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Leveraging Numerical Simulation Technology to Advance Drug Preparation: A Comprehensive Review of Application Scenarios and Cases

Authors :
Qifei Gu
Huichao Wu
Xue Sui
Xiaodan Zhang
Yongchao Liu
Wei Feng
Rui Zhou
Shouying Du
Source :
Pharmaceutics, Vol 16, Iss 10, p 1304 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

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. Methods: 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. Results: 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. Conclusions: 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.

Details

Language :
English
ISSN :
19994923
Volume :
16
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Pharmaceutics
Publication Type :
Academic Journal
Accession number :
edsdoj.83ef9bb516d047dc94e187b0623df164
Document Type :
article
Full Text :
https://doi.org/10.3390/pharmaceutics16101304