Journal of Pharmacokinetics and Pharmacodynamics最新文献

{"title":"A systems pharmacology model for paracetamol overdose and treatment.","authors":"Jingyun Li, Angela L Chiew, Geoffrey K Isbister, Stephen B Duffull","doi":"10.1007/s10928-026-10060-9","DOIUrl":"10.1007/s10928-026-10060-9","url":null,"abstract":"<p><p>Paracetamol overdose is the leading cause of acute liver failure in many countries, including North America and the United Kingdom. While timely administration with the standard treatment is generally effective, the optimal treatment for scenarios such as \"massive\" overdose or modified release paracetamol overdose remains unknown. In this work we aim to develop and calibrate a systems pharmacology model for paracetamol-induced hepatotoxicity with the influence of administration of the antidote N-acetylcysteine (NAC). The system model integrates five components, including (1) input of paracetamol, (2) paracetamol metabolism of parent drug and metabolites, (3) physiological turnover of endogenous sulfur-containing substrates, including the metabolism of cysteine to produce glutathione and inorganic sulfate, etc., (4) a general model for the release of biomarkers from injured hepatocytes to blood, and (5) a PK model for NAC and three proposed mechanisms of NAC effect. The final systems model demonstrated a good description of the concentration-time courses of paracetamol, its metabolites and biomarkers after administration of a normal dose to a large overdose of paracetamol. The final model provides a quantitative and comprehensive understanding of the causal pathway of paracetamol-induced liver toxicity and its treatment, which allows the investigation of the 'what if' scenarios in the rescue of paracetamol poisoning.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 6","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149025230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A mechanism-based model of immune status effects on antibiotic PK/PD targets in bacteremia.","authors":"Marinda van de Kreeke, Anh Duc Pham, Michelle Mehciz, Tamara Jordens, Marnix G Uyterlinde, Rob C van Wijk, Linda B S Aulin, Catherijne A J Knibbe, Elke H J Krekels, Laura B Zwep, J G Coen van Hasselt","doi":"10.1007/s10928-026-10063-6","DOIUrl":"10.1007/s10928-026-10063-6","url":null,"abstract":"<p><p>A key determinant of antibiotic dose selection is the pharmacokinetic/pharmacodynamic (PK/PD) target, typically determined using dose fractionation studies in preclinical infection models. However, such studies often do not consider the host immune response, despite its important role in bacterial infection. We therefore aimed to systematically characterize the potential contributions of the innate immune response on antibiotic PK/PD targets using a novel mathematical mechanism-based model, incorporating interactions between neutrophils, monocytes and bacterial pathogens. We parametrized the model using data from multiple in vitro host-pathogen interaction studies and calibrated using data from previous in vivo infection models. Key parameters included phagocytosis and digestion rates of neutrophils and monocytes, driven by immune cell concentrations and finite ingestion capacities. To describe data from immune competent rodent infection models, maximum phagocytosis rates required a 77% reduction relative to in vitro estimates for both cell types. The calibrated host-pathogen interaction model was then integrated with a pharmacodynamic model accounting for pathogen-drug interactions for four antibiotic modalities. We performed in silico dose fractionation studies for bacteremia thereby evaluating the impact of different types and magnitudes of immune deficiencies, e.g., neutropenia, monocytopenia, on PK/PD targets in humans. The combination of severe neutropenia and monocytopenia required up to 2.2-fold increase in target AUC/MIC for concentration-dependent antibiotics, and up to a 58% increase in T>MIC for time-dependent antibiotics, compared with immune competent individuals. In conclusion, this study provides general insights into the impact of neutrophil and monocyte suppression on PK/PD targets and associated dosage adjustments in case of immune suppression.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 6","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13597578/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149025222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Depot-central synchronization of a pharmacokinetic model with capacity-limited saturable absorption.","authors":"Xiaotian Wu, Yuting Jin, Zhong Jin, Jun Li","doi":"10.1007/s10928-026-10058-3","DOIUrl":"10.1007/s10928-026-10058-3","url":null,"abstract":"<p><p>Nonlinear drug absorption, driven by saturable transport or enzyme-mediated processes, significantly impacts drug disposition, yet its theoretical framework remains underdeveloped. This study investigates a one-compartment pharmacokinetic (PK) model featuring nonlinear saturable absorption and linear elimination