Clinical Pharmacokinetics最新文献

{"title":"Population Pharmacokinetic Modelling of Norepinephrine in Healthy Volunteers Prior to and During General Anesthesia.","authors":"Yingxue Li, Jeroen V Koomen, Douglas J Eleveld, Johannes P van den Berg, Jaap Jan Vos, Ilonka N de Keijzer, Michel M R F Struys, Pieter J Colin","doi":"10.1007/s40262-024-01430-y","DOIUrl":"10.1007/s40262-024-01430-y","url":null,"abstract":"<p><strong>Background: </strong>Intraoperation hypotension (IOH) is commonly observed in patients undergoing surgery under general anesthesia, and even a brief episode of IOH can lead to unfavorable outcomes. To reduce the risk, blood pressure is closely measured during general anesthesia, and norepinephrine (NE) is frequently administered if hypotension is detected. Despite its routine application, information on the dose-exposure-response relationship of NE remains limited. Additionally, quantification of the influence of general anesthesia on the pharmacokinetics (PK) of NE is lacking.</p><p><strong>Objective: </strong>In this study, we aimed to describe NE PK in healthy volunteers and the influence of general anesthesia on its PK.</p><p><strong>Methods: </strong>A single-center, cross-over study was conducted in healthy volunteers. The volunteers received a step-up NE dosing scheme (0.04, 0.08, 0.12, 0.16 and 0.20 mcg<sup>-1</sup>/kg<sup>-1</sup>/min<sup>-1</sup>) first in the awake state and then under general anesthesia. General anesthesia was administered using a propofol/remifentanil Eleveld target-controlled infusion. During general anesthesia, a 30-second electrical stimulus was given as surrogate for surgical incision to the volunteers at each dosage step. Blood samples were drawn before the initial dosing and after each dosing step, and plasma NE, propofol and remifentanil concentrations were subsequently determined. A population PK model was developed using non-linear mixed effects modelling. Simulations were conducted to predict the plasma NE concentration in patients at different measured propofol concentrations.</p><p><strong>Results: </strong>A total of 1219 samples were analyzed from 36 volunteers. A two-compartment model with a first-order elimination best described the data. Weight, age, and session effect (awake vs general anesthesia) were identified as relevant covariates on the clearance (CL) of NE. A 10% decrease in NE CL was observed after general anesthesia induction. This difference between sessions is better explained by the measured concentration of propofol, rather than the anticipated impact of cardiac output. The estimated post-stimulation NE concentration is 0.66 nmol/L<sup>-1</sup> (95% CI 0.06-1.20 nmol/L<sup>-1</sup>) lower than the pre-stimulation NE concentration. Model simulation indicates that patients at a higher measured propofol concentration (e.g., 6 mcg/mL<sup>-1</sup>) exhibited higher NE concentrations (95% PI 18.10-43.89 nmol/L<sup>-1</sup>) than patients at a lower measured propofol concentration (e.g., 3 mcg/mL<sup>-1</sup>) (95% PI 16.81-38.91 nmol L<sup>-1</sup>).</p><p><strong>Conclusion: </strong>The NE PK is well described with a two-compartment model with a first-order elimination. NE CL exhibiting a 10% decrease under general anesthesia, with this difference being attributed to the measured concentration of propofol. The impact of stimulation on NE PK under general anesthesia is very limite","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1597-1608"},"PeriodicalIF":4.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11573843/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142496349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding Voriconazole Metabolism: A Middle-Out Physiologically-Based Pharmacokinetic Modelling Framework Integrating In Vitro and Clinical Insights.","authors":"Ayatallah Saleh, Josefine Schulz, Jan-Frederik Schlender, Linda B S Aulin, Amrei-Pauline Konrad, Franziska Kluwe, Gerd Mikus, Wilhelm Huisinga, Charlotte Kloft, Robin Michelet","doi":"10.1007/s40262-024-01434-8","DOIUrl":"10.1007/s40262-024-01434-8","url":null,"abstract":"<p><strong>Background and objective: </strong>Voriconazole (VRC), a broad-spectrum antifungal drug, exhibits nonlinear pharmacokinetics (PK) due to saturable metabolic processes, autoinhibition and metabolite-mediated inhibition on their own formation. VRC PK is also characterised by high inter- and intraindividual variability, primarily associated with cytochrome P450 (CYP) 2C19 genetic polymorphism. Additionally, recent in vitro findings indicate that VRC main metabolites, voriconazole N-oxide (NO) and hydroxyvoriconazole (OHVRC), inhibit CYP enzymes responsible for VRC metabolism, adding to its PK variability. This variability poses a significant risk of therapeutic failure or adverse events, which are major challenges in VRC therapy. Understanding the underlying processes and sources of these variabilities is essential for safe and effective therapy. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) modelling framework that elucidates the complex metabolism of VRC and the impact of its metabolites, NO and OHVRC, on the PK of the parent, leveraging both in vitro and in vivo clinical data in a middle-out approach.