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Refining the rheological characteristics of high drug loading ointment via SDS and machine learning.

Authors :
Xilong Qian
Kewei Wang
Yulu Ma
Fang Fang
Xiangsong Meng
Liu Zhou
Yanqiong Pan
Yang Zhang
Yehuang Wang
Xiuxiu Wang
Jing Zhao
Bin Jiang
Shengjin Liu
Source :
PLoS ONE, Vol 19, Iss 5, p e0303199 (2024)
Publication Year :
2024
Publisher :
Public Library of Science (PLoS), 2024.

Abstract

This paper presents an optimized preparation process for external ointment using the Definitive Screening Design (DSD) method. The ointment is a Traditional Chinese Medicine (TCM) formula developed by Professor WYH, a renowned TCM practitioner in Jiangsu Province, China, known for its proven clinical efficacy. In this study, a stepwise regression model was employed to analyze the relationship between key process factors (such as mixing speed and time) and rheological parameters. Machine learning techniques, including Monte Carlo simulation, decision tree analysis, and Gaussian process, were used for parameter optimization. Through rigorous experimentation and verification, we have successfully identified the optimal preparation process for WYH ointment. The optimized parameters included drug ratio of 24.5%, mixing time of 8 min, mixing speed of 1175 rpm, petroleum dosage of 79 g, liquid paraffin dosage of 6.7 g. The final ointment formulation was prepared using method B. This research not only contributes to the optimization of the WYH ointment preparation process but also provides valuable insights and practical guidance for designing the preparation processes of other TCM ointments. This advanced DSD method enhances the screening approach for identifying the best preparation process, thereby improving the scientific rigor and quality of TCM ointment preparation processes.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
19
Issue :
5
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.7fce59c6880f4af7b015273b870f150d
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0303199&type=printable