Epidemiology and Biostatistics Unit at the Antoine Lacassagne Center, Nice, France.
Antoine Lacassagne Center, Nice, France.
Brief Bioinform. 2018 Nov 27;19(6):1203-1217. doi: 10.1093/bib/bbx055.
In therapeutic research, the safety and efficacy of pharmaceutical products are necessarily tested on humans via clinical trials after an extensive and expensive preclinical development period. Methodologies such as computer modeling and clinical trial simulation (CTS) might represent a valuable option to reduce animal and human assays. The relevance of these methods is well recognized in pharmacokinetics and pharmacodynamics from the preclinical phase to postmarketing. However, they are barely used and are poorly regarded for drug approval, despite Food and Drug Administration and European Medicines Agency recommendations. The generalization of CTS could be greatly facilitated by the availability of software for modeling biological systems, by clinical trial studies and hospital databases. Data sharing and data merging raise legal, policy and technical issues that will need to be addressed. Development of future molecules will have to use CTS for faster development and thus enable better patient management. Drug activity modeling coupled with disease modeling, optimal use of medical data and increased computing speed should allow this leap forward. The realization of CTS requires not only bioinformatics tools to allow interconnection and global integration of all clinical data but also a universal legal framework to protect the privacy of every patient. While recognizing that CTS can never replace 'real-life' trials, they should be implemented in future drug development schemes to provide quantitative support for decision-making. This in silico medicine opens the way to the P4 medicine: predictive, preventive, personalized and participatory.
在治疗性研究中，药物产品的安全性和疗效必须在经过广泛而昂贵的临床前开发阶段后，通过临床试验在人体上进行测试。计算机建模和临床试验模拟 (CTS) 等方法可能是减少动物和人体试验的有价值选择。这些方法在药代动力学和药效学从临床前阶段到上市后阶段的相关性得到了很好的认可。然而，尽管美国食品和药物管理局和欧洲药品管理局都提出了建议，这些方法在药物批准方面的应用很少，也不受重视。通过建模生物系统的软件的可用性、临床试验研究和医院数据库，可以极大地促进 CTS 的推广。数据共享和数据合并引发了法律、政策和技术问题，需要加以解决。未来分子的开发将不得不使用 CTS 来实现更快的开发，从而更好地管理患者。药物活性建模与疾病建模、充分利用医疗数据和提高计算速度相结合，应该能够实现这一飞跃。实现 CTS 需要不仅有生物信息学工具来允许所有临床数据的互联和全局集成，还需要有一个普遍的法律框架来保护每个患者的隐私。虽然认识到 CTS 永远不能替代“现实生活”试验，但它们应该在未来的药物开发计划中实施，为决策提供定量支持。这种计算机医学为 P4 医学开辟了道路：预测性、预防性、个性化和参与性。
