Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
10.0
5.5
Journals
Pharmaceutics
Special Issues
Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications
share announcement

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: 29 October 2026 | Viewed by 15973

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 250 words) can be sent to the Editorial Office for assessment.

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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

18 pages, 3594 KB  
Article
Physiologically Based Pharmacokinetic Modeling of Digoxin in Adult and Pediatric Patients with Heart Failure
by Yicui Zhang, Yao Liu, Hua He and Kun Hao
Pharmaceutics 2026, 18(1), 112; https://doi.org/10.3390/pharmaceutics18010112 - 15 Jan 2026
Viewed by 1188
Abstract
Background/Objectives: Digoxin is a cardiotonic agent with a narrow therapeutic window and a high risk of toxicity. The current clinical use is based on an empirically FDA-recommended regimen which has wide dosing ranges, introducing the risk of inappropriate dosing and related adverse [...] Read more.
Background/Objectives: Digoxin is a cardiotonic agent with a narrow therapeutic window and a high risk of toxicity. The current clinical use is based on an empirically FDA-recommended regimen which has wide dosing ranges, introducing the risk of inappropriate dosing and related adverse events. This study aims to develop a physiologically based pharmacokinetic (PBPK) model to characterize digoxin pharmacokinetics in adult and pediatric patients with heart failure, and then to evaluate the FDA-recommended regimen. Methods: The PBPK model was initially developed in healthy adults using PK-Sim®. Then, it was translated to adults with heart failure by incorporating disease factors. Next, it was further translated to pediatrics by scaling age-related parameters. Finally, through two-step translations, the model was used to evaluate current dosing regimens to inform safety and effectiveness based on observing predicted trough concentrations at a steady state. Results: This PBPK model has strong predicting ability, where observed concentrations and key PK metrics (Cmax, AUC0-t) were within 0.5–2.0-fold of predictions in healthy adults, adults with heart failure, neonates, and infants. The model prediction work on the evaluation of recommended dosing regimens from the FDA shows that the current regimen may not achieve the lowest boundary of the therapeutic window (0.5–2 ng/mL) in neonates (0–30 days), whereas infants (1–2 months) and children (<18 years) are generally good within it. Conclusions: This PBPK model explained major physiological and pathological contributors to differences in digoxin pharmacokinetics across populations and showed good performance in pediatric extrapolation. It also pointed out the shortage of empirical dosing regimens for such a drug with a narrow therapeutic window. The model may assist in optimizing the pediatric dosing strategies of digoxin, and suggests that current neonatal dosing regimens need refinement. Full article
(This article belongs to the Special Issue Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications)
►▼ Show Figures

Figure 1

16 pages, 1507 KB  
Article
Escitalopram Dose Optimization During Pregnancy: A PBPK Modeling Approach
by Seo-Yeon Choi, Eunsol Yang and Kwang-Hee Shin
Pharmaceutics 2025, 17(10), 1341; https://doi.org/10.3390/pharmaceutics17101341 - 17 Oct 2025
Cited by 1 | Viewed by 2594
Abstract
Background/Objectives: Escitalopram, a first-line antidepressant, is primarily metabolized by CYP2C19. Its pharmacokinetics are altered during pregnancy. This study aims to predict maternal and fetal exposure to escitalopram during pregnancy and to propose safe and effective dosing strategies using physiologically based pharmacokinetic (PBPK) [...] Read more.
Background/Objectives: Escitalopram, a first-line antidepressant, is primarily metabolized by CYP2C19. Its pharmacokinetics are altered during pregnancy. This study aims to predict maternal and fetal exposure to escitalopram during pregnancy and to propose safe and effective dosing strategies using physiologically based pharmacokinetic (PBPK) modeling. Methods: Predictive PBPK models for escitalopram were developed in nonpregnant women, pregnant women, and the fetoplacental unit using the Simcyp® simulator. Additional models incorporating CYP2C19 phenotypes were constructed. Model performance was evaluated using visual predictive checks and by comparing predicted-to-observed ratios for the maximum plasma concentration (Cmax) and the area under the curve (AUC), within an acceptance criterion of 0.7–1.3. Results: Escitalopram concentrations at doses of 10–20 mg declined with advancing gestation. The cord-to-maternal concentration ratio was approximately 0.70 for both doses. Simulations of maternal and fetoplacental PBPK models across CYP2C19 phenotypes showed that most observed concentrations fell within the 95% confidence intervals of the predictions. Based on the therapeutic range attained and the maintenance of steady-state exposure, a once-daily 20 mg escitalopram dose was predicted to be appropriate during pregnancy. Conclusions: These findings suggest that a once-daily 20 mg dose appears optimal during pregnancy, highlighting the need to consider the gestational stage and CYP2C19 phenotype in dose optimization. Full article
(This article belongs to the Special Issue Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications)
►▼ Show Figures

