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合成生物医学数据的生成,以支持在的临床试验
Alena Simalatsar1,2,3
1Institute of Systems Engineering, University of Applied Sciences and Arts - Western Switzerland, Sion, Switzerland.
Frontiers in big data
|September 1, 2023
概括
合成数据生成对于生物医学研究至关重要,特别是对于罕见疾病和新型治疗方法. 它支持道德和成本效益的内临床试验 (ISCT),解决数据隐私问题,减少对传统动物试验的依赖.
科学领域:
- 生物医学数据科学是生物医学数据科学.
- 翻译研究是翻译研究.
- 计算生物学是一种计算生物学.
背景情况:
- 数据隐私问题限制了有价值的生物医学数据的共享.
- 传统的临床试验是昂贵的,耗时的,并且在道德上具有挑战性.
- 现有的数据匿名化技术有助于一些数据共享.
研究的目的:
- 探索合成生物医学数据生成的必要性和方法.
- 审查全球倡议,促进计算机模拟在研究.
- 在动物实验中支持3R原则 (取代,减少,改进).
主要方法:
- 全球关于研究中的计算机模拟倡议的概述.
- 介绍了用于智能合成生物医学数据生成的方法.
- 讨论在体内临床试验 (ISCT) 的虚拟患者队列.
主要成果:
- 合成数据生成为罕见疾病和新型治疗方法的传统方法提供了可行的替代方案.
- 计算机建模和模拟越来越多地被像FDA这样的监管机构所承认.
- 创建虚拟队列的方法允许进行全面的In Silico临床试验.
结论:
- 智能数据生成,特别是合成数据,对于推动生物医学研究至关重要.
- 基于合成数据的In Silico临床试验 (ISCT) 为高效和道德的研究提供了一个有前途的途径.
- 进一步开发和采用这些技术可以加速医疗创新.
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