CPT: Pharmacometrics & Systems Pharmacology最新文献

{"title":"Predicting Residual 21-Hydroxylase Enzymatic Activity in Pediatric and Adult Congenital Adrenal Hyperplasia Patients: Towards Individualized Therapy.","authors":"Davide Bindellini, Robin Michelet, Yersultan Mirasbekov, Qizong Lao, Charles Sukin, Wilhelm Huisinga, Deborah P Merke, Charlotte Kloft","doi":"10.1002/psp4.70086","DOIUrl":"https://doi.org/10.1002/psp4.70086","url":null,"abstract":"<p><p>Congenital adrenal hyperplasia (CAH) is a genetic disorder characterized by impaired cortisol production and consequent elevated adrenocorticotropic hormone (ACTH): CAH patients often require lifelong hydrocortisone therapy. Disease severity reflects residual 21-hydroxylase enzyme activity, crucial for cortisol synthesis. Accurate assessment of residual enzymatic activity is key to developing individualized dosing. This study aimed to estimate enzymatic activity using a previously developed healthy adult ACTH-cortisol model and to evaluate the potential for individualized therapy. Leveraging ACTH (n = 62) and cortisol (n = 66) concentrations from 51 (20 pediatric, 31 adult) untreated CAH patients, and assuming maximal cortisol production (E_max) = 100% in healthy individuals, residual enzymatic activity was estimated as an E_max scaling factor. To assess proof-of-concept feasibility of individualized therapy, simulations of individual untreated 24-h ACTH and cortisol profiles were performed, and for one patient hydrocortisone dosing regimens (15-25 mg/day in 3 doses, q4h or q6h) were compared to simulated untreated and healthy profiles. The original model failed to capture elevated ACTH in severe CAH and was refined to predict observed data across all patients. Using the refined model, estimated enzymatic activity was higher than in vitro values for adults, while children under 13 years old showed 31.6% of adult enzymatic activity. Shortening dosing intervals had a greater impact on reducing the patient's ACTH overexposure than increasing the daily dose. This model-based approach captured in vivo endogenous cortisol production and enabled simulation-based evaluation of individualized therapy in adults. In children, further validation of the ACTH-cortisol dynamics model and enzymatic activity estimates is needed to evaluate individualized therapy.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating Trastuzumab-Doxorubicin Cardiotoxicity With Multiscale Quantitative Systems Toxicology and PBPK-Toxicodynamic Predictive Modeling Framework.","authors":"Sijia Yu, Hardik Mody, Tanaya R Vaidya, Leonid Kagan, Sihem Ait-Oudhia","doi":"10.1002/psp4.70087","DOIUrl":"https://doi.org/10.1002/psp4.70087","url":null,"abstract":"<p><p>Doxorubicin (DOX) and trastuzumab (TmAb) are widely used to treat HER2-positive breast cancer (BC), as monotherapies and in combination (DOX + TmAb). While highly effective, their combined use significantly increases the risk of irreversible cardiotoxicity, posing a major clinical concern. B-type natriuretic peptide (BNP) and NT-proBNP are serum biomarkers of early cardiotoxicity. Understanding the dynamic relationship between these biomarkers and intracellular apoptosis pathways is key to predicting and mitigating treatment-induced cardiotoxicity. This study aims to extend a previously developed multiscale modeling framework of DOX-induced cardiotoxicity to include DOX + TmAb combinatorial effects and to predict clinical outcomes. Human cardiomyocytes were exposed to different concentrations of DOX, TmAb, DOX + TmAb, or control for 96 h. Time-course data for caspase-9 and -3 expression, cell viability, and BNP were collected and used to develop mathematical models for intracellular apoptosis-signaling protein dynamics, cardiomyocyte viability, and cardiomyocyte injury biomarkers. The cellular model was scaled up to humans with a previously published TmAb human PBPK model using NT-proBNP data and evaluated with left ventricular ejection fraction measurements. The quantitative systems toxicology (QST) model successfully captured in vitro dynamic data across treatment groups. Caspase-3 drove the cardiomyocyte-death model. Multiplicative and additive relationships characterized drug interactions to reflect the enhanced cardiotoxicity seen with DOX + TmAb. The predicted clinical BNP changes were consistent with LVEF dynamics from BC patients treated with TmAb. The QST-PBPK model bridges in vitro experimental findings with clinical cardiotoxicity outcomes. It provides a predictive tool for cardiotoxicity, aiding potentially in dose optimization and clinical monitoring for HER2-positive BC patients.