Gu Qifei, Wu Huichao, Sui Xue, Zhang Xiaodan, Liu Yongchao, Feng Wei, Zhou Rui, Du Shouying
College of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China.
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China.
Pharmaceutics. 2024 Oct 7;16(10):1304. doi: 10.3390/pharmaceutics16101304.
BACKGROUND/OBJECTIVES: Numerical simulation plays an important role in pharmaceutical preparation recently. Mechanistic models, as a type of numerical model, are widely used in the study of pharmaceutical preparations. Mechanistic models are based on a priori knowledge, i.e., laws of physics, chemistry, and biology. However, due to interdisciplinary reasons, pharmacy researchers have greater difficulties in using computer models.
In this paper, we highlight the application scenarios and examples of mechanistic modelling in pharmacy research and provide a reference for drug researchers to get started.
By establishing a suitable model and inputting preparation parameters, researchers can analyze the drug preparation process. Therefore, mechanistic models are effective tools to optimize the preparation parameters and predict potential quality problems of the product. With product quality parameters as the ultimate goal, the experiment design is optimized by mechanistic models. This process emphasizes the concept of quality by design.
The use of numerical simulation saves experimental cost and time, and speeds up the experimental process. In pharmacy experiments, part of the physical information and the change processes are difficult to obtain, such as the mechanical phenomena during tablet compression and the airflow details in the nasal cavity. Therefore, it is necessary to predict the information and guide the formulation with the help of mechanistic models.
背景/目的:数值模拟在近年来的药物制剂研究中发挥着重要作用。机理模型作为一种数值模型,在药物制剂研究中被广泛应用。机理模型基于先验知识,即物理、化学和生物学定律。然而,由于跨学科的原因,药学研究人员在使用计算机模型时面临更大的困难。
本文重点介绍了机理建模在药学研究中的应用场景和实例,为药物研究人员入门提供参考。
通过建立合适的模型并输入制剂参数,研究人员可以分析药物制剂过程。因此,机理模型是优化制剂参数和预测产品潜在质量问题的有效工具。以产品质量参数为最终目标,通过机理模型优化实验设计。这一过程强调了设计质量的概念。
数值模拟的使用节省了实验成本和时间,加快了实验进程。在药学实验中,部分物理信息和变化过程难以获取,如片剂压制过程中的力学现象和鼻腔内的气流细节。因此,有必要借助机理模型预测这些信息并指导制剂研发。