Dissolution Challenges Associated with the Surface pH of Drug Particles: Integration into Mechanistic Oral Absorption Modeling

2022 ◽  
Vol 24 (1) ◽  
Author(s):  
Bart Hens ◽  
Nidhi Seegobin ◽  
Marival Bermejo ◽  
Yasuhiro Tsume ◽  
Nicola Clear ◽  
...  
Keyword(s):  
Oral Absorption ◽  
Surface Ph ◽  
Absorption Modeling

Maximizing the Impact of Physiologically Based Oral Absorption Modeling and Simulation

2017 ◽  
Vol 106 (3) ◽  
pp. 734-737 ◽  
Author(s):  
John I. Chung ◽  
Ron C. Kelly ◽  
Jan Wahlstrom ◽  
Benjamin Wu ◽  
Tian Wu ◽  
...  
Keyword(s):  
Modeling And Simulation ◽  
Oral Absorption ◽  
Physiologically Based ◽  
Absorption Modeling ◽  
The Impact

scholarly journals Bottom-Up Physiologically Based Oral Absorption Modeling of Free Weak Base Drugs

Pharmaceutics ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 844
Author(s):  
Naoya Matsumura ◽  
Asami Ono ◽  
Yoshiyuki Akiyama ◽  
Takuya Fujita ◽  
Kiyohiko Sugano
Keyword(s):  
Oral Absorption ◽  
Particle Growth ◽  
Pharmacokinetic Data ◽  
Weak Base ◽  
Bottom Up ◽  
Physiologically Based ◽  
Absorption Modeling ◽  
Modeling Strategy ◽  
Intrinsic Solubility

In this study, we systematically evaluated “bottom-up” physiologically based oral absorption modeling, focusing on free weak base drugs. The gastrointestinal unified theoretical framework (the GUT framework) was employed as a simple and transparent model. The oral absorption of poorly soluble free weak base drugs is affected by gastric pH. Alternation of bulk and solid surface pH by dissolving drug substances was considered in the model. Simple physicochemical properties such as pKa, the intrinsic solubility, and the bile micelle partition coefficient were used as input parameters. The fraction of a dose absorbed (Fa) in vivo was obtained by reanalyzing the pharmacokinetic data in the literature (15 drugs, a total of 85 Fa data). The AUC ratio with/without a gastric acid-reducing agent (AUCr) was collected from the literature (22 data). When gastric dissolution was neglected, Fa was underestimated (absolute average fold error (AAFE) = 1.85, average fold error (AFE) = 0.64). By considering gastric dissolution, predictability was improved (AAFE = 1.40, AFE = 1.04). AUCr was also appropriately predicted (AAFE = 1.54, AFE = 1.04). The Fa values of several drugs were slightly overestimated (less than 1.7-fold), probably due to neglecting particle growth in the small intestine. This modeling strategy will be of great importance for drug discovery and development.

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