Journal of Pharmacokinetics and Pharmacodynamics最新文献

{"title":"Pharmacometrics education for all by overcoming language barriers to enhance global collaboration.","authors":"Sonia Khier, Anna H-X P Chan Kwong, Maud Harnichard, Sihem Ait-Oudhia","doi":"10.1007/s10928-025-09991-6","DOIUrl":"https://doi.org/10.1007/s10928-025-09991-6","url":null,"abstract":"<p><p>Proficiency in English is essential in scientific disciplines; however, it is unevenly distributed globally, creating barriers for those with limited training. Research in neuroscience supports the benefits of teaching in a student's native language. Consequently, pharmacometrics, a complex and growing field, stands to gain significantly from overcoming language barriers to better train future scientists. One effective strategy is to offer pharmacometrics education in various languages, particularly in regions with low English proficiency, such as French-speaking African countries. Recently, two French-led pharmacometrics training programs were conducted in Africa, demonstrating the positive impact of such initiatives. These programs are adaptable to other countries and languages, and ultimately, they could contribute to global health improvements by making pharmacometrics education more accessible worldwide.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"46"},"PeriodicalIF":2.8,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144753648","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: Cross-species translational modelling of targeted therapeutic oligonucleotides using physiologically based pharmacokinetics.","authors":"Abdallah Derbalah, Felix Stader, Cong Liu, Adriana Zyla, Tariq Abdulla, Qier Wu, Masoud Jamei, Iain Gardner, Armin Sepp","doi":"10.1007/s10928-025-09993-4","DOIUrl":"10.1007/s10928-025-09993-4","url":null,"abstract":"","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"45"},"PeriodicalIF":2.8,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310875/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144742322","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":"Lessons learned from QT prolongation risk assessment for antibody-drug conjugates in oncology.","authors":"Shruti D Shah, Roxanne C Jewell, Geraldine Ferron-Brady, Sandra A G Visser","doi":"10.1007/s10928-025-09988-1","DOIUrl":"10.1007/s10928-025-09988-1","url":null,"abstract":"<p><p>Antibody-drug conjugates (ADCs) are advanced cancer therapeutics that link monoclonal antibodies to cytotoxic drugs, enhancing targeted delivery to tumors. Since the FDA's first ADC approval in 2000, 14 ADCs have received approval to date (March 2025), underscoring their therapeutic value across cancer types. A prolonged QT interval is a known risk factor for the development of torsades de pointes (TdP), a potentially fatal ventricular arrhythmia. Therefore, assessing and mitigating the potential for QT prolongation is a fundamental aspect of drug development, especially for oncology therapeutics where patients may already be at an increased risk of cardiovascular complications or receiving other QT-prolonging drugs. Traditional QT risk assessment, as outlined in the ICH E14 guidance, is challenging in oncology due the safety profile of anticancer drugs, which precludes study in healthy participants, and the ethical complications of placebo-controlled studies in patients with cancer; therefore, dedicated QT studies and/or concentration-corrected QT (QTc) assessments have been used as alternative approaches. This review investigates QT risk assessment for FDA-approved ADCs, examining nonclinical and clinical approaches and summarizing the strategies used in informing each ADC's labeling. Findings suggest that ADCs generally exhibit low proarrhythmic risk, attributed to the low systemic concentration of their payloads, and minimal QT effects have been observed in clinical settings. This analysis advocates a streamlined, fit-for-purpose QT risk assessment strategy in ADC development, reducing reliance on dedicated QT studies and promoting integrated assessments in early-phase trials. This approach can optimize ADC safety evaluation, supporting ongoing innovation and therapeutic application in oncology.