Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict CYP3A-Mediated Drug Interaction between Saxagliptin and Nicardipine: Bridging Rat-to-Human Extrapolationopen access

Authors
Lee, Jeong-MinYoon, Jin-HaMaeng, Han-JooKim, Yu Chul
Issue Date
Feb-2024
Publisher
MDPI
Keywords
drug-drug interaction; nicardipine; saxagliptin; PBPK modeling
Citation
PHARMACEUTICS, v.16, no.2
Journal Title
PHARMACEUTICS
Volume
16
Number
2
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/90773
DOI
10.3390/pharmaceutics16020280
ISSN
1999-4923
1999-4923
Abstract
The aim of this study was to predict the cytochrome P450 3A (CYP3A)-mediated drug-drug interactions (DDIs) between saxagliptin and nicardipine using a physiologically based pharmacokinetic (PBPK) model. Initially, in silico and in vitro parameters were gathered from experiments or the literature to construct PBPK models for each drug in rats. These models were integrated to predict the DDIs between saxagliptin, metabolized via CYP3A2, and nicardipine, exhibiting CYP3A inhibitory activity. The rat DDI PBPK model was completed by optimizing parameters using experimental rat plasma concentrations after co-administration of both drugs. Following co-administration in Sprague-Dawley rats, saxagliptin plasma concentration significantly increased, resulting in a 2.60-fold rise in AUC, accurately predicted by the rat PBPK model. Subsequently, the workflow of the rat PBPK model was applied to humans, creating a model capable of predicting DDIs between the two drugs in humans. Simulation from the human PBPK model indicated that nicardipine co-administration in humans resulted in a nearly unchanged AUC of saxagliptin, with an approximate 1.05-fold change, indicating no clinically significant changes and revealing a lack of direct translation of animal interaction results to humans. The animal-to-human PBPK model extrapolation used in this study could enhance the reliability of predicting drug interactions in clinical settings where DDI studies are challenging.
Files in This Item
There are no files associated with this item.
Appears in
Collections
ETC > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Maeng, Han Joo photo

Maeng, Han Joo
Pharmacy (Dept.of Pharmacy)
Read more

Altmetrics

Total Views & Downloads

BROWSE