</p><p><strong>Methods: </strong>A coupled parent-metabolite PBPK model for VRC, NO and OHVRC was developed in a stepwise manner using PK-Sim<sup>®</sup> and MoBi<sup>®</sup>. Based on available in vitro data, NO formation was assumed to be mediated by CYP2C19, CYP3A4, and CYP2C9, while OHVRC formation was attributed solely to CYP3A4. Both metabolites were assumed to be excreted via renal clearance, with hepatic elimination also considered for NO. Inhibition functions were implemented to describe the complex interaction network of VRC autoinhibition and metabolite-mediated inhibition on each CYP enzyme.</p><p><strong>Results: </strong>Using a combined bottom-up and middle-out approach, incorporating data from multiple clinical studies and existing literature, the model accurately predicted plasma concentration-time profiles across various intravenous dosing regimens in healthy adults, of different CYP2C19 genotype-predicted phenotypes. All (100%) of the predicted area under the concentration-time curve (AUC) and 94% of maximum concentration (C<sub>max</sub>) values of VRC met the 1.25-fold acceptance criterion, with overall absolute average fold errors of 1.12 and 1.14, respectively. Furthermore, all predicted AUC and C<sub>max</sub> values of NO and OHVRC met the twofold acceptance criterion.</p><p><strong>Conclusion: </strong>This comprehensive parent-metabolite PBPK model of VRC quantitatively elucidated the complex metabolism of the drug and emphasised the substantial impact of the primary metabolites on VRC PK. The comprehensive approach combining bottom-up and middle-out modelling, thereby accounting for VRC autoinhibition, metabolite-mediated inhibition, and the impact of CYP2C19 genetic polymorphisms, enhances our understanding of VRC PK. Moreover, the model can be pivotal in designing further","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1609-1630"},"PeriodicalIF":4.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11573852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Age, Sex, Renal Impairment and Hepatic Impairment on the Safety, Pharmacokinetics and Pharmacodynamics of Asundexian.","authors":"Christine Brase, Sebastian Schmitz, Katharina Sommer, Atef Halabi, Friederike Kanefendt","doi":"10.1007/s40262-024-01435-7","DOIUrl":"10.1007/s40262-024-01435-7","url":null,"abstract":"<p><strong>Introduction: </strong>Asundexian is a reversible and selective inhibitor of activated factor XI. It is currently under investigation for the prevention of secondary stroke in at-risk patients; these patients are often characterised by advanced age, impaired organ function and comorbidities. This article summarises results from three Phase I studies that investigated the effects of age and sex (study 1), chronic kidney disease including end-stage kidney disease (ESKD) on dialysis and dialysis-free days (study 2) and Child-Pugh A and B liver disease (study 3) on the safety, pharmacokinetics and pharmacodynamics of a single oral dose of asundexian 25 mg.</p><p><strong>Methods: </strong>Study 1 was a multicentre, randomised, single-blind, placebo-controlled group-stratification design; study 2 was a single-centre, non-randomised, non-placebo-controlled, non-blinded group-stratification design; and study 3 had a non-randomised, non-blinded, non-placebo-controlled group-stratification design.</p><p><strong>Results: </strong>Single doses of asundexian 25 mg were generally well tolerated in all three studies, with no asundexian-related bleeding events or treatment-emergent adverse events of special interest. Point estimates (geometric least squares [LS] means) (90% confidence intervals [CIs]) for the total asundexian area under the plasma concentration-time curve (AUC) for participants aged ≥ 65 to < 75 years versus ≥ 18 to < 45 years and ≥ 75 to ≤ 80 years versus ≥ 18 to < 45 years were 1.257 (1.134-1.393) and 1.288 (1.158-1.433), respectively, and for females versus males, it was 1.084 (0.995-1.182). Point estimates (geometric LS means) (90% CIs) for unbound AUC in participants in estimated glomerular filtration rate (eGFR) categories G2 (60-89 mL/min/1.73 m<sup>2</sup>), G3 (30-59 mL/min/1.73 m<sup>2</sup>) and G4 (15-29 mL/min/1.73 m<sup>2</sup>) versus control were 1.003 (0.698-1.443), 0.791 (0.550-1.138) and 0.882 (0.606-1.285), respectively, and in participants with ESKD on dialysis-free day versus control was 0.597 (0.406-0.877). There was no effect of the dialysis procedure on the pharmacokinetics of asundexian. In participants deemed Child-Pugh class A and Child-Pugh class B, geometric LS means (90% CIs) for unbound AUC were 0.834 (0.597-1.164) and 1.143 (0.810-1.612), respectively, when compared to participants with normal liver function. Activated partial thromboplastin time (aPTT) was assessed as a pharmacodynamic variable of interest. Geometric mean maximum aPTT prolongation as a ratio to baseline after administration of asundexian 25 mg ranged from 1.45 to 1.55 in all age and sex groups, 1.49-1.59 in the control and eGFR G2 to G4 groups, 1.38-1.54 in the control and ESKD groups on dialysis and dialysis-free day and 1.38-1.89 in the healthy control and liver impairment groups.