通过分析层次过程和拓指数预测适合 keloid 的药物
K Janagi1,2, A Usha1, Rashad Ismail3
1Department of Pure and Applied Mathematics, Alliance University Alliance College of Engineering and Design, Bengaluru, 562106, India.
Scientific reports
|September 30, 2025
概括
这项研究使用多标准决策 (MCDM) 和分析层次过程 (AHP) 排名了12种类药物. doxorubicin 成为最有效的 keloid 治疗方法,而 5-Fluorouracil 是最不有效的.
科学领域:
- 药用化学 医学化学
- 计算化学的计算化学
- 皮肤病学 皮肤病学
背景情况:
- 基洛伊德的患病率正在增加,需要新的有效治疗药物.
- 目前的 keloid 治疗需要优化,以改善患者的治疗结果.
- 药物疗效的预测建模对于开发先进疗法至关重要.
研究的目的:
- 通过使用多标准决策 (MCDM) 确定用于 keloid 治疗的最有效药物.
- 根据其物理化学性质和预测的疗效,对12种基洛因药物进行排名.
- 应用分析层次过程 (AHP) 进行药物选择.
主要方法:
- 利用定量结构与属性关系 (QSPR) 技术来分析物理化学性质.
- 采用了从分子结构中得出的基于度的拓索引.
- 应用了分析层次过程 (AHP) 进行多标准决策和药物排名.
主要成果:
- 德克索鲁比被确定为治疗 keloid 的最有效药物.
- 在被研究的药物中,5-fluorouracil被确定为最不有效的药物.
- AHP排名提供了一个明确的药物适合 keloid 治疗的层次结构.
结论:
- doxorubicin 显示出作为 keloids 的主要治疗剂的显著潜力.
- 该研究强调了QSPR和AHP在评估和选择治疗复杂疾病的药物的实用性.
- 这些发现可以指导优越的化物治疗策略和药物组合的开发.
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