生物分析
广告
控制(管理)
数据科学
计算机科学
色谱法
质量(理念)
医学
药代动力学
药理学
化学
哲学
认识论
人工智能
作者
Stephen Keller,Jorge Quiroz,Dave Christopher,Enaksha Wickremsinhe,Wanping Geng,Glen Hawthorne,Christopher James,Yvonne Katterle,Wenkui Li,Guowen Liu,Andrew P. Mayer,Martin Paton,Joseph Pav,Julian Potter,James M. Vergis,Jonathan Wang,Lucas Westcott‐Baker,Eric Woolf,Yongjun Xue
出处
期刊:Bioanalysis
[Future Science Ltd]
日期:2021-02-01
卷期号:13 (3): 135-145
被引量:1
标识
DOI:10.4155/bio-2020-0265
摘要
The use of quality control (QC) samples in bioanalysis is well established and consistent with regulatory guidance. However, a systematic evaluation of whether QC samples serve the intended purpose of improving data quality has not been undertaken. The Translational and ADME Sciences Leadership Group (TALG) of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) conducted an evaluation to assess whether closer agreement is observed when comparing pharmacokinetic data from two passed runs, than when comparing data from failed and passed (retest) runs. Analysis of data collected across organizations, molecular types and analytical platforms, revealed that bioanalytical methods are very reproducible; and that QC samples improve the overall quality of pharmacokinetic concentration data and justifies their continued use.
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