</p><p><strong>Conclusions: </strong>The effects of the investigated intrinsic factors on the exposure of asundexian were small and not considered clinical","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1631-1648"},"PeriodicalIF":4.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11573861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142603591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Milk pH and Fat Content on the Prediction of Milk-to-Plasma Ratio: Knowledge Gap and Considerations for Lactation Study Design and Interpretation.","authors":"Khaled Abduljalil, Muhammad Faisal","doi":"10.1007/s40262-024-01432-w","DOIUrl":"10.1007/s40262-024-01432-w","url":null,"abstract":"<p><strong>Background and objective: </strong>Different empirical lactation models have been published to predict the milk-to-plasma (M/P) ratio of drugs to gain knowledge on the extent of drug distribution to the breastmilk. M/P ratios will likely vary across the lactation period due to differences in physiological milk pH and fat content, which are not routinely reported in clinical lactation pharmacokinetic studies. This work aims to evaluate the sensitivity of two (a theory-based phase distribution and a log-transformed regression) lactation models for M/P prediction at different physiological milk pH and fat content.</p><p><strong>Methods: </strong>A literature search was conducted to collate reported M/P ratios for different drugs and their physicochemical parameters required for the prediction of the M/P ratio. Two distribution models were used for M/P ratio predictions. The M/P ratio of drugs was predicted under the physiological milk pHs of 6.8, 7.0, 7.2, and 7.4 and at of 1%, 3%, and 6% fat content. Calculated M/P ratios were compared with the observed M/P ratios.</p><p><strong>Results: </strong>A total of 200 M/P ratios for 130 compounds (40 acids and 90 bases) were collected from clinical studies and included in the analysis. For both model, precision decreases and bias increases outside the milk pH range 7.0-7.2 and fat contents more than 3%. Significant variability exists in the observed M/P ratios. Both milk pH and fat content are important parameters for model prediction.</p><p><strong>Conclusion: </strong>Calculated M/P ratios are influenced by multiple covariates, including milk pH and fat content. The phase distribution model is less sensitive to these covariates than the log-transformed model, especially for acidic compounds. For complex matrices such as breastmilk, the actual physiological parameters of the sampled milk, at least milk fat and pH, and their distributions are required covariates to improve the prediction outcomes, design lactation pharmacokinetic studies, and inform the potential breastfed infant dose.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1561-1572"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142496336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 Modeling of Total and Unbound Valproic Acid to Evaluate Dosing in Children With and Without Hypoalbuminemia.","authors":"Eleni Karatza, Jaydeep Sinha, Patricia D Maglalang, Andrea Edginton, Daniel Gonzalez","doi":"10.1007/s40262-024-01418-8","DOIUrl":"10.1007/s40262-024-01418-8","url":null,"abstract":"<p><strong>Background and objective: </strong>Valproic acid (VPA) demonstrates nonlinear pharmacokinetics (PK) due to a capacity-limited protein binding, which has potential implications on its total and unbound plasma concentrations, especially during hypoalbuminemia. A physiologically based pharmacokinetic (PBPK) model was developed to assess the nonlinear dose-exposure relationship of VPA with special emphasis on pediatric patients with hypoalbuminemia.</p><p><strong>Methods: </strong>A PBPK model was first developed and evaluated in adults using PK-Sim^® and MoBi^® (v.11) and the scaled to children 1 year and older. The capacity-limited protein binding was characterized by second-order kinetics between VPA and albumin with a 2:1 molar ratio. All drug-specific parameters were informed by literature and optimized using published PK data of VPA. PK simulations were performed in virtual populations with normal and low albumin levels.</p><p><strong>Results: </strong>The reported concentration-time profiles of total and unbound VPA were adequately predicted by the PBPK model across the age and dose range (3-120 mg/kg). The model was able to characterize the nonlinear PK, as the concentration-dependent fraction unbound (f_u) and the related dose-dependent clearance values were well predicted. Simulated steady-state trough concentrations of total VPA were less than dose-proportional and were within the therapeutic drug monitoring range of 50-100 mg/L for doses between 30 and 45 mg/kg per day in children with normal albumin concentrations. However, virtual children with hypoalbuminemia largely failed to achieve the target exposure.