Physiologically Based Pharmacokinetic Modelling of Prominent Oral Contraceptive Agents and Applications in Drug-Drug Interactions.


Journal

CPT: pharmacometrics & systems pharmacology
ISSN: 2163-8306
Titre abrégé: CPT Pharmacometrics Syst Pharmacol
Pays: United States
ID NLM: 101580011

Informations de publication

Date de publication:
21 Dec 2023
Historique:
revised: 24 11 2023
received: 04 08 2023
accepted: 13 12 2023
medline: 22 12 2023
pubmed: 22 12 2023
entrez: 22 12 2023
Statut: aheadofprint

Résumé

Considerable interest remains across the pharmaceutical industry and regulatory landscape in capabilities to model oral contraceptives (OCs), whether combined (COCs) with ethinyl estradiol (EE) or progestin-only pill (PoP). Acceptance of COC drug-drug interaction (DDI) assessment using PBPK is often limited to the estrogen component (EE), requiring further verification, with extrapolation from EE to progestins discouraged. There is a paucity of published progestin component PBPK models to support the regulatory DDI guidance for industry to evaluate a new chemical entity's (NCE) DDI potential with COCs. Guidance recommends a clinical interaction study to be considered if, an investigational drug is a weak or moderate inducer, or a moderate/strong inhibitor, of CYP3A4. Therefore, availability of validated OC PBPK models within one software platform, will be useful in predicting the DDI potential with NCEs earlier in the clinical development. Thus, this work was focused on developing and validating PBPK models for progestins, DNG, DRSP, LNG and NET, within Simcyp®, and assessing the DDI potential with known CYP3A4 inhibitors (e.g., ketoconazole) and inducers (e.g., rifampicin) with published clinical data. In addition, this work demonstrated confidence in the Simcyp® EE model for regulatory and clinical applications by extensive verification in 70+ clinical PK and CYP3A4 interaction studies. The results provide greater capability to prospectively model clinical CYP3A4 DDI with COCs using Simcyp® PBPK to interrogate the regulatory decision-tree to contextualise the potential interaction by known perpetrators and NCEs, enabling model-informed decision making, clinical study designs and delivering potential alternative COC options for women of childbearing potential.

Identifiants

pubmed: 38130003
doi: 10.1002/psp4.13101
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

This article is protected by copyright. All rights reserved.

Auteurs

Gareth J Lewis (GJ)

Drug Metabolism and Pharmacokinetics, In Vitro In Vivo Translation, Research, GlaxoSmithKline, Stevenage, United Kingdom.

Deepak Ahire (D)

Washington State University, US.

Kunal S Taskar (KS)

Drug Metabolism and Pharmacokinetics, In Vitro In Vivo Translation, Research, GlaxoSmithKline, Stevenage, United Kingdom.

Classifications MeSH