In Silico Pharmacokinetic and Pharmacodynamic (PK-PD) Modeling

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 886

Special Issue Editors


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Guest Editor
Faculty of Pharmacy and Pharmaceutical Sciences, Katz Group-Rexall Centre for Pharmacy & Health Research, University of Alberta, 11315–87 Avenue, Edmonton, AB T6G 2E1, Canada
Interests: pharmacokinetics; chirality; drug interactions; formulation and drug delivery
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E-Mail Website
Guest Editor
Faculty of Pharmacy & Pharmaceutical Sciences, Katz Group-Rexall Centre for Pharmacy & Health Research, University of Alberta, 11361–87 Avenue, Edmonton, AB T6G 2E1, Canada
Interests: biopharmaceutics; inhalable nanopartilces; traditional medicines
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pharmacokinetic and pharmacodynamic (PK-PD) modeling is an essential tool in modern drug development and therapeutic optimization. Leveraging recent advancements in computational methods, including physiologically based pharmacokinetic (PBPK) modeling and machine learning, researchers can simulate complex biological systems, predict therapeutic outcomes, and refine dosing strategies with unprecedented precision.

This Special Issue aims to focus on the transformative integration of in silico approaches into PK-PD modeling, showcasing advancements in methodology, computational tools, and their translational applications. By addressing key challenges in precision medicine, regulatory science, and clinical decision-making, we aim to foster interdisciplinary innovation and broaden the impact of in silico modeling on healthcare outcomes.

Key Topics of Interest:

  • Physiologically Based Pharmacokinetic (PBPK) and Toxicokinetic (PBTK) Modeling: Predicting ADME processes across populations and physiological conditions; regulatory applications.
  • Population Pharmacokinetics (PopPKs): Mixed-effects modeling of inter-individual variability in drug exposure and response.
  • Quantitative Systems Pharmacology (QSP): Integrating systems biology with PK-PD to evaluate drug interactions within complex networks.
  • Bayesian Pharmacometric Modeling: Utilizing Bayesian methods to incorporate prior knowledge for personalized therapy optimization.
  • Artificial Intelligence and Machine Learning in PK-PD: Applications in drug interaction prediction, dose optimization, and precision medicine.
  • In Silico Bioequivalence: Reducing clinical trial reliance through computational approaches.
  • Multi-Objective Optimization: Balancing efficacy and toxicity in therapeutic regimens using advanced algorithms.
  • Regulatory Science and Quality Assessment: Computational tools in regulatory decision-making and pharmaceutical product evaluation.
  • Translational and Predictive Modeling: Real-world case studies demonstrating successful clinical implementation of in silico predictions.

Benefits of Publishing in This Special Issue:

  • Enhanced visibility and citation potential through focused dissemination.
  • Opportunities for interdisciplinary collaboration across computational biology, clinical pharmacology, and pharmaceutical sciences.
  • Contribution to the advancement of cutting-edge in silico modeling techniques and applications.

Submit your manuscript today and contribute to the future of precision pharmacology and computational innovation!

Prof. Dr. Neal M. Davies
Prof. Dr. Raimar Löbenberg
Guest Editors

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Keywords

  • physiologically based pharmacokinetics (PBPKs)
  • population pharmacokinetics (PopPKs)
  • quantitative systems pharmacology (QSP)
  • Bayesian modeling
  • artificial intelligence in PK-PD
  • in silico bioequivalence
  • multi-objective optimization
  • translational pharmacokinetics

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Published Papers (2 papers)

