Namdar Ashkan, Borhanzadeh Tina, Salahinejad Erfan
Faculty of Materials Science and Engineering, K. N. Toosi University of Technology, Tehran, Iran.
Sci Rep. 2024 Dec 28;14(1):31164. doi: 10.1038/s41598-024-82496-3.
This paper introduces an evidence-based, design-of-experiments (DoE) approach to analyze and optimize drug delivery systems, ensuring that release aligns with the therapeutic window of the medication. First, the effective factors and release data of the system are extracted from the literature and meta-analytically undergo regression modeling. Then, the interaction and correlation of the factors to each other and the release amount are quantitatively assessed. Finally, the factors are numerically and graphically optimized via linking the meta-analyzed release data and the well-documented therapeutic window of the drug, followed by verification. For a more in-depth explanation, the introduced approach is exemplified by a drug delivery, consisting of emulsion-derived poly lactic-co-glycolic acid-vancomycin (PLGA-VAN) capsules for treating Staphylococcus Aureus-induced osteomyelitis. Novel and validated findings for the model system, along with the thorough architecture of the introduced approach, suggest its potential applicability for any delivery systems with sufficient reliable data in the literature.
本文介绍了一种基于证据的实验设计（DoE）方法，用于分析和优化药物递送系统，确保释放与药物的治疗窗相匹配。首先，从文献中提取该系统的有效因素和释放数据，并通过荟萃分析进行回归建模。然后，定量评估各因素之间以及各因素与释放量之间的相互作用和相关性。最后，通过将荟萃分析得到的释放数据与该药物充分记录的治疗窗相联系，对各因素进行数值和图形优化，随后进行验证。为了更深入地解释，以一种药物递送为例对所介绍的方法进行说明，该药物递送由用于治疗金黄色葡萄球菌引起的骨髓炎的乳液衍生聚乳酸-乙醇酸-万古霉素（PLGA-VAN）胶囊组成。该模型系统的新颖且经过验证的发现，以及所介绍方法的完整架构，表明其对于文献中有足够可靠数据的任何递送系统都具有潜在的适用性。
