Nicolaus Copernicus University, Collegium Medicum, Department of Pharmaceutical Technology, Jurasza Str. 2, 85-094 Bydgoszcz, Poland.
Nicolaus Copernicus University, Collegium Medicum, Department of Pharmaceutical Technology, Jurasza Str. 2, 85-094 Bydgoszcz, Poland.
Eur J Pharm Sci. 2018 Nov 1;124:295-303. doi: 10.1016/j.ejps.2018.08.027. Epub 2018 Aug 26.
Pharmaceutical pellets are spherical agglomerates manufactured in extrusion/spheronization process. The composition of the pellets, the amount of active pharmaceutical ingredient (API) and the type of used excipients have an influence on the shape and quality of dosage form. A proper quality of the pellets can also be achieved by identifying the most important technological process parameters. In this paper, a knowledge discovery method, called dominance-based rough set approach (DRSA) has been applied to evaluate critical process parameters in pellets manufacturing. For this purpose, a set of condition attributes (amount of API; type and amount of excipient used; process parameters such as screw and rotation speed, time and temperature of spheronization) and a decision attribute (quality of the pellets defined by the aspect ratio) were used to set up an information system. The DRSA analysis allowed to induce decision rules containing information about process parameters which have a significant impact on the quality of manufactured pellets. Those rules can be used to optimize the process of pellets manufacturing.
药用微丸是通过挤出/滚圆工艺制成的球形团聚体。微丸的组成、活性药物成分（API）的含量和所使用的赋形剂的类型都会影响剂型的形状和质量。通过确定最重要的工艺参数，也可以获得适当的微丸质量。在本文中，应用了一种称为基于优势的粗糙集方法（DRSA）的知识发现方法来评估微丸制造中的关键工艺参数。为此，使用了一组条件属性（API 的含量；所使用的赋形剂的类型和含量；工艺参数，如螺杆和转速、滚圆的时间和温度）和决策属性（由纵横比定义的微丸质量）来建立信息系统。DRSA 分析允许诱导包含有关对制得的微丸质量有重大影响的工艺参数的决策规则。这些规则可用于优化微丸制造工艺。
