Recent Advances in Physiologically Based Biopharmaceutics Modeling

A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmacokinetics and Pharmacodynamics".

Deadline for manuscript submissions: 25 June 2026 | Viewed by 1788

Special Issue Editor


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Guest Editor
Faculty of Pharmaceutical Sciences, Department of Medicinal and Life Sciences, Tokyo University of Science, Tokyo, Japan
Interests: mathematical modeling and data science in pharmaceutics; medical pharmacy; drug dosage form

Special Issue Information

Dear Colleagues,

The quantitative prediction of the pharmacokinetics, especially the absorption kinetics, of orally administered drugs has been investigated by many researchers. However, oral absorption is an amalgamation of many disciplines, including pharmacokinetics, formulation science, the physical chemistry of drugs, and physiology in the gastrointestinal tract of humans; research that achieves accurate prediction is still in its infancy. Needless to say, physiologically based biopharmaceutics modeling (PBBM) has attracted attention in the field of pharmaceutics in recent years as an approach to solving this problem. It is important to understand the benefits and current challenges of PBBM by having many case studies presented in a journal.

This Special Issue focuses on PBBM research in drug product development and clinical development. This Special Issue will include modeling and simulation approaches to forecast or evaluate the relative BA and BE between drug formulations, modeling approaches to predict the effects of food ingestion and concomitant medications on drug absorption, as well as studies discussing the relationship between drug formulation quality (such as API particle size and dissolution test specifications) and PBBM. It is hoped that this Special Issue will lead to the appropriate scientific use of PBBM and patient-centered drug development and drug approval review.

Dr. Atsushi Kambayashi
Guest Editor

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Keywords

  • oral drug absorption
  • bioavailability
  • bioequivalence
  • modeling and simulation
  • physiologically based biopharmaceutics modeling

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Published Papers (1 paper)

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Research

22 pages, 2896 KB  
Article
Integrating In Vitro BE Checker with In Silico Physiologically Based Biopharmaceutics Modeling to Predict the Pharmacokinetic Profiles of Oral Drug Products
by Takuto Niino, Takato Masada, Toshihide Takagi, Makoto Kataoka, Hiroyuki Yoshida, Shinji Yamashita and Atsushi Kambayashi
Pharmaceutics 2025, 17(9), 1222; https://doi.org/10.3390/pharmaceutics17091222 - 20 Sep 2025
Viewed by 1297
Abstract
Objective: The objective of this study was to develop a Physiologically Based Biopharmaceutics Modeling (PBBM) framework that can predict PK profiles in humans based on data generated from the BE Checker. Methods: Metoprolol and dipyridamole were selected as model drugs. A [...] Read more.
Objective: The objective of this study was to develop a Physiologically Based Biopharmaceutics Modeling (PBBM) framework that can predict PK profiles in humans based on data generated from the BE Checker. Methods: Metoprolol and dipyridamole were selected as model drugs. A mathematical model was developed to describe drug dissolution, membrane permeation, and dynamic changes in pH and fluid volume within the BE Checker system. Using data generated under various experimental conditions, dissolution rate constants were estimated. For dipyridamole, the precipitation rate constant was also estimated, assuming simultaneous dissolution and precipitation processes. The estimated parameters were subsequently incorporated into the human PBBM to simulate PK profiles. Finally, the predictive accuracy of PK parameters such as Cmax and AUC was assessed. Results: For metoprolol, the PK profiles using the paddle revolution rates of 100 and 200 rpm closely matched the observed human data, particularly for Cmax and AUC, a key indicator of BE. In the case of dipyridamole, accurate predictions of the mean human PK profile were achieved when using BE Checker data obtained under high paddle speed (200 rpm) and longer pre-FaSSIF infusion times (20–30 min). Conversely, simulations based on lower paddle speed (50 rpm) and shorter pre-FaSSIF infusion time (10 min) underestimated plasma concentrations in humans. Conclusions: These findings suggest that the combination of BE Checker data acquired under high agitation conditions and the in silico mathematical model developed in this study enables accurate prediction of average human PK profiles. Full article
(This article belongs to the Special Issue Recent Advances in Physiologically Based Biopharmaceutics Modeling)
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