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Mechanistic Modeling and Simulation Methodologies on Product-Specific Guidance Development for Non-Orally Administered Drug Products","authors":"Steven G. Chopski,&nbsp;Ross L. Walenga,&nbsp;Ming-Liang Tan,&nbsp;Khondoker Alam,&nbsp;Andrew Babiskin,&nbsp;Lanyan Fang,&nbsp;Eleftheria Tsakalozou","doi":"10.1002/psp4.70078","DOIUrl":"10.1002/psp4.70078","url":null,"abstract":"<p>The U.S. Food and Drug Administration (FDA) publishes product-specific guidances (PSGs), with bioequivalence (BE) recommendations for prospective generics. Developing BE recommendations for non-orally administered drug products including long-acting injectables (LAI), orally inhaled drug products, and drugs applied locally to the skin, ophthalmic, and nasal routes may be challenging because conventional BE methods and considerations for orally administered drug products may not apply. Mechanistic modeling approaches such as physiologically based pharmacokinetic (PBPK) models or computational fluid dynamics (CFD) models are used for the development of BE methods and BE assessment standards in PSGs for non-orally administered drug products, as evidenced by cases provided here. This manuscript discusses in silico methodologies that support PSG development for non-orally administered drug products through the model-integrated evidence paradigm. Specifically for orally inhaled drug products, we highlight modeling and simulation (M&amp;S) recommendations that have occurred in one new PSG that was published for formoterol fumarate; glycopyrrolate inhalation metered aerosol in February 2024 and referred to in 16 other PSGs with different active pharmaceutical ingredients and device types, such that M&amp;S approaches may be optionally used to provide insight on regional drug delivery and support BE assessments. For drug products applied to the skin, we focus on three successful case studies where PBPK models were used to support revised PSG recommendations with reduced need for ex vivo and human studies. Ophthalmic products, LAI, and nasal products illustrated advancements in M&amp;S methodologies that may be potentially used for the development of new or revised PSG recommendations.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 9","pages":"1421-1430"},"PeriodicalIF":3.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12439276/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State-of-the-Art on Model-Informed Drug Development Approaches for Pediatric Rare Diseases.","authors":"Rajesh Krishna, Amitava Mitra, Matthew L Zierhut, Lilly East, Chandra Durairaj","doi":"10.1002/psp4.70083","DOIUrl":"https://doi.org/10.1002/psp4.70083","url":null,"abstract":"<p><p>Pediatric rare diseases present unique challenges for drug development due to small patient populations, ethical constraints on clinical trial design, and limited prospectively defined natural history data. Model-Informed Drug Development (MIDD) has emerged as a powerful paradigm to address these challenges by leveraging quantitative methods to enhance decision-making across all stages of drug development. This paper reviews the state-of-the-art MIDD approaches being applied to pediatric rare disease therapeutics, including the traditional pharmacometrics methodologies of population pharmacokinetic/pharmacodynamic (PK/PD) modeling, physiologically based pharmacokinetic (PBPK) modeling, disease progression modeling, and more future-facing Bayesian trial designs, and real-world data integration. We highlight how these methods facilitate dose optimization, support extrapolation from adult or other pediatric data, and enable more efficient and ethical clinical trial strategies. Case studies from recent regulatory submissions illustrate the growing acceptance of MIDD in pediatric rare disease contexts. Finally, we discuss the technological and regulatory advances driving this field forward, as well as current limitations and future opportunities for expanding the impact of MIDD on accelerating safe and effective treatments for children with rare diseases.