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Development of Physiologically Based Pharmacokinetic (PBPK) Modeling

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

Deadline for manuscript submissions: 30 September 2025 | Viewed by 16924

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Special Issue Editors

Dr. Bárbara Sánchez-Dengra

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Guest Editor

Engineering: Pharmacokinetics and Pharmaceutical Technology Area, Miguel Hernandez University, San Juan de Alicante, 03550 Alicante, Spain
Interests: blood-brain barrier; bioequivalence; in vivo predictive dissolution; in vitro-in vivo correlation; PBPK; pharmacokinetics
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Prof. Dr. Isabel Gonzalez-Alvarez

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Guest Editor

Engineering: Pharmacokinetics and Pharmaceutical Technology Area, Miguel Hernandez University, San Juan de Alicante, 03550 Alicante, Spain
Interests: PBPK; biowaivers; pharmacokinetics; dissolution; absorption; drug solubility
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue: “Development of Physiologically Based Pharmacokinetic (PBPK) Modeling”. PBPK modeling is a mathematical tool which is able to describe the drug concentration in an organism using compartments that correspond to the different tissues and taking into consideration the physiology of this organism to parameterize the model.

This type of model has become useful in drug development since its discovery and early phases, when in vitro data and physicochemical properties could be used to obtain plasma profiles, which would be, later on, validated in vivo, until the clinical development phases, in which simulations can be used to describe drug performance in special populations.

This Special Issue aims to compile the latest research carried out with this tool, in both preclinical and clinical development stages. Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: early drug development, risk assessment and toxicity assessment, absorption/formulation modeling, and the prediction of drug–disease interactions and drug–drug interactions.

We look forward to receiving your contributions.

Dr. Bárbara Sánchez-Dengra
Prof. Dr. Isabel Gonzalez-Alvarez
Guest Editors

Manuscript Submission Information

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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.

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Keywords

physiologically based pharmacokinetic modeling (PBPK)
modeling and simulations (M&S)
pharmacokinetics
ADME
pharmacometrics

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Published Papers (8 papers)

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Research

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42 pages, 15778 KB

Open AccessArticle

A Mechanistic Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling Approach Informed by In Vitro and Clinical Studies for Topical Administration of Adapalene Gels

by Namrata S. Matharoo, Harsha T. Garimella, Thu M. Truong, Saiaditya Badeti, Joyce X. Cui, Sesha Rajeswari Talluri, Amitkumar Virani, Babar K. Rao and Bozena Michniak-Kohn

Pharmaceutics 2025, 17(9), 1108; https://doi.org/10.3390/pharmaceutics17091108 - 25 Aug 2025

Viewed by 742

Abstract

Background/Objectives: Adapalene is a synthetic retinoid used as a treatment for acne vulgaris. In this study, we attempted to evaluate the dermal pharmacokinetics of adapalene utilizing experimental and in silico tools. Methods: We utilized three over the counter (OTC) adapalene gels to evaluate local dermal pharmacokinetics. A data-driven, robust, mechanistic dermal physiologically based pharmacokinetic (PBPK) model was developed by integrating the physicochemical properties of adapalene, the formulation attributes of the gels, and the biophysical aspects of dermal absorption. The dermal PBPK model was validated against experimental data using in vitro release studies and in vitro permeation studies with human cadaver skin. A clinical study was performed to evaluate the effects of adapalene from the three gel formulations. The impact of adapalene delivery from three gels on the stratum corneum (SC) thickness, pilosebaceous unit area, keratinocyte number, and epidermal thickness was captured using a non-invasive technique, line-field confocal optical coherence tomography (LC–OCT). These responses were evaluated using an Emax model. Results: The dermal PBPK model has successfully predicted adapalene penetration profiles across different gel formulations. The model accuracy, in predicting drug release and permeation characteristics, was confirmed using the experimental data. Clinical evaluation revealed formulation-dependent differences in adapalene’s effects on measured skin parameters, with distinct pharmacodynamic profiles observed for each gel formulation. Conclusions: The overall study gave us a detailed insight into potential effects of formulation on the dermal pharmacokinetics and pharmacodynamics of adapalene using three marketed gels. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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16 pages, 1525 KB

Open AccessArticle

Physiologically Based Pharmacokinetic Modeling to Assess Perpetrator and Victim Cytochrome P450 2C Induction Risk

by Marina Slavsky, Aniruddha Sunil Karve and Niresh Hariparsad

Pharmaceutics 2025, 17(8), 1085; https://doi.org/10.3390/pharmaceutics17081085 - 21 Aug 2025