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"44"},"PeriodicalIF":2.8,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144731926","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":"Practical guide to concentration-QTc modeling: a hands-on tutorial.","authors":"Joanna Parkinson, Corina Dota, Dinko Rekić","doi":"10.1007/s10928-025-09981-8","DOIUrl":"10.1007/s10928-025-09981-8","url":null,"abstract":"<p><p>Concentration-QTc (C-QTc) analysis is a model-based method widely used to assess the impact of drugs on QT interval duration. C-QTc modelling was enabled to be used after the publication of the International Council for Harmonisation (ICH) E14 Questions and Answers guidance document in 2015, followed by the Scientific White Paper on C-QTc modelling (Garnett et al. J Pharmacokinet Pharmacodyn 45(3):383-397 2018), which included technical details and recommendations on how to perform and report the modelling. This hands-on tutorial aims to provide a practical implementation of the recommended C-QTc modelling methodology, including R code to perform the complete analysis, from data formatting to model predictions. The target audience is scientists who will perform C-QTc analyses. The tutorial uses real data from a previously published QT study by (Johannesen et al.Clin Pharmacol Ther 96(5):549-558 2014), focusing on two active treatments (dofetilide and verapamil) and placebo to illustrate positive and negative QT signals. The methodology implemented in this tutorial follows the recommendations outlined in the White paper. This tutorial includes practical steps for preparing an analysis-ready dataset, conducting exploratory data analysis, fitting the linear mixed effects (LME) model, assessing model performance and estimating the upper limit of the two-sided 90% confidence interval (CI) of baseline and placebo-corrected QTc (ΔΔQTc). Reproducibility of this workflow is ensured through the use of pkgr to manage R packages. The R codes provided as part of this tutorial were successfully used for several projects within the AstraZeneca portfolio and accepted by health authorities as part of QTc submissions.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"43"},"PeriodicalIF":2.8,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144731927","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":"Quantifying clinical and genetic factors influencing rate and severity of autosomal dominant tubulointerstitial kidney disease progression.","authors":"Shyam S Ramesh, Mark Rogge, Kendrah O Kidd, Adrienne H Williams, Deok Yong Yoon, Julie Roignot, Katherine Blakeslee, Anthony J Bleyer, Sarah Kim","doi":"10.1007/s10928-025-09989-0","DOIUrl":"10.1007/s10928-025-09989-0","url":null,"abstract":"<p><p>Autosomal dominant tubulointerstitial kidney disease (ADTKD), caused by mutations in UMOD and MUC1 genes, leads to tubular damage and fibrosis, ultimately resulting in kidney failure (KF). This study investigated clinical and genetic factors influencing the rate and severity of ADTKD progression by developing quantitative models. An estimated glomerular filtration rate (eGFR) of 10 mL/min/1.73 m² was used to define KF, corresponding to dialysis initiation. Natural history data from the Wake Forest University School of Medicine study were used to develop the models for UMOD (n = 371) and MUC1 (n = 233) disease types (age ≥ 18 years). Longitudinal change in eGFR and time-to-KF were quantified using nonlinear mixed-effects and parametric time-to-event modeling approaches, respectively, in Monolix (version 2024R1). Sigmoid I_max functions with steepness parameters varying before and after inflection points best captured eGFR decline. Patients with UMOD and MUC1 disease variants exhibited a similar initial shallow steepness ( <math><mo>≈</mo></math> 1), but after inflection, each declined rapidly. MUC1 patients progressed faster than UMOD during the post-inflection phase (γ₂ = 10.23 vs. 6.34). eGFR at first clinic visit (eGFR_FCV) and age at first clinic visit (AFCV) significantly affected between-subject variability in eGFR decline. A Weibull hazard function best described the time to KF. In UMOD, males reached Te (the age at which approximately 36.8% of individuals remain free from KF) 4 years earlier than females on average (β_Te_Male = -0.07), indicating faster progression in males. Older AFCV was associated with slower progression to KF (β_Te_AFCV = 0.59 for UMOD and 0.81 for MUC1). These models may help enable quantitative data-driven subgroup analysis in the future, optimizing inclusion/exclusion criteria for ADTKD clinical trials.