Open AccessApplication of Physiologically‐Based Pharmacokinetic Modeling to Predict Gastric pH‐Dependent Drug–Drug Interactions for Weak Base Drugs
Author(s) -
Dong Zhongqi,
Li Jia,
Wu Fang,
Zhao Ping,
Lee SueChih,
Zhang Lillian,
Seo Paul,
Zhang Lei
Publication year - 2020
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12541
Subject(s) - physiologically based pharmacokinetic modelling , pharmacology , pharmacokinetics , drug , tapentadol , saxagliptin , chemistry , darunavir , erlotinib , drug interaction , drug drug interaction , medicine , opioid , receptor , biochemistry , human immunodeficiency virus (hiv) , metformin , family medicine , sitagliptin , insulin , antiretroviral therapy , viral load , epidermal growth factor receptor
Weak‐base drugs are susceptible to drug–drug interactions (DDIs) when coadministered with gastric acid–reducing agents (ARAs). We developed PBPK models to evaluate the potential of such pH‐dependent DDIs for four weak‐base drugs, i.e., tapentadol, darunavir, erlotinib, and saxagliptin. The physiologically‐based pharmacokinetic (PBPK) models of these drugs were first optimized using pharmacokinetic (PK) data following oral administration without ARAs, which were then verified with data from additional PK studies in the presence and absence of food. The models were subsequently used to predict the extent of DDIs with ARA coadministration. Sensitivity analysis was conducted to explore the impact of gastric pH on quantitative prediction of drug exposure in the presence of ARA. The results suggested that the PBPK models developed could adequately describe the lack of the effect of ARA on the PK of tapentadol, darunavir, and saxagliptin and could qualitatively predict the effect of ARA in reducing the absorption of erlotinib. Further studies involving more drugs with positive pH‐dependent DDIs are needed to confirm the findings and broaden our knowledge base to further improve the utilization of PBPK modeling to evaluate pH‐dependent DDI potential.