Viewed by 644

Abstract

Background: Accurate assessment of CYP2C induction-mediated drug–drug interactions (DDIs) remains a challenge, despite the importance of CYP2C enzymes in drug metabolism. Limitations in available models and scarce clinical induction data have hampered quantitative preclinical DDI risk evaluation. Methods: In this study, the authors utilized an all-human hepatocyte triculture system to capture CYP2C induction using the perpetrators rifampicin, efavirenz, carbamazepine, and apalutamide. In vitro induction parameters were quantified by measuring changes in both mRNA and enzyme activities for CYP2C8, CYP2C9, and CYP2C19. These induction parameters, along with CYP-specific intrinsic clearance (CL_int) for the victim compounds, were incorporated into a physiologically based pharmacokinetic (PBPK) model, and pharmacokinetics (PK) of known CYP2C substrates were predicted with and without co-administration of perpetrator compounds using clinical dosing regimens. The results were quantitatively compared with the currently utilized mechanistic static modeling (MSM) approach and the reported clinical DDI outcomes. Results: By incorporating the measured f_m of CYP2C substrates into PBPK modeling, we observed a lower propensity to over- or underpredict the exposure of these substrates as victims of CYP2C induction-based DDIs when co-administered with known perpetrators, which resulted in an excellent correlation to observed clinical outcomes. The MSM approach predicted the CYP3A4 induction-based DDI risk accurately but could not capture CYP2C induction with similar precision. Conclusions: Overall, this is the first study that demonstrates the utility of PBPK modeling as a complementary approach to MSM for CYP2C induction-based DDI risk assessment. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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25 pages, 2704 KB

Open AccessArticle

A Parent–Metabolite Middle-Out PBPK Model for Genistein and Its Glucuronide Metabolite in Rats: Integrating Liver and Enteric Metabolism with Hepatobiliary and Enteroluminal Transport to Assess Glucuronide Recycling

by Bhargavi Srija Ramisetty, Rashim Singh, Ming Hu and Michael Zhuo Wang

Pharmaceutics 2025, 17(7), 814; https://doi.org/10.3390/pharmaceutics17070814 - 23 Jun 2025

Viewed by 685

Abstract

Background: Glucuronide recycling in the gut and liver profoundly affects the systemic and/or local exposure of drugs and their glucuronide metabolites, impacting both clinical efficacy and toxicity. This recycling also alters drug exposure in the colon, making it critical to establish local concentration for drugs targeting colon (e.g., drugs for colon cancer and inflammatory bowel disease). Methods: In this study, a parent–metabolite middle-out physiologically based pharmacokinetic (PBPK) model was built for genistein and its glucuronide metabolite to estimate the systemic and local exposure of the glucuronide and its corresponding aglycone in rats by incorporating UDP-glucuronosyltransferase (UGT)-mediated metabolism and transporter-dependent glucuronide disposition in the liver and intestine, as well as gut microbial-mediated deglucuronidation that enables the recycling of the parent compound. Results: This parent–metabolite middle-out rat PBPK model utilized in vitro-to-in vivo extrapolated (IVIVE) metabolic and transporter clearance values based on in vitro kinetic parameters from surrogate species, the rat tissue abundance of relevant proteins, and saturable Michaelis–Menten mechanisms. Inter-system extrapolation factors (ISEFs) were used to account for transporter protein abundance differences between in vitro systems and tissues and between rats and surrogate species. Model performance was evaluated at multiple dose levels for genistein and its glucuronide. Model sensitivity analyses demonstrated the impact of key parameters on the plasma concentrations and local exposure of genistein and its glucuronide. Our model was applied to simulate the quantitative impact of glucuronide recycling on the pharmacokinetic profiles in both plasma and colonocytes. Conclusions: Our study underlines the importance of glucuronide recycling in determining local drug concentrations in the intestine and provides a preliminary modeling tool to assess the influence of transporter-mediated drug–drug interactions on glucuronide recycling and local drug exposure, which are often misrepresented by systemic plasma concentrations. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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18 pages, 4761 KB

Open AccessArticle

Whole-Body Physiologically Based Pharmacokinetic Modeling Framework for Tissue Target Engagement of CD3 Bispecific Antibodies

by Monica E. Susilo, Stephan Schaller, Luis David Jiménez-Franco, Alexander Kulesza, Wilhelmus E. A. de Witte, Shang-Chiung Chen, C. Andrew Boswell, Danielle Mandikian and Chi-Chung Li

Pharmaceutics 2025, 17(4), 500; https://doi.org/10.3390/pharmaceutics17040500 - 9 Apr 2025