under single- and multiple-dose regimens. We derive mathematical solutions for the concentration-time profiles in both scenarios. For multiple-dose administration, we identify a critical threshold where steady-state concentrations ([Formula: see text]) transition between constant and non-constant periodic solutions depending on the dosing regimen. Our analysis reveals that the Hill or Michaelis-Menten exponent α directly modulates oscillation amplitude, with higher values increasing plasma variability. Furthermore, we mathematically characterize key PK metrics, such as the Area Under the Concentration-time Curve (AUC) and the Fluctuation Index (FI), demonstrating that the relationship between single- and multiple-dose AUC is regimen-dependent, while the FI exhibits a dose-dependency that contrasts with classical first-order kinetics. These theoretical results are validated using clinical data for Cefatrizine. Overall, this work elucidates the intrinsic properties of nonlinear Hill-type or Michaelis-Menten absorption, providing a robust mathematical foundation for optimizing dosage regimen design.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148818607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ehrlich occupancy time: beyond [Formula: see text] to a complete residence time framework.","authors":"Justin Eilertsen, Santiago Schnell, Sebastian Walcher","doi":"10.1007/s10928-026-10049-4","DOIUrl":"10.1007/s10928-026-10049-4","url":null,"abstract":"<p><p>Drug-target occupancy time-the cumulative duration a target remains bound-critically influences therapeutic efficacy. While Copeland's widely-used residence time ([Formula: see text]) emphasizes dissociation kinetics, it neglects association rates, rebinding events, and drug elimination that affect in vivo outcomes. Returning to Paul Ehrlich's 1913 principle that drugs act only when bound (\"Corpora non agunt nisi fixata\"), we develop a mathematically rigorous framework defining Ehrlich occupancy time, EOT, as the integral of fractional target occupancy over time. Our approach explicitly incorporates association ([Formula: see text]) and dissociation ([Formula: see text]) kinetics, accounts for rebinding, and extends to systems with drug removal. For drug-receptor closed systems at equilibrium, we prove that relative EOT equals the equilibrium occupancy fraction; under ligand-excess conditions this reduces to [Formula: see text], where [Formula: see text] is the dissociation constant and [Formula: see text] the drug concentration. For induced-fit mechanisms, conformational changes reduce the effective dissociation constant to [Formula: see text] (where [Formula: see text] and [Formula: see text] are forward and reverse isomerization rates), prolonging occupancy through kinetic trapping. Critically, for drug-receptor systems with first-order drug elimination at rate [Formula: see text], we derive rigorous bounds: [Formula: see text], where [Formula: see text] is the total cumulative occupancy time as [Formula: see text], revealing that both binding affinity and elimination rate jointly determine occupancy. This explains why high-affinity drugs can fail clinically if eliminated rapidly, and identifies pharmacokinetic optimization opportunities. We prove Copeland's definition is a special case of Ehrlich occupancy time when rebinding is absent. Our framework provides quantitative tools for optimizing drug design beyond binding affinity and enables improved prediction of in vivo efficacy where pharmacokinetics dominate.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148620218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"External validation of population pharmacokinetic models of adalimumab in adult patients with inflammatory bowel disease: towards model-informed precision dosing.","authors":"Irene Aguilo-Lafarga, Tonet Serés-Noriega, Vicente Gimeno-Ballester, Pilar Antonia Corsino Roche, Raquel Vicente Lidon, Eva Maria Sierra Moros, Sonia Gallego, Santiago Garcia Lopez, Maria Reyes Abad Sazatornil","doi":"10.1007/s10928-026-10056-5","DOIUrl":"10.1007/s10928-026-10056-5","url":null,"abstract":"<p><p>Inflammatory bowel disease (IBD) has variability in the pharmacokinetics of adalimumab, which may predispose patients to subtherapeutic concentrations, therapeutic failure, and/or drug immunogenicity. Population pharmacokinetic (popPK) models estimate individual pharmacokinetic parameters and allow to personalize therapeutic regimens through Model-Informed Precision Dosing (MIPD). This retrospective, longitudinal study evaluated the predictive performance of six popPK models of adalimumab in adult patients with IBD treated at a tertiary hospital. The adequacy and prediction of the models were externally validated using visual analysis of the goodness-of-fit (GOF) plots, prediction-corrected visual predicted checks (pcVPC), analysis of residuals, and statistical metrics such as the Akaike Information Criteria. Bias and prediction were also calculated using mean prediction error, mean