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"41"},"PeriodicalIF":2.8,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144707849","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":"A semi-mechanistic population pharmacokinetic-pharmacodynamic model to assess downstream drug-target effects on erythropoiesis.","authors":"S Viktor Rognås, Franziska Schaedeli Stark, Maddalena Marchesi, Hanna E Silber Baumann, João A Abrantes","doi":"10.1007/s10928-025-09990-7","DOIUrl":"10.1007/s10928-025-09990-7","url":null,"abstract":"<p><p>Erythropoiesis is a complex process that results in the production of erythrocytes from hematopoietic stem cells in the bone marrow. This work aimed to develop a population pharmacokinetic-pharmacodynamic (PKPD) model describing erythropoiesis and hemoglobin synthesis following bitopertin, an inhibitor of glycine transporter 1 (GlyT1), administration. Data from a Phase 1 clinical trial in 67 healthy subjects administered bitopertin (10, 30, or 60 mg) or placebo for 120 days were analyzed. Hematological assessments included erythrocyte and reticulocyte counts, immature reticulocyte fraction, hemoglobin concentration, and mean corpuscular hemoglobin. The proposed semi-mechanistic model, which leverages data and physiological knowledge, was found to adequately simultaneously describe the dose- and time-dependent changes in the biomarkers. The framework was used to illustrate the potential outcome of hypothetical drug-target interactions at distinct stages of erythropoiesis and hemoglobin synthesis, exemplifying its usefulness in a clinical setting.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"42"},"PeriodicalIF":2.8,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289712/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144707848","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":"Identification of oncology pharmacokinetic drivers through in vitro experiments and computational modeling.","authors":"Britton Boras, Eric C Greenwald, Yuli Wang, Manli Shi, Bernadette Pascual, Julie A Cianfrogna, Derek W Bartlett, Mary E Spilker","doi":"10.1007/s10928-025-09986-3","DOIUrl":"10.1007/s10928-025-09986-3","url":null,"abstract":"<p><p>Drug discovery balances many factors as it identifies compounds for clinical testing, including compound efficacy, safety, pharmacokinetic (PK) properties, commercial feasibility, competitive positioning, and organizational pressures to move quickly with limited knowledge. When considering target engagement within clinically acceptable dosing constraints, design elements often balance potency requirements against the required extent of target engagement, which subsequently inform the PK design criteria (e.g. absorption and half-life considerations). Hence, an early understanding of the magnitude and duration of target engagement can focus design teams by providing well defined design criteria. To this end, an in vitro target engagement assay has been developed to bin targets and compounds by the type of target engagement profile required for efficacy (cellular anti-proliferation). This in turn directionally informs on the required concentration profile most aligned with the efficacy readout, bucketing results into three primary categories that drive efficacy: high transient concentrations, average concentrations, and threshold concentrations. This manuscript will outline the methodology developed for this early target coverage assessment and provide examples with selected compounds spanning molecularly targeted and cytotoxic oncology small molecules.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"40"},"PeriodicalIF":2.2,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690509","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":"Physiologically-based pharmacokinetic model for predicting drug-drug interactions perpetrated by posaconazole in healthy subjects with normal weight and obesity: Concomitant use and washout.","authors":"Christopher D Bruno, Ahmed Elmokadem, David J Greenblatt, Christina R Chow","doi":"10.1007/s10928-025-09983-6","DOIUrl":"10.1007/s10928-025-09983-6","url":null,"abstract":"<p><p>Posaconazole is an effective broad-spectrum triazole antifungal used as prophylaxis or to treat invasive Aspergillus and Candida infections in adults and pediatric patients. Posaconazole is a known strong inhibitor of cytochrome P4503A4 (CYP3A4) and substrate of P-glycoprotein (P-gp), which may lead to drug-drug interactions (DDIs) when co-administered with CYP3A4-sensitive substrates and warrants modified dosing of sensitive drugs when administered concomitantly with posaconazole. Given the long elimination half-life of posaconazole (26-35 h), there is the potential for DDIs caused by posaconazole after discontinuing the antifungal. Our clinical studies revealed that the half-life of posaconazole is significantly prolonged in subjects with a body mass index (BMI) ≥ 35 kg/m², which may put this population at an increased risk of DDIs after stopping posaconazole. This manuscript describes the development, verification, and validation of a whole-body, physiologically-based pharmacokinetic (PBPK) model which describes the concomitant use and washout DDIs of posaconazole delayed-release tablet (DRT) with victim drugs ranolazine and lurasidone in healthy volunteers of normal weight and with obesity. The key findings of this model are 1) the half-life of posaconazole is significantly prolonged in patients with BMI ≥ 35 kg/m² and 2) the mechanism of inhibition of CYP3A4 by posaconazole appears to be irreversible in vivo. This model may be used moving forward to assess the potential for washout DDIs with CYP3A4-sensitive substrates during concomitant use with, and after discontinuing posaconazole in subjects with normal weight and obesity.