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Pharmaceutics
Special Issues
Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications
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Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications

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

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1988

Special Issue Editor

Dr. Dong‑Gyun Han

E-Mail Website
Guest Editor
College of Pharmacy and Research Institute for Drug Development, Pusan National University, Geumjeong-gu, Busan 46241, Republic of Korea
Interests: bioanalysis; biopharmaceutics; pharmacokinetics; DMPK; PBPK/PD modeling

Special Issue Information

Dear Colleagues,

Physiologically based pharmacokinetic (PBPK) modeling is a mathematical approach utilized to predict the absorption, distribution, metabolism, and excretion (ADME) of both synthetic and naturally occurring chemical substances in humans and various animal species. The utility of physiologically based pharmacokinetic (PBPK) models has been substantiated across multiple academic and industrial domains, encompassing stages of drug development, clinical simulations, and regulatory science.

Since its inception and initial phases, this model has exhibited considerable utility in the field of drug development. During the early stages, in vitro data and physicochemical properties can be employed to generate pharmacokinetic profiles, which are subsequently validated through in vivo studies. In the later phases of clinical development, simulations may be utilized to elucidate drug performance within specific populations.

In this Special Issue, original research articles and reviews are welcome to be submitted. Research areas may include, but are not limited to, the following: PBPK modeling and simulation, including the pharmacokinetics of populations, drug–drug interactions, the integration of tissue concentration, PBPK-based precision dosing, PBPK/PD modeling, PBPK-based quantitative systems pharmacology (QSP) approaches, etc.

Dr. Dong‑Gyun Han
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceutics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • physiologically based pharmacokinetic (PBPK) modeling
  • IVIVE
  • pharmacokinetics
  • ADME
  • modeling and simulation
  • PK/PD
  • biopharmaceutics
  • quantitative systems pharmacology

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Published Papers (2 papers)

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15 pages, 882 KiB  
Article
Physiologically Based Pharmacokinetic Simulation of Tofacitinib in Humans Using Extrapolation from Single-Species Renal Failure Model
by Sung Hun Bae, So Yeon Park, Hyeon Gyeom Choi and So Hee Kim
Pharmaceutics 2025, 17(7), 914; https://doi.org/10.3390/pharmaceutics17070914 - 15 Jul 2025
Viewed by 199
Abstract
Background/Objectives: Tofacitinib is a Janus kinase 1 and 3 inhibitor that was developed to treat rheumatoid arthritis. Accordingly, this study aimed to predict plasma tofacitinib concentrations and pharmacokinetic parameters in patients with renal failure through physiologically based pharmacokinetic (PBPK) simulations. Methods: PK-Sim [...] Read more.
Background/Objectives: Tofacitinib is a Janus kinase 1 and 3 inhibitor that was developed to treat rheumatoid arthritis. Accordingly, this study aimed to predict plasma tofacitinib concentrations and pharmacokinetic parameters in patients with renal failure through physiologically based pharmacokinetic (PBPK) simulations. Methods: PK-Sim and Simcyp simulators were used, as well as conventional Dedrick plot analysis, employing a single animal extrapolation method. The predictions were compared with previously published data. Results: PBPK simulations of tofacitinib in patients with renal failure closely matched the observed plasma concentration profiles and pharmacokinetic results, including the area under the plasma concentration–time curve (AUC), maximum plasma concentration (Cmax), and time to reach Cmax (Tmax). The ratios of the simulated to observed plasma concentrations and pharmacokinetic parameters for tofacitinib were within a 0.5–2.0-fold error range. Although the results from the Dedrick plot were reasonably good, they were less accurate than those of the PBPK simulations. This was because the Dedrick plot relied solely on preclinical plasma concentration data without incorporating drug physicochemical properties, in vitro data, or physiological and pathophysiological variables. Conclusions: The findings suggest that PBPK simulations using single-species extrapolation effectively provide preliminary estimates of plasma tofacitinib concentration profiles and pharmacokinetic parameters in humans under specific conditions, including renal failure. Furthermore, the results provide a foundation for adjusting tofacitinib dosage and dosing schedules to maintain effective plasma concentrations by considering the pathophysiological characteristics of patients according to their specific diseases. Full article
(This article belongs to the Special Issue Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications)
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20 pages, 3849 KiB  
Article
Leveraging Omeprazole PBPK/PD Modeling to Inform Drug–Drug Interactions and Specific Recommendations for Pediatric Labeling
by Amira Soliman, Leyanis Rodriguez-Vera, Ana Alarcia-Lacalle, Leandro F. Pippa, Saima Subhani, Viera Lukacova, Jorge Duconge, Natalia V. de Moraes and Valvanera Vozmediano
Pharmaceutics 2025, 17(3), 373; https://doi.org/10.3390/pharmaceutics17030373 - 14 Mar 2025
Viewed by 1380
Abstract
Background/Objectives: Omeprazole is widely used for managing gastrointestinal disorders like GERD, ulcers, and H. pylori infections. However, its use in pediatrics presents challenges due to drug interactions (DDIs), metabolic variability, and safety concerns. Omeprazole’s pharmacokinetics (PK), primarily influenced by CYP2C19 metabolism, is affected [...] Read more.
Background/Objectives: Omeprazole is widely used for managing gastrointestinal disorders like GERD, ulcers, and H. pylori infections. However, its use in pediatrics presents challenges due to drug interactions (DDIs), metabolic variability, and safety concerns. Omeprazole’s pharmacokinetics (PK), primarily influenced by CYP2C19 metabolism, is affected by ontogenetic changes in enzyme expression, complicating dosing in children. Methods: This study aimed to develop and validate a physiologically based pharmacokinetic (PBPK) model for omeprazole and its metabolites to predict age-related variations in metabolism and response. Results: The PBPK model successfully predicted exposure to parent and metabolites in adults and pediatrics, incorporating competitive and mechanism-based inhibition of CYP2C19 and CYP3A4 by omeprazole and its metabolites. By accounting for age-dependent metabolic pathways, the model enabled priori predictions of omeprazole exposure in different age groups. Linking PK to the pharmacodynamics (PD) model, we described the impact of age-related physiological changes on intragastric pH, the primary outcome for proton pump inhibitors efficacy. Conclusions: The PBPK-PD model allowed for the virtual testing of dosing scenarios, providing an alternative to clinical studies in pediatrics where traditional DDI studies are challenging. This approach offers valuable insights for accurate dosing recommendations in pediatrics, accounting for age-dependent variability in metabolism, and underscores the potential of PBPK modeling in guiding pediatric drug development. Full article
(This article belongs to the Special Issue Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications)
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