</p><p><strong>Conclusion: </strong>The PBPK model helped assess the nonlinear dose-exposure relationship of VPA and the impact of albumin concentrations on the achievement of target exposure.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1435-1448"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11521762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Pharmacokinetic Analysis of Tucatinib in Healthy Participants and Patients with Breast Cancer or Colorectal Cancer.","authors":"Daping Zhang, Adekemi Taylor, Jie Janet Zhao, Christopher J Endres, Ariel Topletz-Erickson","doi":"10.1007/s40262-024-01412-0","DOIUrl":"10.1007/s40262-024-01412-0","url":null,"abstract":"<p><strong>Background and objective: </strong>Tucatinib is a highly selective, oral, reversible, human epidermal growth factor receptor 2 (HER2)-specific tyrosine kinase inhibitor. Tucatinib is approved at a 300-mg twice-daily dose in adults in combination with trastuzumab and capecitabine for advanced HER2-postitive (HER2+) unresectable or metastatic breast cancer and in combination with trastuzumab for RAS wild-type HER2+ unresectable or metastatic colorectal cancer. This study sought to characterize the pharmacokinetics (PK) and assess sources of PK variability of tucatinib in healthy volunteers and in patients with HER2+ metastatic breast or colorectal cancers.</p><p><strong>Methods: </strong>A population pharmacokinetic model was developed based on data from four healthy participant studies and three studies in patients with either HER2+ metastatic breast cancer or metastatic colorectal cancer using a nonlinear mixed-effects modeling approach. Clinically relevant covariates were evaluated to assess their impact on exposure, and overall model performance was evaluated by prediction-corrected visual predictive checks.</p><p><strong>Results: </strong>A two-compartment pharmacokinetic model with linear elimination and first-order absorption preceded by a lag time adequately described tucatinib pharmacokinetic profiles in 151 healthy participants and 132 patients. Tumor type was identified as a significant covariate affecting tucatinib bioavailability and clearance, resulting in a 1.2-fold and 2.1-fold increase in tucatinib steady-state exposure (area under the concentration-time curve) in HER2+ metastatic colorectal cancer and HER2+ metastatic breast cancer, respectively, compared with healthy participants. No other covariates, including mild renal or hepatic impairment, had an impact on tucatinib pharmacokinetics.</p><p><strong>Conclusions: </strong>The impact of statistically significant covariates identified was not considered clinically meaningful. No tucatinib dose adjustments are required based on the covariates tested in the final population pharmacokinetic model.</p><p><strong>Clinical trial registration: </strong>NCT03723395, NCT03914755, NCT03826602, NCT03043313, NCT01983501, NCT02025192.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1477-1487"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11522094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142379184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Human Iron Kinetics Using Stable Iron Isotopic Techniques.","authors":"Nicole U Stoffel, Christophe Zeder, Michael B Zimmermann","doi":"10.1007/s40262-024-01421-z","DOIUrl":"10.1007/s40262-024-01421-z","url":null,"abstract":"<p><p>Stable iron isotope techniques are critical for developing strategies to combat iron deficiency anemia, a leading cause of global disability. There are four primary stable iron isotope methods to assess ferrokinetics in humans. (i) The fecal recovery method applies the principles of a metabolic balance study but offers enhanced accuracy because the amount of iron isotope present in feces can be directly traced back to the labeled dose, distinguishing it from endogenous iron lost in stool from shed intestinal cells. (ii) In the plasma isotope appearance method, plasma samples are collected for several hours after oral dosing to evaluate the rate, quantity, and pattern of iron absorption. Key metrics include the time of peak isotope concentration and the area under the curve. (iii) The erythrocyte iron incorporation method measures iron bioavailability (absorption and erythrocyte iron utilization) from a whole blood sample collected 2 weeks after oral dosing. Simultaneous administration of oral and intravenous tracers allows for separate measurements of iron absorption and iron utilization. These three methods determine iron absorption by measuring tracer concentrations in feces, serum, or erythrocytes after administration of a tracer. In contrast, (iv) in iron isotope dilution, an innovative new approach, iron of natural composition acts as the tracer, diluting an ad hoc modified isotopic signature obtained via prior isotope administration and equilibration with body iron. This technique enables highly accurate long-term studies of iron absorption, loss, and gain. This review discusses the application of these kinetic methods and their potential to address important questions in hematology and iron biology.