Physiologically-Based Pharmacokinetic Modeling to Support the Clinical Management of Drug-Drug Interactions With Bictegravir.
Adult
Amides
/ pharmacokinetics
Cobicistat
/ pharmacokinetics
Cytochrome P-450 CYP3A Inducers
/ pharmacokinetics
Cytochrome P-450 CYP3A Inhibitors
/ pharmacokinetics
Drug Interactions
/ physiology
Female
Glucuronosyltransferase
/ antagonists & inhibitors
Heterocyclic Compounds, 3-Ring
/ pharmacokinetics
Humans
Male
Middle Aged
Models, Biological
Piperazines
/ pharmacokinetics
Pyridones
/ pharmacokinetics
Ritonavir
/ pharmacokinetics
Voriconazole
/ pharmacokinetics
Young Adult
Journal
Clinical pharmacology and therapeutics
ISSN: 1532-6535
Titre abrégé: Clin Pharmacol Ther
Pays: United States
ID NLM: 0372741
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
received:
08
10
2020
accepted:
27
01
2021
pubmed:
25
2
2021
medline:
1
12
2021
entrez:
24
2
2021
Statut:
ppublish
Résumé
Bictegravir is equally metabolized by cytochrome P450 (CYP)3A and uridine diphosphate-glucuronosyltransferase (UGT)1A1. Drug-drug interaction (DDI) studies were only conducted for strong inhibitors and inducers, leading to some uncertainty whether moderate perpetrators or multiple drug associations can be safely coadministered with bictegravir. We used physiologically-based pharmacokinetic (PBPK) modeling to simulate DDI magnitudes of various scenarios to guide the clinical DDI management of bictegravir. Clinically observed DDI data for bictegravir coadministered with voriconazole, darunavir/cobicistat, atazanavir/cobicistat, and rifampicin were predicted within the 95% confidence interval of the PBPK model simulations. The area under the curve (AUC) ratio of the DDI divided by the control scenario was always predicted within 1.25-fold of the clinically observed data, demonstrating the predictive capability of the used modeling approach. After the successful verification, various DDI scenarios with drug pairs and multiple concomitant drugs were simulated to analyze their effect on bictegravir exposure. Generally, our simulation results suggest that bictegravir should not be coadministered with strong CYP3A and UGT1A1 inhibitors and inducers (e.g., atazanavir, nilotinib, and rifampicin), but based on the present modeling results, bictegravir could be administered with moderate dual perpetrators (e.g., efavirenz). Importantly, the inducing effect of rifampicin on bictegravir was predicted to be reversed with the concomitant administration of a strong inhibitor such as ritonavir, resulting in a DDI magnitude within the efficacy and safety margin for bictegravir (0.5-2.4-fold). In conclusion, the PBPK modeling strategy can effectively be used to guide the clinical management of DDIs for novel drugs with limited clinical experience, such as bictegravir.
Identifiants
pubmed: 33626178
doi: 10.1002/cpt.2221
pmc: PMC8597021
doi:
Substances chimiques
Amides
0
Cytochrome P-450 CYP3A Inducers
0
Cytochrome P-450 CYP3A Inhibitors
0
Heterocyclic Compounds, 3-Ring
0
Piperazines
0
Pyridones
0
bictegravir
8GB79LOJ07
UGT1A1 enzyme
EC 2.4.1.-
Glucuronosyltransferase
EC 2.4.1.17
Voriconazole
JFU09I87TR
Cobicistat
LW2E03M5PG
Ritonavir
O3J8G9O825
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1231-1239Informations de copyright
© 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.
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