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Abstract

Background: T-cell-engaging bispecific (TCB) antibodies represent a promising therapy that utilizes T-cells to eliminate cancer cells independently of the major histocompatibility complex. Despite their success in hematologic cancers, challenges such as cytokine release syndrome (CRS), off-tumor toxicity, and resistance limit their efficacy in solid tumors. Optimizing biodistribution is key to overcoming these challenges. Methods: A physiologically based pharmacokinetic (PBPK) model was developed that incorporates T-cell transmigration, retention, receptor binding, receptor turnover, and cellular engagement. Preclinical biodistribution data were modeled using two TCB formats: one lacking tumor target binding and another with target arm binding, each with varying CD3 affinities in a transgenic tumor-bearing mouse model. Results: The PBPK model successfully described the distribution of activated T-cells and various TCB formats. It accurately predicted preclinical biodistribution patterns, demonstrating that higher CD3 affinity leads to faster clearance from the blood and increased accumulation in T-cell-rich organs, often reducing tumor exposure. Simulations of HER2-CD3 TCB doses (0.1 µg to 100 mg) revealed monotonic increases in synapse AUC within the tumor. A bell-shaped dose-Cmax relationship for synapse formation was observed, and Tmax was delayed at higher doses. Blood PK was a reasonable surrogate for tumor synapse at low doses but less predictive at higher doses. Conclusions: We developed a whole-body PBPK model to simulate the biodistribution of T-cells and TCB molecules. The insights from this model provide a comprehensive understanding of the factors affecting PK, synapse formation, and TCB activity, aiding in dose optimization and the design of effective therapeutic strategies. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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17 pages, 4537 KB

Open AccessArticle

Development and Application of Physiologically-Based Pharmacokinetic Model to Predict Systemic and Organ Exposure of Colorectal Cancer Drugs

by Sara Peribañez-Dominguez, Zinnia Parra-Guillen and Iñaki F. Troconiz

Pharmaceutics 2025, 17(1), 57; https://doi.org/10.3390/pharmaceutics17010057 - 3 Jan 2025

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Abstract

Background/Objectives: Colorectal cancer (CRC) holds the third and second position among cancers affecting men and women, respectively. Frequently, the first-line treatment for metastatic CRC consists of the intravenous administration of 5-fluorouracil and leucovorin in combination with oxaliplatin or irinotecan. Physiologically-based pharmacokinetic models (PBPK) aim to mechanistically incorporate body physiology and drug physicochemical attributes, enabling the description of both systemic and organ drug exposure based on the treatment specificities. This bottom-up approach represents an opportunity to personalize treatment and minimize the therapeutic risk/benefit ratio through the understanding of drug distribution within colorectal tissue. This project has the goal of characterizing the systemic and tissue exposure of four anti-cancer drugs in humans using a PBPK platform fed with data from the literature. Methods: A literature search was performed to collect clinical data on systemic concentration versus time profiles. Physicochemical features were obtained from the literature, as well as parameters associated with distribution, metabolism, and excretion. The PBPK models were built using PK-Sim^®. Results: The data from 51 clinical studies were extracted and combined in one single dataset. The PBPK models successfully described the exposure vs. time profiles with respect to both, with both the typical tendency and dispersion shown by the data. The percentage of observations falling within the two-fold error bounds ranged between 94 and 100%. The colon/plasma AUC_inf ratios were similar for 5-FU, oxaliplatin, and leucovorin, but it was significantly higher for irinotecan. Conclusions: The PBPK models support tailored treatment approaches by linking in vitro studies to organ exposure. These models serve as the initial step towards incorporating a dedicated tumor compartment, which will further account for the variability in tumor microenvironment characteristics to improve therapeutic strategies. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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26 pages, 1294 KB

Open AccessArticle

PBPK Modeling of Lamotrigine and Efavirenz during Pregnancy: Implications for Personalized Dosing and Drug-Drug Interaction Management

by Bárbara Costa, Maria João Gouveia and Nuno Vale

Pharmaceutics 2024, 16(9), 1163; https://doi.org/10.3390/pharmaceutics16091163 - 3 Sep 2024

Cited by 3 | Viewed by 2323

Abstract

This study aimed to model the pharmacokinetics of lamotrigine (LTG) and efavirenz (EFV) in pregnant women using physiologically based pharmacokinetic (PBPK) and pregnancy-specific PBPK (p-PBPK) models. For lamotrigine, the adult PBPK model demonstrated accurate predictions for pharmacokinetic parameters. Predictions for the area under the curve (AUC) and peak plasma concentration (Cmax) generally agreed well with observed values. During pregnancy, the PBPK model accurately predicted AUC and Cmax with a prediction error (%PE) of less than 25%. The evaluation of the EFV PBPK model revealed mixed results. While the model accurately predicted certain parameters for non-pregnant adults, significant discrepancies were observed in predictions for higher doses (600 vs. 400 mg) and pregnant individuals. The model’s performance during pregnancy was poor, indicating the need for further refinement to account for genetic polymorphism. Gender differences also influenced EFV pharmacokinetics, with lower exposure levels in females compared to males. These findings highlight the complexity of modeling EFV, in general, but specifically in pregnant populations, and the importance of validating such models for accurate clinical application. The study highlights the importance of tailoring dosing regimens for pregnant individuals to ensure both safety and efficacy, particularly when using combination therapies with UGT substrate drugs. Although drug-drug interactions between LTG and EFV appear minimal, further research is needed to improve predictive models and enhance their accuracy. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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21 pages, 3654 KB