absolute percentage error and root mean square error. Bootstrap resampling was applied for statistical comparisons. Pharmacokinetic parameters were estimated using Bayesian methods and compared to theoretical values. A total of 201 subjects were included, 88% with Crohn's disease, mean age 48.6 (± 16.2) years, 44.8% women. Overall, Berends and Vande Casteele models demonstrated the best predictive performance in the majority of comparative analyses: higher coverage in pcVPC and correlation between observed and predicted values, lower bias and precision values, the lowest AIC, and a homogeneous distribution of residuals. However, both models overestimated adalimumab population clearance. These findings support the application of the Berends and Vande Casteele models in clinical MIPD strategies. Therefore, pending broader evidence in different populations, driving MIPD adoption is critical to optimize adalimumab regimens and maximize sustained clinical outcomes.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148620240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Tracer kinetic modeling of a 14 kDa anti-CD8 PET tracer (2C8v144) for in vivo estimation of CD8 expression in tissue and blood, binding affinity, and total body receptor occupancy.","authors":"Ruediger E Port, C Andrew Boswell, Annie Ogasawara, Herman Gill, Jan Marik, Alice F Tarantal, Eric Berg, Simon P Williams, Gregory Z Ferl","doi":"10.1007/s10928-026-10055-6","DOIUrl":"10.1007/s10928-026-10055-6","url":null,"abstract":"","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148620227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion models for virtual populations and pharmacometric simulations.","authors":"Prathamesh Kishor Gadgil, Shamith Manjunath Poojari, Murali Ramanathan","doi":"10.1007/s10928-026-10054-7","DOIUrl":"10.1007/s10928-026-10054-7","url":null,"abstract":"<p><p>To evaluate diffusion model-based artificial intelligence approaches for generating virtual populations with physiological determinants of drug dosing (PDODD) and pharmacokinetic (PK) profiles. A denoising diffusion probabilistic model (DDPM) was applied to a 31-variable dataset of PDODD covariates (18 continuous, 13 binary) from the National Health and Nutrition Examination Survey and compared to a tabular variational autoencoder (TVAE). For nivolumab PK data (12,000 patients, 13 time points, 5 covariates), sequence-based diffusion model (SDM) and a time-aware diffusion model (TDM) with temporal self-attention were evaluated. The predictive performance of the TDM was evaluated by imputing masked time points. All models were trained and tested on 80%:20% partitions of the data using univariate, bivariate, and multivariate distributional similarity metrics. The diffusion model satisfactorily approximated the univariate distributions of continuous PDODD biomarkers (mean Kolmogorov-Smirnov D-statistic, KSD = 0.014), disease status frequencies (mean absolute error, MAE = 0.31%), and preserved bivariate correlations (MAE = 0.033). DDPM outperformed TVAE for categorical variables (0.31% vs. 1.07% MAE) and correlation (0.033 vs. 0.091 MAE). For nivolumab PK, SDM has KSD of 0.047 and a relative error of 1.36%. TDM accurately imputed missing PK timepoints (KSD = 0.014), reconstructing masked Day 1, Peak concentration (Cmax) Dose-9, and Terminal phase concentrations with MAE of 0.43%, 0.25%, and 0.76%, and correlations ≥ 0.999. Diffusion models demonstrated strong performance in generating cross-sectional PK covariate data and longitudinal PK profiles, capturing complex distributional and temporal dependencies. Diffusion-based approaches provide a flexible and robust framework for virtual simulations in pharmacometrics.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13421196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148620213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategies for pediatric dose derivation from population pharmacokinetic models.","authors":"Andreas Krause, Géraldine Cellière","doi":"10.1007/s10928-026-10053-8","DOIUrl":"10.1007/s10928-026-10053-8","url":null,"abstract":"<p><p>Health authorities worldwide require clinical studies in children to ensure scientifically rigorous and consistent dosing. Before pediatric data are available, model-based methods provide a scientific and reproducible way to determine doses for pediatric studies. A general introduction to pediatric scaling is provided, followed by a focus on population pharmacokinetic methods to scale from adults to children using exposure matching. Exposure matching involves two steps: first, optimal pediatric doses are derived using a fine grid of body sizes and doses; second, feasible doses are selected based on availability of dose strengths. Three strategies are employed and compared, best fit (similar exposure in adults and children across ages and body sizes), conservative (children's exposure not exceeding adults'), and progressive (children's exposure not less than adults'). Each recommendation is evaluated against the exposure metrics C_max, C_trough, and AUC at steady state for the optimal dosing scheme. Simulations assess interindividual variability in exposure. Visualizations enable risk assessment of exposure distributions and post-hoc refinement of dosing schemes. The formalized approach offers clinical teams a reproducible basis for pediatric dose selection. An implementation in R and Monolix is provided.