Abstract

Polymeric microparticles are widely used as drug delivery platforms either alone or embedded in more complex structures for regenerative medicine. Emulsion-solvent evaporation is the most extensively used technique for microparticles preparation. Despite the apparent simplicity of this method, there is no general procedure for producing microparticles of predictable characteristics (particle size, size distribution, encapsulation efficiency, and drug loading). Hybrid systems such as neurofuzzy logic allow identifying relationships between inputs and outputs, expressing the generated mathematical models through rules in linguistic format. In this work, the relationships between the variables involved in the emulsion-solvent evaporation process and the quality parameters of PLGA microparticles as drug delivery systems were established. Neurofuzzy logic software was able to generate models of high predictability (> 85%) for the microspheres properties namely particle size, size distribution, encapsulation efficiency and drug loading. Moreover, the generated sets of IF-THEN rules allowed to dictate general guidelines to better select the PLGA microparticles formulation parameters. This approach would be of great interest as a starting point to set-up protocols for the development of PLGA microparticles obtained by emulsion-solvent evaporation for many applications.

摘要

聚合物微粒被广泛用作药物输送平台，无论是单独使用还是嵌入到再生医学的更复杂的结构中。乳液-溶剂蒸发是最广泛使用的微粒制备技术。尽管该方法看似简单，但没有通用的程序来生产具有可预测特征（粒径、尺寸分布、包封效率和载药量）的微粒。神经模糊逻辑等混合系统允许识别输入和输出之间的关系，通过语言格式的规则表达生成的数学模型。在这项工作中，建立了乳液-溶剂蒸发过程中涉及的变量与作为药物递送系统的 PLGA 微粒的质量参数之间的关系。Neurofuzzy 逻辑软件能够针对微球特性（即粒径、尺寸分布、包封效率和载药量）生成高可预测性 (> 85%) 的模型。此外，生成的 IF-THEN 规则集允许规定一般准则，以更好地选择 PLGA 微粒配方参数。这种方法作为制定用于许多应用的乳液-溶剂蒸发获得的 PLGA 微粒开发方案的起点将引起极大的兴趣。生成的 IF-THEN 规则集可以规定一般准则，以更好地选择 PLGA 微粒配方参数。这种方法作为制定用于许多应用的乳液-溶剂蒸发获得的 PLGA 微粒开发方案的起点将引起极大的兴趣。生成的 IF-THEN 规则集可以规定一般准则，以更好地选择 PLGA 微粒配方参数。这种方法作为制定用于许多应用的乳液-溶剂蒸发获得的 PLGA 微粒的方案的起点将引起极大的兴趣。