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Evaluating the impact of acid-reducing agents on drug absorption using biorelevant in vitro tools and PBPK modeling -
Domagoj Segregur1, Richard Barker2, James Mann3
1Institute of Pharmaceutical Technology, J. W. Goethe University, 9 Max von Laue St., 60438, Frankfurt am Main, Germany.
Background:
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.
Methods:
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.
Results:
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.
Conclusion:
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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