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1389-1405"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11522093/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selecting the Best Pharmacokinetic Models for a Priori Model-Informed Precision Dosing with Model Ensembling.","authors":"Bram C Agema, Tolra Kocher, Ayşenur B Öztürk, Eline L Giraud, Nielka P van Erp, Brenda C M de Winter, Ron H J Mathijssen, Stijn L W Koolen, Birgit C P Koch, Sebastiaan D T Sassen","doi":"10.1007/s40262-024-01425-9","DOIUrl":"10.1007/s40262-024-01425-9","url":null,"abstract":"<p><strong>Background and objective: </strong>When utilizing population pharmacokinetic (popPK) models for a priori dosage individualization, selecting the best model is crucial to obtain adequate doses. We developed and evaluated several model-selection and ensembling methods, using external evaluation on the basis of therapeutic drug monitoring (TDM) samples to identify the best (set of) models per patient for a priori dosage individualization.</p><p><strong>Methods: </strong>PK data and models describing both hospitalized patients (n = 134) receiving continuous vancomycin (26 models) and patients (n = 92) receiving imatinib in an outpatient setting (12 models) are included. Target attainment of four model-selection methods was compared with standard dosing: the best model based on external validation, uninformed model ensembling, model ensembling using a weighting scheme on the basis of covariate-stratified external evaluation, and model selection using covariates in decision trees that were subsequently ensembled.</p><p><strong>Results: </strong>Overall, the use of PK models improved the proportion of patients exposed to concentrations within the therapeutic window for both cohorts. Relative improvement of proportion on target for best model, unweighted, weighted, and decision trees were - 7.0%, 2.3%, 11.4%, and 37.0% (vancomycin method-development); 23.2%, 7.9%, 15.6%, and, 77.2% (vancomycin validation); 40.7%, 50.0%, 59.5%, and 59.5% (imatinib method-development); and 19.0%, 28.5%, 38.0%, and 23.8% (imatinib validation), respectively.</p><p><strong>Conclusions: </strong>The best (set of) models per patient for a priori dosage individualization can be identified using a relatively small set of TDM samples as external evaluation. Adequately performing popPK models were identified while also excluding poor-performing models. Dose recommendations resulted in more patients within the therapeutic range for both vancomycin and imatinib. Prospective validation is necessary before clinical implementation.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1449-1461"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11522197/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142342872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Pharmacometrics in Advancing the Clinical Research of Antibody-Drug Conjugates: Principles and Modeling Strategies.","authors":"Xiuqi Li, Dan Liu, Shupeng Liu, Mengyang Yu, Xiaofei Wu, Hongyun Wang","doi":"10.1007/s40262-024-01423-x","DOIUrl":"10.1007/s40262-024-01423-x","url":null,"abstract":"<p><p>Antibody-drug conjugates (ADCs) have become a pivotal area in the research and development of antitumor drugs. They provide innovative possibilities for tumor therapy by integrating the tumor-targeting capabilities of monoclonal antibodies with the cytotoxic effect of small molecule drugs. Pharmacometrics, an important discipline, facilitates comprehensive understanding of the pharmacokinetic characteristics of ADCs by integrating clinical trial data through modeling and simulation. However, due to the complex structure of ADCs, their modeling approaches are still unclear. In this review, we analyzed published population pharmacokinetic models for ADCs and classified them into single-analyte, two-analyte, and three-analyte models. We also described the benefits, limitations, and recommendations for each model. Furthermore, we suggested that the development of population pharmacokinetic models for ADCs should be rigorously considered and established based on four key aspects: (1) research objectives; (2) available in vitro and animal data; (3) accessible clinical information; and (4) the capability of bioanalytical methods. This review offered insights to guide the application of pharmacometrics in the clinical research of ADCs, thereby contributing to more effective therapeutic development.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1373-1387"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142342869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Model-Informed Precision Dosing of Tacrolimus: A Systematic Review of Population Pharmacokinetic Models and a Benchmark Study of Software Tools.","authors":"Yannick Hoffert, Nada Dia, Tim Vanuytsel, Robin Vos, Dirk Kuypers, Johan Van Cleemput, Jef Verbeek, Erwin Dreesen","doi":"10.1007/s40262-024-01438-4","DOIUrl":"10.1007/s40262-024-01438-4","url":null,"abstract":"","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1511"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142496334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}