The last two decades have witnessed profound changes in how advanced computational tools can help leverage tons of data to improve our knowledge, and ultimately reduce cost and increase productivity in drug development. Pharmacometrics has demonstrated its impact through model-informed drug development (MIDD) approaches. It is now an indispensable component throughout the whole continuum of drug discovery, development, regulatory review, and approval. Today, applications of pharmacometrics are common in designing better trials and accelerating evidence-based decisions. Newly emerging technologies, especially those from data and computer sciences, are being integrated with existing computational tools used in the pharmaceutical industry at a remarkably fast pace. The new challenges faced by the pharmacometrics community are not what or how to contribute, but which optimal MIDD strategy should be adopted to maximize its value in the decision-making process. While we are embracing new innovative approaches and tools, this article discusses how a variety of existing modeling tools, with differentiated advantages and focus, can work in concert to inform drug development.

中文翻译：

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定量药理学在药物开发中的应用


过去二十年见证了先进的计算工具如何帮助利用大量数据来改进我们的知识，并最终降低成本并提高药物开发的生产力的深刻变化。定量药理学通过模型引导的药物开发 （MIDD） 方法证明了其影响。它现在是贯穿药物发现、开发、监管审查和批准的整个过程中不可或缺的组成部分。如今，定量药理学在设计更好的试验和加速循证决策方面很常见。新兴技术，尤其是来自数据和计算机科学的技术，正在以非常快的速度与制药行业使用的现有计算工具集成。定量药理学界面临的新挑战不是贡献什么或如何贡献，而是应该采用哪种最佳 MIDD 策略，以在决策过程中最大限度地发挥其价值。虽然我们正在采用新的创新方法和工具，但本文讨论了各种具有差异化优势和重点的现有建模工具如何协同工作，为药物开发提供信息。