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"39"},"PeriodicalIF":2.2,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12274254/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144667888","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":"Using Fisher Information Matrix to predict uncertainty in covariate effects and power to detect their relevance in Non-Linear Mixed Effect Models in pharmacometrics.","authors":"Lucie Fayette, Karl Brendel, France Mentré","doi":"10.1007/s10928-025-09987-2","DOIUrl":"https://doi.org/10.1007/s10928-025-09987-2","url":null,"abstract":"<p><p>This work focuses on design of experiments for Pharmacokinetic (PK) and Pharmacodynamic (PD) studies. Non-Linear Mixed Effects Models (NLMEM) modelling allows the identification and quantification of covariates that explain inter-individual variability (IIV). The Fisher Information Matrix (FIM), computed by linearization, has already been used to predict uncertainty on covariate parameters and power of test to detect statistical significance. A covariate effect is deemed statistically significant if it is different from 0 according to a Wald comparison test and clinically relevant if the ratio of change it causes in the parameter is relevant according to a test inspired by the two one-sided tests (TOST) as in bioequivalence studies. FIM calculation was extended by computing its expectation on the joint distribution of the covariates, discrete and continuous. Three methods were proposed: using a provided sample of covariate vectors, simulating covariate vectors, based on provided independent distributions or on estimated copulas. Thereafter, CI of ratios, power of tests and number of subjects needed to achieve desired confidence were derived. Methods were implemented in a working version of the R package PFIM6.1. A simulation study was conducted under various scenarios, including different sample sizes, sampling points, and IIV. Overall, uncertainty on covariate effects and power of tests were accurately predicted. The method was applied to a population PK model of the drug cabozantinib including 27 covariate relationships. Despite numerous relationships, limited representation of certain covariates, FIM correctly predicted uncertainty, and is therefore suitable for rapidly computing number of subjects needed to achieve given powers.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"38"},"PeriodicalIF":2.2,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637369","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":"FDA's insights: implementing new strategies for evaluating drug-induced QTc prolongation.","authors":"Yanyan Ji, Lars Johannesen, Christine Garnett","doi":"10.1007/s10928-025-09985-4","DOIUrl":"10.1007/s10928-025-09985-4","url":null,"abstract":"<p><p>The questions and answers (Q&A) document for ICH E14/S7B provides the following advancements for QTc assessment: concentration-QTc modeling (C-QTc) as the primary analysis, accepting alternative approaches (Q&A 5.1 and 6.1) to thorough QT (TQT) studies, and incorporating an integrated nonclinical risk assessment as supporting evidence. Based on QT study reports reviewed by the FDA between 2016 and 2024, changes to the E14 guideline have resulted in a 34% decrease in the proportion of TQT studies, while the use of C-QTc analysis as the primary analysis has significantly increased. Studies using C-QTc instead of by-time analysis as the primary analysis reduced median sample sizes by 67%, 42%, and 35% for parallel, nested crossover, and crossover studies, respectively. The white paper C-QTc model was used for 60% of drugs that prolonged the QTc interval. From 2020 to 2024, reviews incorporating an integrated nonclinical risk assessment have also increased. The advancements in QTc assessments have streamlined QTc assessment and made clinical trials less resource-intensive. As the advancements continue to evolve the drug safety evaluation is likely to become even more adaptive and enable more precise and targeted QTc assessment.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"52 4","pages":"37"},"PeriodicalIF":2.2,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12198268/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484786","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}