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Isavuconazole and Calcium Channel Blocker for Invasive Fungal Disease Accompanied With Hypertension: Evidence From the FAERS and PBPK/PD Model","authors":"Jianxing Zhou,&nbsp;Bo Xiao,&nbsp;Zipeng Wei,&nbsp;Mengting Jia,&nbsp;Xin Luo,&nbsp;Huimin Wei,&nbsp;Xiaohan Zhang,&nbsp;Maobai Liu,&nbsp;Yifan Zhang,&nbsp;Xuemei Wu","doi":"10.1002/psp4.70056","DOIUrl":"10.1002/psp4.70056","url":null,"abstract":"<p>Patients with invasive fungal disease (IFD) frequently present with hypertension, necessitating polypharmacy and increasing the risk of drug–drug interactions (DDIs). This study evaluated the safety of combining isavuconazole (ISA), a triazole antifungal drug (TAD), and calcium channel blockers (CCBs) in hypertensive patients with IFD using the FDA Adverse Event Reporting System (FAERS) and physiologically based pharmacokinetic/pharmacodynamic models. FAERS data on hypertension and hypotension involving TADs from 2015 (first quarter) to 2023 (fourth quarter) were used. Disproportionality analysis was performed using the reporting odds ratio (ROR) and information component (IC) methods. DDI models were developed and validated using the Simcyp simulator and in vitro experiments. Dose regimen evaluation and optimization were conducted using the established DDI model. ISA was not associated with hypertension or hypotension. Nifedipine and amlodipine were frequently associated with hypotension induced by CYP3A4 inhibition. The simulated regimens showed that ISA doubled plasma exposure to nifedipine immediate-release (IR) and controlled-release (CR) formulations, increased the maximum concentration by 1.51-fold for nifedipine IR and 2.15-fold for nifedipine CR, and caused a 3.5- to 4.09-fold increase in maximum systolic blood pressure reduction for nifedipine IR. The effects of amlodipine were negligible. Dose optimization, such as halving the nifedipine dose, effectively managed the overexposure. ISA appears safe for use in hypertensive patients with IFD when combined with CCBs, with minimal risk of significant DDIs. Personalized dosing adjustments can mitigate DDI risk. These findings support the clinical use of ISA to enhance dosing precision and patient safety.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 8","pages":"1359-1369"},"PeriodicalIF":3.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ascpt.onlinelibrary.wiley.com/doi/epdf/10.1002/psp4.70056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanism-Based Modeling Approaches to Quantify the Effect of Immunogenicity on the Pharmacokinetics of Therapeutic Proteins in Drug Development","authors":"Paridhi Gupta,&nbsp;Josiah T. Ryman,&nbsp;Vibha Jawa,&nbsp;Bernd Meibohm","doi":"10.1002/psp4.70080","DOIUrl":"10.1002/psp4.70080","url":null,"abstract":"<p>Therapeutic protein administration in both preclinical and clinical studies can result in the formation of anti-drug antibodies against the therapeutic protein. Anti-drug antibody formation may alter the pharmacokinetics of the therapeutic protein, reduce its plasma concentrations, increase exposure variability, and may lead to a loss of efficacy and adverse events. In an effort to quantitatively understand the effect of anti-drug antibodies on the concentration-time profile of a therapeutic protein, as well as develop effective strategies to mitigate its impact in the preclinical and clinical development of therapeutic proteins, mathematical models have been developed to characterize the therapeutic protein pharmacokinetics and its modulation by anti-drug antibodies in vivo. Here, we review several different mechanism-based modeling frameworks, summarize their approaches to predict immunogenicity effects, and explore the merits and limitations of each model.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 9","pages":"1431-1441"},"PeriodicalIF":3.