Advances in Pharmacokinetics and Drug Interactions

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

Deadline for manuscript submissions: 20 April 2026 | Viewed by 5203

Special Issue Editors


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Center for Pharmacometrics & Systems Pharmacology, Department of Pharmaceutics Lake Nona (Orlando), University of Florida, 6550 Sanger Road, Office 464, Orlando, FL 32827, USA
Interests: the development and application of disease-drug-trial models in the area of chronic progressive diseases; special patient populations; drug-drug interactions; pharmacokinetics

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Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL, USA
Interests: pharmacokinetics; special populations; pharmacometrics; quantitative pharmacology
Special Issues, Collections and Topics in MDPI journals

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Faculdade de Ciências Farmacêuticas, Universidade Federal de Alfenas (UNIFAL-MG), Alfenas 371300-001, Brazil
Interests: drug toxicology; toxicological analysis; pharmacokinetics; pharmacodynamics; validation of methods

Special Issue Information

Dear Colleagues,

Pharmaceutics is announcing this Special Issue on “Advances in Pharmacokinetics and Drug Interactions” with the goal of exploring the latest developments and advancements in pharmacokinetics (PK), quantitative pharmacology, and drug–drug interactions. Great strides have been made towards furthering our understanding of pharmacokinetics and drug interactions with the development of more advanced modeling and simulation approaches. Quantitative pharmacology approaches are helpful for understanding drug absorption, distribution, metabolism, and excretion, predicting drug concentrations, assessing drug–drug interactions, and understanding the variability in drug response. By integrating PK models with pharmacodynamic (PD) models, we can further forecast drug effects on biomarkers or clinical endpoints.

Drug–drug interactions (DDIs) are a major concern in drug development and clinical practice. DDIs can escalate the frequency and severity of adverse events or elevate the risk of treatment failure. Early prediction of the likelihood and the magnitude of DDIs has become part of the assessment of a new drug’s safety profile during drug development. Mechanistic and physiological approaches enable researchers to anticipate drug behavior across patient populations. In this context, physiologically based pharmacokinetic modeling has been extensively used to assess DDIs and support new drug applications to regulatory agencies. Subsequently, simulations allow the identification of patient subgroups at a higher risk of therapeutic failure, drug interactions, or safety concerns. Once these differences are characterized, the PK model can be linked to response models to assess whether dose adjustments are needed and, in this case, to optimize dosing strategies. Further improvements in pharmacokinetics and drug interactions may enhance pharmacological efficacy, safety, and patient outcomes, enabling more customized and effective treatment interventions.

This Special Issue—“Advances in Pharmacokinetics and Drug Interactions”—aims to showcase recent progress in pharmacokinetics and drug interactions to explore drug behavior and therapeutic results. Potential topics include but are not limited to:

  • PK(/PD), PBPK, QSP models of drugs;
  • Optimization of dosing regimens;
  • Static models to investigate DDI potential and mechanistic models to investigate and confirm DDI potential;
  • In vitro–in vivo extrapolation in the context of DDI;
  • Mechanisms of drug–drug or drug–xenobiotic interactions;
  • Quantitative pharmacology approaches.

We cordially invite researchers from academia, industry, and government agencies working in related fields to submit their work. The Special Issue will undergo rigorous review and editing by leading experts in pharmacokinetics and drug metabolism, ensuring that the articles meet the highest standards of quality and relevance.

Based on your expertise in the field, we would be honored if you would consider our invitation. If you are interested in discussing the Issue further, please feel free to contact the guest editors:

Prof. Dr. Stephan Schmidt
Prof. Dr. Natalia V. De Moraes
Prof. Dr. Vanessa Bergamin Boralli
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.

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

  • pharmacokinetics
  • drug interactions
  • PBPK modeling
  • drug delivery systems
  • personalized medicine

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Published Papers (3 papers)