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Research

41 pages, 3917 KB  
Article
Physiologically Based Pharmacokinetic Modeling and Simulations in Lieu of Clinical Pharmacology Studies to Support the New Drug Application of Asciminib
by Ioannis Loisios-Konstantinidis, Felix Huth, Matthias Hoch and Heidi J. Einolf
Pharmaceutics 2025, 17(10), 1266; https://doi.org/10.3390/pharmaceutics17101266 - 26 Sep 2025
Abstract
Background: Asciminib (Scemblix®) is approved for the first-line treatment of adult patients with chronic myeloid leukemia in the chronic phase at 40 mg twice daily (BID) and 80 mg once daily (QD) or 200 mg BID for patients harboring the [...] Read more.
Background: Asciminib (Scemblix®) is approved for the first-line treatment of adult patients with chronic myeloid leukemia in the chronic phase at 40 mg twice daily (BID) and 80 mg once daily (QD) or 200 mg BID for patients harboring the T315I mutation. Objectives: (1) Extrapolate the DDI magnitude as the perpetrator or victim of other drugs and the effect of organ impairment to untested doses; (2) Predict clinically untested DDI scenarios. Methods: Asciminib is primarily cleared by cytochrome P450 (CYP)3A4, UDP-glucuronosyltransferases (UGT)2B7, UGT2B17, UGT1A3/4, and the breast-cancer-resistance protein (BCRP). In vitro asciminib is an inhibitor of several CYP, UGT enzymes, and transporters and is an inducer of CYP1A2 and CYP3A4. Clinical DDI studies assessed asciminib 40 mg BID as a perpetrator on CYP-sensitive substrates. Additional studies evaluated the impact of strong CYP3A4 perpetrators and imatinib on a single 40 mg dose of asciminib. Hepatic and renal impairment studies were also conducted at the 40 mg dose. A nonlinear whole-body physiologically based pharmacokinetic (PBPK) model was developed and verified for asciminib as a CYP3A4, UGT, and BCRP substrate and a perpetrator of several CYP and UGT enzymes. Results: This PBPK model was applied in lieu of clinical pharmacology studies to support the new drug application of Scemblix® and to bridge data from 40 mg BID to the 80 mg QD and 200 mg BID dose regimens. Conclusions: The PBPK predictions informed the drug product label and are estimated to have replaced at least 10 clinical studies. Full article
(This article belongs to the Special Issue In Silico Pharmacokinetic and Pharmacodynamic (PK-PD) Modeling)
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17 pages, 1231 KB  
Article
Indirect Modeling of Post-Prandial Intestinal Lymphatic Uptake of Halofantrine Using PBPK Approaches: Limitations and Implications
by Malaz Yousef, Farag E. S. Mosa, Khaled H. Barakat, Neal M. Davies and Raimar Löbenberg
Pharmaceutics 2025, 17(9), 1228; https://doi.org/10.3390/pharmaceutics17091228 - 22 Sep 2025
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Abstract
Background/Objectives: Despite the recognized importance and distinctive characteristics of the intestinal lymphatic pathway in drug absorption, its pharmacokinetic modeling remains largely unexplored. This study aimed to address this gap by developing a physiologically based pharmacokinetic model (PBPK) to represent the oral lymphatic uptake [...] Read more.
Background/Objectives: Despite the recognized importance and distinctive characteristics of the intestinal lymphatic pathway in drug absorption, its pharmacokinetic modeling remains largely unexplored. This study aimed to address this gap by developing a physiologically based pharmacokinetic model (PBPK) to represent the oral lymphatic uptake of halofantrine following a fatty meal. Methods: Using GastroPlus™ 9.8.3 and published literature data, halofantrine absorption, distribution, metabolism, and elimination in both fasting and fed states were modeled. As the used software does not directly simulate intestinal lymphatic transport, lymphatic involvement in the fed state was examined indirectly through parameter adjustments such as first-pass metabolism, pKa-driven solubility changes, and bile-salt-mediated solubilization, with the aid of molecular dynamics simulations under post-prandial pH. Results: The pharmacokinetic models revealed a reduction in the first-pass effect of halofantrine in the fed state compared to that in the fasting state. While adjustments in metabolism kinetics sufficed for constructing a representative PBPK model in the fasting state, capturing the fed-state profile required both modifications to metabolism kinetics and other parameters related to the structural rearrangements of halofantrine driven by the changes in intestinal pH following food intake. These changes were confirmed using molecular dynamics simulations of halofantrine in pHs reflecting the post-prandial conditions. Conclusions: This study underscores the need for further exploration and direct modeling of intestinal lymphatic uptake via PBPK models, highlighting its underexplored status in simulation algorithms. Moreover, the importance of integrating representative physicochemical factors for drugs, particularly in post-prandial conditions or lipid formulations, is evident. Overall, these findings contribute to advancing predictive regulatory and developmental considerations in drug development using post hoc analyses. Full article
(This article belongs to the Special Issue In Silico Pharmacokinetic and Pharmacodynamic (PK-PD) Modeling)
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