Optimization of pellets manufacturing process using rough set theory

Abstract

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.

Keywords: Aspect ratio; Knowledge discovery; Pellets; Rough set theory.