医疗保健和药物开发中的合成数据:定义,监管框架,问题
Giuseppe Pasculli1, Marco Virgolin2, Puja Myles3
1InSilicoTrials Technologies S.p.A., Trieste, Italy.
CPT: pharmacometrics & systems pharmacology
|April 7, 2025
概括
"合成"一词在临床研究中含糊地用于观察和人工数据. 本次审查澄清了真实/观察数据和人工数据之间的区别,以提高监管清晰度和医疗科学的进步.
科学领域:
- 临床研究方法论临床研究方法论
- 监管科学是一种监管科学.
- 医疗保健中的人工智能 (AI)
背景情况:
- 药物和医疗器械开发中人工智能的监管框架不断发展,需要明确的数据定义.
- "合成"一词的模两可的使用使得观察数据和人工智能生成数据之间的区别变得复杂.
- 对当前文献和监管讨论的批判性评估突出了这一定义挑战.
研究的目的:
- 阐明临床研究中观察 (真实/真实) 数据和人工 (人工智能生成) 数据之间的区别.
- 探索两种数据类型的公用事业,监管立场和未来需求.
- 评估观察和人工数据在推动医学科学和治疗发展方面的潜力.
主要方法:
- 科学出版物和监管文件的批判文献审查.
- 分析与数据源相关的术语的当前含糊不清的使用.
- 对临床试验和人工智能的数据类型的不同观点的评估.
主要成果:
- 对于"合成"数据,使用含糊不清的术语的证据,指的是观察和人工数据.
- 确定监管话语和临床研究的关键考虑因素.
- 识别不同的公用事业和监管挑战观察与人工数据.
结论:
- 在药物开发和医疗设备中,对人工智能来说,观察数据和人工数据之间的明确区分至关重要.
- 需要标准化术语和监管清晰度,以利用这两种数据类型的潜力.
- 需要进一步的研究和监管指导,以优化对观察和人工数据的使用,以促进医学进步.
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