Figure 1

16 pages, 3320 KB  
Article
A Comprehensive Physiologically Based Pharmacokinetic Framework of Ofloxacin: Predicting Disposition in Renal Impairment
by Ammara Zamir, Muhammad Fawad Rasool, Iltaf Hussain, Sary Alsanea, Samiah A. Alhabardi and Faleh Alqahtani
Pharmaceutics 2025, 17(9), 1224; https://doi.org/10.3390/pharmaceutics17091224 - 20 Sep 2025
Viewed by 3146
Abstract
Background: In the last several years, “physiologically based pharmacokinetic (PBPK) modeling” has gathered significant emphasis in the modeling of drug absorption, disposition, and metabolism. This research study aims to elaborate the plasma/serum concentration–time profiles and pharmacokinetics (PK) of ofloxacin by establishing a [...] Read more.
Background: In the last several years, “physiologically based pharmacokinetic (PBPK) modeling” has gathered significant emphasis in the modeling of drug absorption, disposition, and metabolism. This research study aims to elaborate the plasma/serum concentration–time profiles and pharmacokinetics (PK) of ofloxacin by establishing a PBPK model in healthy subjects and those suffering from renal impairment (RI). Methods: A comprehensive literature analysis was conducted to screen out all the systemic PK profiles and parameters specific to ofloxacin, followed by their implementation in PK-Sim® version 12 software. This model-driven approach begins by developing the model in healthy populations using both intravenous (IV) and per-oral (PO) routes and then extrapolating it to the diseased population. The model evaluation was then strengthened for different PK variables such as the maximal plasma/serum concentration (Cmax), the area under the curve from 0 to t (AUC0–t), and plasma/serum clearance (CL) by employing various metrics such as predicted/observed ratios (Rpre/obs), visual predictive checks, the average fold error (AFE), root mean squared error (RMSE), and mean absolute error (MAE). Results: The AFE, RSME, and MAE for Cmax in RI were 1.10, 0.22, and 0.16, respectively, which fell within the acceptable simulated error range. Furthermore, dosage adjustments for individuals with mild, moderate, and severe RI were presented by box-whisker plots to compare their systemic exposure with that of the healthy population. Conclusions: These model predictions have confirmed the PK variations in ofloxacin, which may assist the clinicians in optimizing dosage schedules in healthy and various categories of RI populations. Full article
(This article belongs to the Special Issue Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications)
►▼ Show Figures

Figure 1

15 pages, 882 KB  
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 1437
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)
►▼ Show Figures

Figure 1

20 pages, 3849 KB  
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
Cited by 7 | Viewed by 3679
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)
►▼ Show Figures

Graphical abstract

Review

Jump to: Research

29 pages, 980 KB  
Review
Ketamine in Diabetes Care: Metabolic Insights and Clinical Applications
by Shiryn D. Sukhram, Majandra Sanchez, Ayotunde Anidugbe, Bora Kupa, Vincent P. Edwards, Muhammad Zia and Grozdena Yilmaz
Pharmaceutics 2026, 18(1), 81; https://doi.org/10.3390/pharmaceutics18010081 - 8 Jan 2026
Viewed by 1774
Abstract
Background: Depression and diabetic neuropathy (DN) commonly complicate diabetes and impair glycemic control and quality of life. Ketamine and its S-enantiomer, esketamine, provide rapid antidepressant and analgesic effects, yet diabetes-related pathophysiology and co-therapies may modify exposure, response, and safety. Methods: We conducted a [...] Read more.
Background: Depression and diabetic neuropathy (DN) commonly complicate diabetes and impair glycemic control and quality of life. Ketamine and its S-enantiomer, esketamine, provide rapid antidepressant and analgesic effects, yet diabetes-related pathophysiology and co-therapies may modify exposure, response, and safety. Methods: We conducted a scoping review following PRISMA-ScR. MEDLINE/PubMed, CINAHL, and APA PsycInfo were searched (January 2020–31 May 2025). Eligible human and animal studies evaluated ketamine, esketamine, or norketamine in the context of diabetes (type 1 [T1DM], type 2 [T2DM], gestational [GDM]), or DN, and reported psychiatric, analgesic, metabolic, or mechanistic outcomes. Two reviewers independently screened and charted data; no formal risk-of-bias assessment was performed. Results: Eleven studies met inclusion criteria: four human case reports/series (three T1DM, one T2DM), one randomized trial in GDM, two narrative reviews of topical ketamine for DN, and four preclinical rodent studies using streptozotocin- or diet-induced diabetes models. Short-term improvements were reported for treatment-resistant depression and neuropathic pain, including opioid-sparing postoperative analgesia in GDM. Glycemic effects varied across settings, with both hyperglycemia and hypoglycemia reported. Mechanistic and clinical drug–drug and drug-disease interactions (particularly involving metformin, GLP-1 receptor agonists, SGLT2 inhibitors, and CYP3A4/CYP2B6 modulators) remain insufficiently studied. We outline a forward-looking population pharmacokinetic (popPK) and pharmacokinetic-pharmacodynamic (PK-PD) research agenda, including priority covariates (eGFR, hepatic function, inflammatory status, HbA1c, genotype, co-medications) and sparse-sampling windows for future model-informed precision dosing. Conclusions: Current evidence supports cautious, selective use of ketamine for refractory depression and DN within multidisciplinary diabetes care. Purpose-built popPK/PK-PD studies in both human and preclinical diabetic models cohorts are needed to quantify variability, define drug–disease–drug interactions and glycemic risk, and inform individualized dosing strategies. Full article
(This article belongs to the Special Issue Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling and Applications)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop