Ying C Ou, Arthur Lo, Brian Lee, Phillip Liu, Karen Kimura, Charisse Eary, Alan Hopkins
{"title":"Integration of biostatistics and pharmacometrics computing platforms for efficient and reproducible PK/PD analysis: a case study.","authors":"Ying C Ou, Arthur Lo, Brian Lee, Phillip Liu, Karen Kimura, Charisse Eary, Alan Hopkins","doi":"10.1002/jcph.157","DOIUrl":null,"url":null,"abstract":"<p><p>Results of pharmacometric analyses influence high-level decisions such as clinical trial design, drug approval, and labeling. Key challenges for timely delivery of pharmacometric analyses are the data assembly process and tracking and documenting the modeling process and results. Since clinical efficacy and safety data typically reside in the biostatistics computing area, an integrated computing platform for pharmacometric and biostatistical analyses would be ideal. A case study is presented integrating a pharmacometric modeling platform into an existing statistical computing environment (SCE). The feasibility and specific configurations of running common PK/PD programs such as NONMEM and R inside of the SCE are provided. The case study provides an example of an integrated repository that facilitates efficient data assembly for pharmacometrics analyses. The proposed platform encourages a good pharmacometrics working practice to maintain transparency, traceability, and reproducibility of PK/PD models and associated data in supporting drug development and regulatory decisions. </p>","PeriodicalId":48908,"journal":{"name":"Journal of Clinical Pharmacology","volume":"53 11","pages":"1112-20"},"PeriodicalIF":2.9000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/jcph.157","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/jcph.157","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2013/8/29 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Results of pharmacometric analyses influence high-level decisions such as clinical trial design, drug approval, and labeling. Key challenges for timely delivery of pharmacometric analyses are the data assembly process and tracking and documenting the modeling process and results. Since clinical efficacy and safety data typically reside in the biostatistics computing area, an integrated computing platform for pharmacometric and biostatistical analyses would be ideal. A case study is presented integrating a pharmacometric modeling platform into an existing statistical computing environment (SCE). The feasibility and specific configurations of running common PK/PD programs such as NONMEM and R inside of the SCE are provided. The case study provides an example of an integrated repository that facilitates efficient data assembly for pharmacometrics analyses. The proposed platform encourages a good pharmacometrics working practice to maintain transparency, traceability, and reproducibility of PK/PD models and associated data in supporting drug development and regulatory decisions.
期刊介绍:
The Journal of Clinical Pharmacology (JCP) is a Human Pharmacology journal designed to provide physicians, pharmacists, research scientists, regulatory scientists, drug developers and academic colleagues a forum to present research in all aspects of Clinical Pharmacology. This includes original research in pharmacokinetics, pharmacogenetics/pharmacogenomics, pharmacometrics, physiologic based pharmacokinetic modeling, drug interactions, therapeutic drug monitoring, regulatory sciences (including unique methods of data analysis), special population studies, drug development, pharmacovigilance, womens’ health, pediatric pharmacology, and pharmacodynamics. Additionally, JCP publishes review articles, commentaries and educational manuscripts. The Journal also serves as an instrument to disseminate Public Policy statements from the American College of Clinical Pharmacology.