Open AccessArticle

Interspecies Brain PBPK Modeling Platform to Predict Passive Transport through the Blood–Brain Barrier and Assess Target Site Disposition

by Parsshava Mehta, Amira Soliman, Leyanis Rodriguez-Vera, Stephan Schmidt, Paula Muniz, Monica Rodriguez, Marta Forcadell, Emili Gonzalez-Perez and Valvanera Vozmediano

Pharmaceutics 2024, 16(2), 226; https://doi.org/10.3390/pharmaceutics16020226 - 4 Feb 2024

Cited by 5 | Viewed by 4022

Abstract

The high failure rate of central nervous system (CNS) drugs is partly associated with an insufficient understanding of target site exposure. Blood–brain barrier (BBB) permeability evaluation tools are needed to explore drugs’ ability to access the CNS. An outstanding aspect of physiologically based pharmacokinetic (PBPK) models is the integration of knowledge on drug-specific and system-specific characteristics, allowing the identification of the relevant factors involved in target site distribution. We aimed to qualify a PBPK platform model to be used as a tool to predict CNS concentrations when significant transporter activity is absent and human data are sparse or unavailable. Data from the literature on the plasma and CNS of rats and humans regarding acetaminophen, oxycodone, lacosamide, ibuprofen, and levetiracetam were collected. Human BBB permeability values were extrapolated from rats using inter-species differences in BBB surface area. The percentage of predicted AUC and Cmax within the 1.25-fold criterion was 85% and 100% for rats and humans, respectively, with an overall GMFE of <1.25 in all cases. This work demonstrated the successful application of the PBPK platform for predicting human CNS concentrations of drugs passively crossing the BBB. Future applications include the selection of promising CNS drug candidates and the evaluation of new posologies for existing drugs. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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Review

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18 pages, 2121 KB

Open AccessReview

Advancements in Virtual Bioequivalence: A Systematic Review of Computational Methods and Regulatory Perspectives in the Pharmaceutical Industry

by Nasser Alotaiq and Doni Dermawan

Pharmaceutics 2024, 16(11), 1414; https://doi.org/10.3390/pharmaceutics16111414 - 3 Nov 2024

Cited by 8 | Viewed by 3730

Abstract

Background/Objectives: The rise of virtual bioequivalence studies has transformed the pharmaceutical landscape, enabling more efficient drug development processes. This systematic review aims to explore advancements in physiologically based pharmacokinetic (PBPK) modeling, its regulatory implications, and its role in achieving virtual bioequivalence, particularly for complex drug formulations. Methods: We conducted a systematic review of clinical trials using computational methods, particularly PBPK modeling, to carry out bioequivalence assessments. Eligibility criteria are emphasized during in silico modeling and pharmacokinetic simulations. Comprehensive literature searches were performed across databases such as PubMed, Scopus, and the Cochrane Library. A search strategy using key terms and Boolean operators ensured that extensive coverage was achieved. We adhered to the PRISMA guidelines in regard to the study selection, data extraction, and quality assessment, focusing on key characteristics, methodologies, outcomes, and regulatory perspectives from the FDA and EMA. Results: Our findings indicate that PBPK modeling significantly enhances the prediction of pharmacokinetic profiles, optimizing dosing regimens, while minimizing the need for extensive clinical trials. Regulatory agencies have recognized this utility, with the FDA and EMA developing frameworks to integrate in silico methods into drug evaluations. However, challenges such as study heterogeneity and publication bias may limit the generalizability of the results. Conclusions: This review highlights the critical need for standardized protocols and robust regulatory guidelines to facilitate the integration of virtual bioequivalence methodologies into pharmaceutical practices. By embracing these advancements, the pharmaceutical industry can improve drug development efficiency and patient outcomes, paving the way for innovative therapeutic solutions. Continued research and adaptive regulatory frameworks will be essential in navigating this evolving field. Full article

(This article belongs to the Special Issue Development of Physiologically Based Pharmacokinetic (PBPK) Modeling)

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