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12439280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Modeling of Digital-Motor and Clinician-Reported Outcomes Using Item Response Theory: Towards Powerful Trials for Rare Neurological Diseases.","authors":"Alzahra Hamdan, Andreas Traschütz, Lukas Beichert, Xiaomei Chen, Cynthia Gagnon, Bart P van de Warrenburg, Filippo M Santorelli, Nazlı Başak, Giulia Coarelli, Rita Horvath, Stephan Klebe, Rebecca Schüle, Andrew C Hooker, Matthis Synofzik, Mats O Karlsson","doi":"10.1002/psp4.70081","DOIUrl":"https://doi.org/10.1002/psp4.70081","url":null,"abstract":"<p><p>Robust and highly sensitive outcomes are crucial for small trials in rare diseases. Combining different outcome types might improve sensitivity to identify disease severity and progression, yet innovative methodologies are scarce. Here we develop an Item Response Theory framework that allows integrated modeling of both continuous and categorical outcomes (ccIRT). With degenerative ataxias, a group of rare neurological coordination diseases, as a showcase, we developed a ccIRT model integrating two ataxia outcome types: a clinician-reported outcome (Scale for the Assessment and Rating of Ataxia; SARA; categorical data) and digital-motor outcomes for gait and limb coordination (continuous data). The ccIRT model leveraged data from 331 assessments from a natural history study for spastic ataxias. The model describes SARA items and digital-motor outcomes data as functions of a common underlying ataxia severity construct, evaluating 9 gait and 17 limb coordination digital-motor measures for their ability to add to SARA in estimating individual ataxia severity levels. Based on our proposed workflow for assessing digital-motor outcomes in ccIRT models, the final model selected three digital gait and three limb coordination measures, reducing average uncertainty in ataxia severity estimates by 49% (10% SD) compared to the SARA-only IRT model. Trial simulations showed a 49% and 61% reduction in sample sizes needed to detect disease-modifying effects in two genotypes. Overall, our ccIRT framework for combining multiple outcome domains, even of different variable types, facilitates a more precise estimation of disease severity and a higher power, which is particularly relevant for rare diseases with inherently small and short trials. Trial Registration: ClinicalTrials.gov: NCT04297891.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disease Modeling and External Model Evaluation Through Clinical Data Sharing Platform for HR+/HER2− Breast Cancer","authors":"Kenta Yoshida,&nbsp;René Bruno,&nbsp;Pascal Chanu","doi":"10.1002/psp4.70073","DOIUrl":"10.1002/psp4.70073","url":null,"abstract":"<p>Predictive models for disease progression are valuable for clinical trial design and interpretation; however, suitable data are needed for the development of such models. This study aimed to develop a Tumor Growth Inhibition-Overall Survival (TGI-OS) model for hormone receptor-positive (HR+)/human epidermal growth factor receptor 2 negative (HER2−) breast cancer using clinical trial data available through Vivli, a clinical trial data sharing platform. The CONFIRM study (Phase 3 study comparing fulvestrant 250 vs. 500 mg) was used for model development, and the PALOMA-3 and SANDPIPER Phase 3 studies (palbociclib and taselisib) were used for external model qualifications. Longitudinal tumor size profiles were first analyzed with the TGI model. The TGI-OS model, a parametric model linking TGI metrics and baseline predictors of survival outcomes, was then developed using data from the CONFIRM study and showed successful internal qualification, including the prediction of the survival difference between two dose groups. The TGI-OS model showed large underestimation for the OS for PALOMA-3; nevertheless, the predicted treatment effect (hazard ratio of OS) was in good agreement with the observation for both studies, suggesting its potential as a tool to support drug development decisions. While integrating shared clinical trial data from multiple sources, facilitated by platforms like Vivli, is crucial for advancing predictive modeling efforts, caution should be exercised when such models are applied for new studies, especially when there are breakthroughs in the treatment landscape.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 9","pages":"1442-1448"},"PeriodicalIF":3.