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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.

<p class="ADMETabstracttext">The purpose of the present study was to harmonize the protocol of equilibrium solubility measurements for poorly water-soluble drugs to lower inter-laboratory variance. The “mandatory” and “recommended” procedures for the shake-flask method were harmonized based on the knowledge and experiences of each company and information from the literature. The solubility of model drugs was measured by the harmonized protocol (HP) and the non-harmonized proprietary protocol of each company (nonHP). Albendazole, griseofulvin, dipyridamole, and glibenclamide were used as model drugs. When using the nonHP, the solubility values showed large inter-laboratory variance. In contrast, inter-laboratory variance was markedly reduced when using the HP.</p>

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