...
首页> 外文期刊>CPT: Pharmacometrics & Systems Pharmacology >Data Digitizing: Accurate and Precise Data Extraction for Quantitative Systems Pharmacology and Physiologically‐Based Pharmacokinetic Modeling
【24h】

Data Digitizing: Accurate and Precise Data Extraction for Quantitative Systems Pharmacology and Physiologically‐Based Pharmacokinetic Modeling

机译:数据数字化:定量系统药理和基于生理学药代理建模的准确和精确的数据提取

获取原文
           

摘要

In quantitative systems pharmacology (QSP) and physiologically‐based pharmacokinetic (PBPK) modeling, data digitizing is a valuable tool to extract numerical information from published data presented as graphs. To quantify their relevance, a literature search revealed a remarkable mean increase of 16% per year in publications citing digitizing software together with QSP or PBPK. Accuracy, precision, confounder influence, and variability were investigated using scaled median symmetric accuracy (ζ), thus finding excellent accuracy (mean ζ?=?0.99%). Although significant, no relevant confounders were found (mean ζ?±?SD circles?=?0.69%?±?0.68% vs. triangles?=?1.3%?±?0.62%). Analysis of 181 literature peak plasma concentration values revealed a considerable discrepancy between reported and post hoc digitized data with 85% having ζ??5%. Our findings suggest that data digitizing is precise and important. However, because the greatest pitfall comes from pre‐existing errors, we recommend always making published data available as raw values.
机译:在定量系统药理学(QSP)和基于生理学的药代动力学(PBPK)建模中,数据数字化是一种有价值的工具,用于从作为图表所呈现的已发布数据中提取数值信息。为了量化它们的相关性,文献搜索显示出在与QSP或PBPK一起引用数字化软件的出版物中每年16%的显着平均增加。使用缩放的中值对称精度(ζ)研究了准确性,精确,混淆的影响和可变性,从而找到了优异的精度(平均值ζ?= 0.99%)。虽然显着,但没有发现相关的混淆(平均值ζ?±?SD圈子?= 0.69%?±0.68%Vs.三角形?=?1.3%?±0.62%)。 181个文献峰血浆浓度值的分析显示报告和HOC数字化数据之间的相当大的差异,具有85%的ζ?>?5%。我们的研究结果表明数据数字化是准确而重要的。但是,由于最伟大的陷阱来自预先存在的错误,我们建议始终使已发布的数据作为原始值。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号