In Vitro Assessment of Transporter Mediated Perpetrator DDIs for Several Hepatitis C Virus Direct-Acting Antiviral Drugs and Prediction of DDIs with Statins Using Static Models.
HCV drugs
drug interactions
mechanistic static models
statins
transporters
Journal
The AAPS journal
ISSN: 1550-7416
Titre abrégé: AAPS J
Pays: United States
ID NLM: 101223209
Informations de publication
Date de publication:
21 03 2022
21 03 2022
Historique:
received:
09
08
2021
accepted:
21
12
2021
entrez:
22
3
2022
pubmed:
23
3
2022
medline:
3
5
2022
Statut:
epublish
Résumé
Inhibitory effects of asunaprevir, daclatasvir, grazoprevir, paritaprevir, simeprevir, and voxilaprevir, direct-acting antiviral (DAA) drugs for the treatment of chronic hepatitis C virus (HCV) infection, were evaluated in vitro against a range of clinically important drug transporters. In vitro inhibition studies were conducted using transporter transfected cells and membrane vesicles. The risk of clinical drug-drug interactions (DDIs) was assessed using simplified static models recommended by regulatory agencies. Furthermore, we refined and developed static models to predict complex DDIs with several statins (pitavastatin, rosuvastatin, atorvastatin, and pravastatin) by mechanistically assessing differential inhibitory effects of perpetrator drugs on multiple transporters, such as organic anion transporting polypeptides (OATP1B), breast cancer resistance protein (BCRP), multidrug resistance protein 2 (MRP2), organic anion transporter 3 (OAT3), and cytochrome P450 CYP3A enzyme, as they are known to contribute to absorption, distribution, metabolism and excretion (ADME) of above statins. These models successfully predicted a total of 46 statin DDIs, including above DAA drugs and their fix-dose combination regimens. Predicted plasma area under curve ratio (AUCR) with and without perpetrator drugs was within ~ 2-fold of observed values. In contrast, simplified static R-value model resulted in increased false negative and false positive predictions when different prediction cut-off values were applied. Our studies suggest that mechanistic static model is a promising and useful tool to provide more accurate prediction of the risk and magnitude of DDIs with statins in early drug development and may help to improve the management of clinical DDIs for HCV drugs to ensure effective and safe HCV therapy. GRAPHICAL ABSTRACT.
Identifiants
pubmed: 35314909
doi: 10.1208/s12248-021-00677-8
pii: 10.1208/s12248-021-00677-8
doi:
Substances chimiques
ATP Binding Cassette Transporter, Subfamily G, Member 2
0
Antiviral Agents
0
Hydroxymethylglutaryl-CoA Reductase Inhibitors
0
Membrane Transport Proteins
0
Neoplasm Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
45Informations de copyright
© 2022. Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, N.J., U.S.A., under exclusive licence to Springer Nature Switzerland AG.
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