在COVID-19的BCG疫苗接种III期试验中应用的药理学中的可复制性
Rob C van Wijk1, Laurynas Mockeliunas1, Gerben van den Hoogen2
1Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 75124, Uppsala, Sweden.
Scientific reports
|September 28, 2023
概括
一个可重现的药量计工作流简化了大型COVID-19疫苗试验的数据分析. 这使得实时向数据安全监测委员会 (DSMB) 报告和快速分析成为可能,确保有效监督临床试验.
科学领域:
- 临床药理学 临床药理学
- 数据科学数据科学数据科学
- 生物统计学 生物统计学
背景情况:
- 大规模的临床试验产生复杂的数据集,需要经常报告进行中间分析和数据安全监测委员会 (DSMB) 审查.
- 可复制性和可追溯性对于临床研究中可靠的药量测量数据分析至关重要.
- 及时评估数据对于有效的临床试验管理和决策至关重要.
研究的目的:
- 为大型临床试验开发和实施可重现的药量测量分析工作流程.
- 为了促进反复的数据审查,DSMB报告和快速的药量分析.
- 确保在整个试验生命周期中有效及时地处理和分析数据.
主要方法:
- 开发了一个基于RMarkdown的药量计处理脚本,用于自动化报告生成.
- 实施了41个临床试验数据集的代数据传输和审查过程.
- 利用源数据创建分析数据集 (NONMEM格式) 并支持模型脚本开发.
主要成果:
- 自动报告被生成并发送到DSMB在三天内数据切断,使实时进度监控.
- 主要终点分析是在数据锁定和解盲后三天完成的.
- 两周后,完成了二次终点分析,证明了工作流效率.
结论:
- 在大型临床试验环境中,开发的药量计工作流显著提高了效率,及时性和可重复性.
- 临床,数据管理和药量测量团队之间的密切合作是工作流程成功的关键.
- 工作流提供了一个强大的模型来管理复杂的数据集,并支持在大型临床试验中的决策.
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