as the metformin exposure during renal impairment. All modeled drug-drug interaction area under the curve and maximum concentration ratios are within 1.5-fold of the observed ratios. The clinical data of renally impaired patients shows the expected increase in metformin exposure with declining kidney function, but also indicates counter-regulatory mechanisms in severe renal disease; these mechanisms were implemented into the model based on findings in preclinical species. Whole-body physiologically based pharmacokinetic models of metformin and cimetidine were built and qualified for the prediction of metformin pharmacokinetics during drug-gene interaction, drug-drug interaction, and different stages of renal disease. The model files will be freely available in the Open Systems Pharmacology model repository. Current guidelines for metformin treatment of renally impaired patients should be reviewed to avoid overdosing in CKD3 and to allow metformin therapy of CKD4 patients.

Sections du résumé

BACKGROUND
Metformin is a widely prescribed antidiabetic BCS Class III drug (low permeability) that depends on active transport for its absorption and disposition. It is recommended by the US Food and Drug Administration as a clinical substrate of organic cation transporter 2/multidrug and toxin extrusion protein for drug-drug interaction studies. Cimetidine is a potent organic cation transporter 2/multidrug and toxin extrusion protein inhibitor.
OBJECTIVE
The objective of this study was to provide mechanistic whole-body physiologically based pharmacokinetic models of metformin and cimetidine, built and evaluated to describe the metformin-SLC22A2 808G>T drug-gene interaction, the cimetidine-metformin drug-drug interaction, and the impact of renal impairment on metformin exposure.
METHODS
Physiologically based pharmacokinetic models were developed in PK-Sim
RESULTS
The established physiologically based pharmacokinetic models adequately describe the available clinical data, including the investigated drug-gene interaction, drug-drug interaction, and drug-drug-gene interaction studies, as well as the metformin exposure during renal impairment. All modeled drug-drug interaction area under the curve and maximum concentration ratios are within 1.5-fold of the observed ratios. The clinical data of renally impaired patients shows the expected increase in metformin exposure with declining kidney function, but also indicates counter-regulatory mechanisms in severe renal disease; these mechanisms were implemented into the model based on findings in preclinical species.
CONCLUSIONS
Whole-body physiologically based pharmacokinetic models of metformin and cimetidine were built and qualified for the prediction of metformin pharmacokinetics during drug-gene interaction, drug-drug interaction, and different stages of renal disease. The model files will be freely available in the Open Systems Pharmacology model repository. Current guidelines for metformin treatment of renally impaired patients should be reviewed to avoid overdosing in CKD3 and to allow metformin therapy of CKD4 patients.

Identifiants

pubmed: 32449077
doi: 10.1007/s40262-020-00896-w
pii: 10.1007/s40262-020-00896-w
pmc: PMC7658088
doi:

Substances chimiques

Hypoglycemic Agents 0
Cimetidine 80061L1WGD
Metformin 9100L32L2N

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1419-1431

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Auteurs

Nina Hanke (N)

Clinical Pharmacy, Saarland University, Campus C2 2, 66123, Saarbrücken, Germany.

Denise Türk (D)

Clinical Pharmacy, Saarland University, Campus C2 2, 66123, Saarbrücken, Germany.

Dominik Selzer (D)

Clinical Pharmacy, Saarland University, Campus C2 2, 66123, Saarbrücken, Germany.

Naoki Ishiguro (N)

Kobe Pharma Research Institute, Nippon Boehringer Ingelheim Co. Ltd., Kobe, Japan.

Thomas Ebner (T)

Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Sabrina Wiebe (S)

Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.
Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany.

Fabian Müller (F)

Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.
Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Peter Stopfer (P)

Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Valerie Nock (V)

Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Thorsten Lehr (T)

Clinical Pharmacy, Saarland University, Campus C2 2, 66123, Saarbrücken, Germany. thorsten.lehr@mx.uni-saarland.de.

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Classifications MeSH