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12439286/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144648720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Verification of Virtual Population Models for Predicting Drug Pharmacokinetics in Ethnic North American Populations.","authors":"Udoamaka Ezuruike, Jean Dinh, Eman El-Khateeb, Alex Blenkinsop, Oliver Hatley, Iain Gardner","doi":"10.1002/psp4.70068","DOIUrl":"https://doi.org/10.1002/psp4.70068","url":null,"abstract":"<p><p>Ethnic variabilities can affect the outcome of drug pharmacokinetics (PK) and drug-drug interactions (DDI). This work aimed to develop four North American (NA) sub-populations: White, African American, Asian American, and Hispanic_Latino suitable for physiologically based pharmacokinetic (PBPK) modeling and simulations. Demographic data and tissue weight/volume, blood flows, cardiac output, plasma protein levels, hematocrit, enzyme and transporter abundances/frequencies, serum creatinine, glomerular filtration rate, and gastrointestinal transit times for the different populations were collated. Equations describing various covariate relationships for these physiological parameters were developed for each ethnicity. Some key population differences that can affect drug PK were higher CYP3A5 and OATP1B1 population mean abundances for African Americans and lower CYP3A4 and OATP1B1 population mean abundances for Asian Americans. The most common CYP2C9 alleles in the White as well as the Asian populations are the *1, *2, and *3 alleles. However, additional lower-activity alleles (*5, *6, *8, and *11) were also shown to occur among the African Americans and Hispanic_Latino subjects. Clinical studies reporting population specific PK profiles (6 studies) or results from a mixed NA population (14 studies including 6 DDI studies) were simulated, and the simulated data were within two-fold of the observed data. PBPK simulations using the 4 NA population files and repaglinide as a probe compound predicted significant differences in the drug exposure for the Asians, African Americans, and White subjects. In conclusion, the developed population files can aid drug development for specific subgroups of the diverse NA population by accounting for variabilities in drug kinetics and DDI consequences.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144658637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical Verification of Tucuxi, a Promising Bayesian Adaptation Tool for Model-Informed Precision Dosing.","authors":"Anne Ravix, Annie E Cathignol, Thierry Buclin, Chantal Csajka, Monia Guidi, Yann Thoma","doi":"10.1002/psp4.70077","DOIUrl":"https://doi.org/10.1002/psp4.70077","url":null,"abstract":"<p><p>Tucuxi, a Swiss-developed Model-Informed Precision Dosing (MIPD) software, aims to support clinical dosage decision-making to achieve therapeutic concentration targets. This study assessed its predictive accuracy compared to NONMEM, a gold-standard tool for Bayesian PK predictions. A panel of models was created to mimic various pharmacokinetic scenarios following oral, bolus, or intravenous administration. For each scenario, a virtual population of 4000 patients receiving doses ranging from 10 to 120 mg every 24 h was created. Sparse and rich profiles were simulated, with either one or four samples taken per patient. Tucuxi and NONMEM predicted concentrations at sampling times, trough (C_min) and peak (C_max) concentrations, and area under the curve (AUC_0-24h) were compared by calculating their relative differences, mean prediction error (MPE) and relative root mean square error (RMSE). The bioequivalence criterion was additionally applied to compare AUC_0-24h, C_min, and C_max. All the outcomes predicted by Tucuxi closely matched those predicted by NONMEM. A median of 99.8% of predicted concentrations at sampling times presented relative errors smaller than 0.1%. For all outcomes predicted, MPE and relative RMSE were 0% (-0.09, 0.07) and 0.82% (0%, 18.79%) respectively. The bioequivalence criterion, calculated for AUC_0-24h, C_min, and C_max, was verified for all models, with median values of 100%. This project highlights Tucuxi's excellent predictive accuracy compared to NONMEM, demonstrating its reliability and potential for adoption in clinical practice.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144658638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}