| 袁晨宜，李 晓，洪卫漫，陈泽锴，周良良，张 定*
，陈振华*.三种常用数据分析方法在药物制剂研究中的应用[J].海南师范大学学报自科版,2025,38(2):167-176 |
| 三种常用数据分析方法在药物制剂研究中的应用 |
| Application of Three Commonly Used Data Analysis Methods in Pharmaceutical Preparations Research |
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| DOI：10.12051/j.issn.1674-4942.2025.02.007 |
| 中文关键词: 数据分析方法 药物制剂 多元统计分析 机器学习 数据挖掘 |
| 英文关键词: data analysis methods pharmaceutical preparations multivariate statistical analysis machine learning data
mining |
| 基金项目:江西省杰出青年基金项目（20224ACB216019） |
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| 摘要点击次数: 812 |
| 全文下载次数: 682 |
| 中文摘要: |
| 随着科学技术不断发展，药物制剂的复杂性和个性化需求日益增加，传统的试错
法已无法满足快速、高效、精准的药物研发要求。数据分析通过使用科学方法、过程和算法从
大规模数据集中洞察和提取信息，为药物制剂设计优化提供了一种科学、系统的手段。数据
分析方法的应用逐渐改善药物剂型设计、优化生产工艺、提高药物制剂研发效率，对提升药物
制剂的质量和疗效具有重要意义。本文概述了多元统计分析、机器学习和数据挖掘这三种常
用的数据分析方法及三者之间联系与侧重，总结了数据分析方法在药物制剂研究中的应用，
并对数据分析在药物制剂研究中应用前景进行探讨和展望，为药物制剂智能化发展提供
参考。 |
| 英文摘要: |
| With the continuous development of science and technology, the complexity of pharmaceutical preparations and
the demand for personalization are increasing, which makes the traditional trial-and-error methods insufficient to meet the
rapid, efficient, and precise requirements of drug research and development. Data analysis, by employing scientific meth⁃
ods, processes, and algorithms to gain insights and extract information from large-scale datasets, provides a scientific and
systematic approach for optimizing pharmaceutical preparation design. The application of data analysis methods is gradual⁃
ly improving the design of drug dosage forms, optimizing production processes, and enhancing the efficiency of drug formu⁃
lation research and development, which is significant for improving the quality and efficacy of pharmaceutical preparations.
This article reviewed three commonly used data analysis method including multivariate statistical analysis, machine learn⁃
ing, and data mining, highlighting their interconnections and focuses. We summarized the application of data analysis meth⁃
ods in the research of pharmaceutical preparation and discussed the prospects for the application of data analysis in this
field, providing a reference for the intelligent development of drug formulations. |
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