Khalil Ben Hassine, Youssef Daali, Yvonne Gloor, Tiago Nava, Yves Théorêt, Maja Krajinovic, Henrique Bittencourt, Chakradhara Rao Satyanarayana Uppugunduri, Marc Ansari
{"title":"基于模型的取样计划优化,实现对小儿患者每日一次和每日四次布舒凡的精确给药。","authors":"Khalil Ben Hassine, Youssef Daali, Yvonne Gloor, Tiago Nava, Yves Théorêt, Maja Krajinovic, Henrique Bittencourt, Chakradhara Rao Satyanarayana Uppugunduri, Marc Ansari","doi":"10.1097/FTD.0000000000001217","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Therapeutic drug monitoring (TDM) is crucial in optimizing the outcomes of hematopoietic stem cell transplantation by guiding busulfan (Bu) dosing. Limited sampling strategies show promise for efficiently adjusting drug doses. However, comprehensive assessments and optimization of sampling schedules for Bu TDM in pediatric patients are limited. We aimed to establish optimal sampling designs for model-informed precision dosing (MIPD) of once-daily (q24h) and 4-times-daily (q6h) Bu administration in pediatric patients.</p><p><strong>Methods: </strong>Simulated data sets were used to evaluate the population pharmacokinetic model-based Bayesian estimation of the area under the concentration-time curve (AUC) for different limited sampling strategy designs. The evaluation was based on the mean prediction error for accuracy and root mean square error for precision. These findings were validated using patient-observed data. In addition, the MIPD protocol was implemented in the Tucuxi software, and its performance was assessed.</p><p><strong>Results: </strong>Our Bayesian estimation approach allowed for flexible sampling times while maintaining mean prediction error within ±5% and root mean square error below 10%. Accurate and precise AUC0-24h and cumulative AUC estimations were obtained using 2-sample and single-sample schedules for q6h and q24h dosing, respectively. TDM on 2 separate days was necessary to accurately estimate cumulative exposure, especially in patients receiving q6h Bu. Validation with observed patient data confirmed the precision of the proposed limited sampling scenarios. Implementing the MIPD protocol in Tucuxi software yielded reliable AUC estimations.</p><p><strong>Conclusions: </strong>Our study successfully established precise limited sampling protocols for MIPD of Bu in pediatric patients. Our findings underscore the importance of TDM on at least 2 occasions to accurately achieve desired Bu exposures. The developed MIPD protocol and its implementation in Tucuxi software provide a valuable tool for routine TDM in pediatric hematopoietic stem cell transplantation.</p>","PeriodicalId":23052,"journal":{"name":"Therapeutic Drug Monitoring","volume":" ","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11554249/pdf/","citationCount":"0","resultStr":"{\"title\":\"Simulation-Based Optimization of Sampling Schedules for Model-Informed Precision Dosing of Once-Daily and 4-Times-Daily Busulfan in Pediatric Patients.\",\"authors\":\"Khalil Ben Hassine, Youssef Daali, Yvonne Gloor, Tiago Nava, Yves Théorêt, Maja Krajinovic, Henrique Bittencourt, Chakradhara Rao Satyanarayana Uppugunduri, Marc Ansari\",\"doi\":\"10.1097/FTD.0000000000001217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Therapeutic drug monitoring (TDM) is crucial in optimizing the outcomes of hematopoietic stem cell transplantation by guiding busulfan (Bu) dosing. Limited sampling strategies show promise for efficiently adjusting drug doses. However, comprehensive assessments and optimization of sampling schedules for Bu TDM in pediatric patients are limited. We aimed to establish optimal sampling designs for model-informed precision dosing (MIPD) of once-daily (q24h) and 4-times-daily (q6h) Bu administration in pediatric patients.</p><p><strong>Methods: </strong>Simulated data sets were used to evaluate the population pharmacokinetic model-based Bayesian estimation of the area under the concentration-time curve (AUC) for different limited sampling strategy designs. The evaluation was based on the mean prediction error for accuracy and root mean square error for precision. These findings were validated using patient-observed data. In addition, the MIPD protocol was implemented in the Tucuxi software, and its performance was assessed.</p><p><strong>Results: </strong>Our Bayesian estimation approach allowed for flexible sampling times while maintaining mean prediction error within ±5% and root mean square error below 10%. Accurate and precise AUC0-24h and cumulative AUC estimations were obtained using 2-sample and single-sample schedules for q6h and q24h dosing, respectively. TDM on 2 separate days was necessary to accurately estimate cumulative exposure, especially in patients receiving q6h Bu. Validation with observed patient data confirmed the precision of the proposed limited sampling scenarios. Implementing the MIPD protocol in Tucuxi software yielded reliable AUC estimations.</p><p><strong>Conclusions: </strong>Our study successfully established precise limited sampling protocols for MIPD of Bu in pediatric patients. Our findings underscore the importance of TDM on at least 2 occasions to accurately achieve desired Bu exposures. 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Simulation-Based Optimization of Sampling Schedules for Model-Informed Precision Dosing of Once-Daily and 4-Times-Daily Busulfan in Pediatric Patients.
Background: Therapeutic drug monitoring (TDM) is crucial in optimizing the outcomes of hematopoietic stem cell transplantation by guiding busulfan (Bu) dosing. Limited sampling strategies show promise for efficiently adjusting drug doses. However, comprehensive assessments and optimization of sampling schedules for Bu TDM in pediatric patients are limited. We aimed to establish optimal sampling designs for model-informed precision dosing (MIPD) of once-daily (q24h) and 4-times-daily (q6h) Bu administration in pediatric patients.
Methods: Simulated data sets were used to evaluate the population pharmacokinetic model-based Bayesian estimation of the area under the concentration-time curve (AUC) for different limited sampling strategy designs. The evaluation was based on the mean prediction error for accuracy and root mean square error for precision. These findings were validated using patient-observed data. In addition, the MIPD protocol was implemented in the Tucuxi software, and its performance was assessed.
Results: Our Bayesian estimation approach allowed for flexible sampling times while maintaining mean prediction error within ±5% and root mean square error below 10%. Accurate and precise AUC0-24h and cumulative AUC estimations were obtained using 2-sample and single-sample schedules for q6h and q24h dosing, respectively. TDM on 2 separate days was necessary to accurately estimate cumulative exposure, especially in patients receiving q6h Bu. Validation with observed patient data confirmed the precision of the proposed limited sampling scenarios. Implementing the MIPD protocol in Tucuxi software yielded reliable AUC estimations.
Conclusions: Our study successfully established precise limited sampling protocols for MIPD of Bu in pediatric patients. Our findings underscore the importance of TDM on at least 2 occasions to accurately achieve desired Bu exposures. The developed MIPD protocol and its implementation in Tucuxi software provide a valuable tool for routine TDM in pediatric hematopoietic stem cell transplantation.
期刊介绍:
Therapeutic Drug Monitoring is a peer-reviewed, multidisciplinary journal directed to an audience of pharmacologists, clinical chemists, laboratorians, pharmacists, drug researchers and toxicologists. It fosters the exchange of knowledge among the various disciplines–clinical pharmacology, pathology, toxicology, analytical chemistry–that share a common interest in Therapeutic Drug Monitoring. The journal presents studies detailing the various factors that affect the rate and extent drugs are absorbed, metabolized, and excreted. Regular features include review articles on specific classes of drugs, original articles, case reports, technical notes, and continuing education articles.