基于生理学的药代动力学模型
药代动力学
潘生丁
药理学
化学
药品
体内
药物相互作用
溶解试验
体外
医学
生物化学
内科学
生物制药分类系统
生物
生物技术
作者
Domagoj Šegregur,Richard A. Barker,James Mann,Andrea Moir,Εva Karlsson,David B. Turner,Sumit Arora,Jennifer B. Dressman
标识
DOI:10.1016/j.ejps.2021.105750
摘要
In vitro and in silico methods have become an essential tool in assessing metabolic drug-drug interactions (DDI) and avoiding reduced efficacy and increased side-effects. Another important type of DDI is the impact of acid-reducing agent (ARA) co-therapy on drug pharmacokinetics due to changes in gastric pH, especially for poorly soluble weakly basic drugs. One-stage, two-stage and transfer dissolution experiments with dipyridamole tablets using novel biorelevant media representing the ARA effect were conducted and the results were coupled with a PBPK model. Clinical pharmacokinetic data were compared with the simulations from the PBPK model and with output from TIM-1 experiments, an evolved in vitro system which aims to simulate the physiology in the upper GI tract. Two-stage and transfer experiments confirmed that these in vitro set-ups tend to overestimate the extent of dipyridamole precipitation occurring in the intestines in vivo. Consequently, data from one-stage dissolution testing under elevated gastric pH conditions were used as an input for PBPK modeling of the ARA/dipyridamole interaction. Using media representing the ARA effect in conjunction with the PBPK model, the ARA effect observed in vivo was successfully bracketed. As an alternative, the TIM-1 system with gastric pH values adjusted to simulate ARA pre-treatment can be used to forecast the ARA effect on dipyridamole pharmacokinetics. Drug-drug interactions of dipyridamole with ARA were simulated well with a combination of dissolution experiments using biorelevant media representing the gastric environment after an ARA treatment together with the PBPK model. Adjustment of the TIM-1 model to reflect ARA-related changes in gastric pH was also successful in forecasting the interaction. Further testing of both approaches for predicting ARA-related DDIs using a wider range of drugs should be conducted to verify their utility for this purpose.
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