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J Pharm Sci. 2019 Jan;108(1):584-591. doi: 10.1016/j.xphs.2018.11.008. Epub 2018 Nov 10.

Predicting the Changes in Oral Absorption of Weak Base Drugs Under Elevated Gastric pH Using an In Vitro-In Silico-In Vivo Approach: Case Examples-Dipyridamole, Prasugrel, and Nelfinavir.

Author information

1
Pharmaceutical Research and Technology Labs, Astellas Pharma Inc, 180 Ozumi, Yaizu, Shizuoka 425-0072, Japan; Institute of Pharmaceutical Technology, Goethe University Frankfurt am Main, Max-von-Laue Straße 9, D-60438 Frankfurt am Main, Germany. Electronic address: atsushi.kambayashi@astellas.com.
2
Institute of Pharmaceutical Technology, Goethe University Frankfurt am Main, Max-von-Laue Straße 9, D-60438 Frankfurt am Main, Germany.

Abstract

The aim of the current research was to develop an in silico oral absorption model coupled with an in vitro dissolution/precipitation testing to predict gastric pH-dependent drug-drug interactions for weakly basic drugs. The effects of elevated gastric pH on the plasma profiles of dipyridamole, prasugrel, and nelfinavir were simulated and compared with pharmacokinetic data reported in humans with or without use of proton pump inhibitors or histamine H2 receptor antagonists. The in vitro dissolution and precipitation data for the weakly basic drugs in biorelevant media were obtained using paddle apparatus. An in silico prediction model based on the STELLA software was designed and simulations were conducted to predict the oral pharmacokinetic profiles of the 3 drugs under both usual (low) and elevated gastric pH conditions. The changes in oral absorption of dipyridamole and prasugrel in subjects with elevated gastric pH compared with those with low stomach pH were predicted well using the in vitro-in silico-in vivo approach. The proposed approach could become a powerful tool in the formulation development of poorly soluble weak base drugs.

KEYWORDS:

dissolution; drug-drug interaction; in silico modeling; oral absorption; pharmacokinetics; poorly water-soluble drugs; precipitation; simulation

PMID:
30423339
DOI:
10.1016/j.xphs.2018.11.008

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