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Integration of biostatistics and pharmacometrics computing platforms for efficient and reproducible PK/PD analysis: A case study
Author(s) -
Ou Ying C.,
Lo Arthur,
Lee Brian,
Liu Phillip,
Kimura Karen,
Eary Charisse,
Hopkins Alan
Publication year - 2013
Publication title -
the journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 116
eISSN - 1552-4604
pISSN - 0091-2700
DOI - 10.1002/jcph.157
Subject(s) - biostatistics , computer science , medicine , epidemiology
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.

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