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13421238/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148620292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of a translational whole-body physiologically based pharmacokinetic model to investigate the biodistribution of lipid nanoparticle-based mRNA therapeutics for intracellular protein targets.","authors":"Kenji Miyazawa, Hojjat Bazzazi, Wei Gao","doi":"10.1007/s10928-026-10052-9","DOIUrl":"10.1007/s10928-026-10052-9","url":null,"abstract":"<p><p>Lipid nanoparticle (LNP)-based messenger RNA (mRNA) therapeutics enable in vivo production of diverse protein modalities, but their translation is complicated by multiscale pharmacokinetics encompassing tissue transport, cellular uptake, and intracellular processing. We developed a platform translational whole-body physiologically based pharmacokinetic (PBPK) model to mechanistically characterize the biodistribution and protein expression of intravenously administered mRNA-LNP therapeutics. The model integrates receptor-mediated, saturable tissue infiltration, lymphatic recirculation, hepatic uptake, and explicit intracellular processes including endosomal degradation, mRNA escape, translation, and protein turnover. Parameters were calibrated using comprehensive rat biodistribution data containing both tissue-level mRNA and translated protein measurements, enabling characterization of rapid early tissue deposition and dominant hepatic protein production. Sensitivity analyses identified endosomal degradation, mRNA stability, and translation efficiency as the primary determinants of hepatic protein exposure, whereas increasing tissue influx alone yielded minimal effect. Using fundamental allometric scaling principle, the model was translated from rat to human and evaluated against published clinical plasma mRNA pharmacokinetics of an mRNA-encoded monoclonal antibody. Virtual population simulations reproduced dose-dependent peak timing and clearance across multiple dosing regimens. Cell-type specific simulation analyses further demonstrated the competing roles of Kupffer cells and hepatocytes in shaping liver protein exposure. This whole-body PBPK framework provides a mechanistic and predictive platform to support first-in-human dose selection, to interrogate multilevel determinants of mRNA pharmacokinetics, and to guide rational mRNA-LNP design.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13421247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148620195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the structural identifiability of nonlinear models of ligand binding dynamics.","authors":"Carla White, Vivi Rottschäfer, Lloyd Bridge","doi":"10.1007/s10928-026-10040-z","DOIUrl":"10.1007/s10928-026-10040-z","url":null,"abstract":"<p><p>Quantification of drug-cell interactions and subsequent cellular responses by using experimental data together with mathematical models of assumed binding and signalling schematics is vital to many research programmes; data fitting provides estimates for important pharmacological parameters including kinetic parameters controlling drug affinity and efficacy. Ordinary differential equation (ODE) models are a key component of many receptor theory studies used for this purpose. In using ODE simulations to fit experimental data and estimate these parameters, the theory of the identifiability properties of the system is often overlooked. Indeed, structural identifiability analysis (SIA) is often overlooked in many fields of bio-modelling. Building on recent SIA for linear ligand binding models in receptor theory, we present a new analysis of identifiability properties of nonlinear receptor theory models. We include models of ligand depletion in binding assays and ligand-induced dimerisation (LID). The classical SIA approaches of Taylor Series and similarity transformation are applied, using detailed step-by-step calculations to illustrate the complexity of the implementations. New results are obtained which show that the nonlinear ligand-depletion counterpart models of non-identifiable linear ligand excess models are globally identifiable from a single timecourse. Also, the LID model is shown to be globally identifiable if an experimental aparatus-dependent parameter is obtained. The analysis highlights issues of tractability of the methods for similar and higher-dimensional nonlinear models in receptor theory.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13380553/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148497786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}