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Research

18 pages, 1542 KiB  
Article
Pharmacogenetic Influences on Individual Responses to Ocular Hypotensive Agents in Glaucoma Patients
by Sara Labay-Tejado, Virginia Fortuna, Néstor Ventura-Abreu, Mar Hernaez, Valeria Opazo-Toro, Alba Garcia-Humanes, Mercè Brunet and Elena Milla
Pharmaceutics 2025, 17(3), 325; https://doi.org/10.3390/pharmaceutics17030325 - 2 Mar 2025
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Abstract
Background/Objectives: To analyze the genotype that predicts the phenotypic characteristics of a cohort of patients with glaucoma and ocular hypertension (OHT) and explore their influence on the response to ocular hypotensive treatment. Methods: This was a prospective study that included 193 [...] Read more.
Background/Objectives: To analyze the genotype that predicts the phenotypic characteristics of a cohort of patients with glaucoma and ocular hypertension (OHT) and explore their influence on the response to ocular hypotensive treatment. Methods: This was a prospective study that included 193 eyes of 109 patients with glaucoma or OHT under monotherapy with beta-blockers, prostaglandin, or prostamide analogues (BBs, PGAs, PDs). Eight single-nucleotide polymorphisms were genotyped using real-time PCR assays: prostaglandin-F2α receptor (PTGFR) (rs3766355, rs3753380); beta-2-adrenergic receptor (ADRB2) (rs1042714); and cytochrome P450 2D6 (CYP2D6) (*2 rs16947; *35 rs769258; *4 rs3892097; *9 rs5030656, and *41 rs28371725). The main variables studied were baseline (bIOP), treated (tIOP), and rate of variation in intraocular pressure (vIOP), and mean deviation of the visual field (MD). The metabolizer phenotype and the CYP2D6 copy number variation were also evaluated. Results: In total, 112 eyes were treated with PGAs (58.0%), 59 with BBs (30.6%), and 22 with PDs (11.4%). For PTGFR (rs3753380), statistically significant differences were observed in vIOP in the PGA group (p = 0.032). Differences were also observed for ADRB2 (rs1042714) in MD (p < 0.001) and vIOP (p = 0.017). For CYP2D6, ultrarapid metabolizers exhibited higher tIOP (p = 0.010) and lower vIOP (p = 0.046) compared to the intermediate and poor metabolizers of the BB group. Additionally, systemic treatment metabolized by CYP2D6 showed a significant influence on vIOP (p = 0.019) in this group. Conclusions: These preliminary findings suggest the future potential of pharmacogenetic-based treatments in glaucoma to achieve personalized treatment for each patient, and thus optimal clinical management. Full article
(This article belongs to the Special Issue Advances in Pharmacokinetics and Drug Interactions)
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16 pages, 4356 KiB  
Article
Assessing Drug–Drug Interaction and Food Effect for BCS Class 2 Compound BI 730357 (Retinoic Acid-Related Orphan Receptor Gamma Antagonist, Bevurogant) Using a Physiology-Based Pharmacokinetics Modeling (PBPK) Approach with Semi-Mechanistic Absorption
by Tobias Kanacher, Erik Sjögren, Julia Korell, Elodie L. Plan, Jose David Gómez-Mantilla and Ibrahim Ince
Pharmaceutics 2025, 17(3), 314; https://doi.org/10.3390/pharmaceutics17030314 - 1 Mar 2025
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Abstract
Background: The drug candidate BI 730357 is a Biopharmaceutics Classification System (BCS) Class II compound showing atypical absorption after oral administration in fasted and fed healthy individuals, for which conventional traditional deconvolution methods could not explain formulation dependencies. Methods: A physiologically [...] Read more.
Background: The drug candidate BI 730357 is a Biopharmaceutics Classification System (BCS) Class II compound showing atypical absorption after oral administration in fasted and fed healthy individuals, for which conventional traditional deconvolution methods could not explain formulation dependencies. Methods: A physiologically based pharmacokinetic (PBPK) model of BI 730357 was developed using the Open Systems Pharmacology (OSP) PBPK software tool PK-Sim®, which could describe the pharmacokinetics in fasted and fed subjects after single and multiple doses. A Weibull function was used to describe the in vivo formulation kinetics, whereas colonic absorption was adopted as the main driver to describe the late phases of observed pharmacokinetics after oral administration. The food effect was applied using the implemented feature PK-Sim®. Results: The model accurately predicted an observed itraconazole drug–drug interaction (DDI) in fasted subjects and was used to explore the effects of the strong CYP3A4 inducer rifampicin on the pharmacokinetics of BI 730357 after administration in fed subjects. Conclusions: The combined results suggest that the BI 730357 PBPK model with semi-mechanistic absorption can prospectively explore the effects of CYP3A4 inhibitors and inducers on the pharmacokinetics after administration in fed or fasted subjects within the given dose range. Full article
(This article belongs to the Special Issue Advances in Pharmacokinetics and Drug Interactions)
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25 pages, 5791 KiB  
Article
Applying Physiologically Based Pharmacokinetic Modeling to Interpret Carbamazepine’s Nonlinear Pharmacokinetics and Its Induction Potential on Cytochrome P450 3A4 and Cytochrome P450 2C9 Enzymes
by Xuefen Yin, Brian Cicali, Leyanis Rodriguez-Vera, Viera Lukacova, Rodrigo Cristofoletti and Stephan Schmidt
Pharmaceutics 2024, 16(6), 737; https://doi.org/10.3390/pharmaceutics16060737 - 30 May 2024
Cited by 1 | Viewed by 2388
Abstract
Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the [...] Read more.
Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the root causes have not been fully studied. This study aims to investigate the mechanisms behind CBZ’s nonlinear PK and its induction potential on CYP3A4 and CYP2C9 enzymes. To achieve this, we developed and validated a physiologically based pharmacokinetic (PBPK) parent–metabolite model of CBZ and its active metabolite Carbamazepine-10,11-epoxide in GastroPlus®. The model was utilized for Drug–Drug Interaction (DDI) prediction with CYP3A4 and CYP2C9 victim drugs and to further explore the underlying mechanisms behind CBZ’s nonlinear PK. The model accurately recapitulated CBZ plasma PK. Good DDI performance was demonstrated by the prediction of CBZ DDIs with quinidine, dolutegravir, phenytoin, and tolbutamide; however, with midazolam, the predicted/observed DDI AUClast ratio was 0.49 (slightly outside of the two-fold range). CBZ’s nonlinear PK can be attributed to its nonlinear metabolism caused by autoinduction, as well as nonlinear absorption due to poor solubility. In further applications, the model can help understand DDI potential when CBZ serves as a CYP3A4 and CYP2C9 inducer. Full article
(This article belongs to the Special Issue Advances in Pharmacokinetics and Drug Interactions)
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