title: Prediction of segregation tendency occurrence in dry particulate pharmaceutical mixtures: development of a mathematical tool adapted for granular systems application.
abstract: Segregation phenomena are of importance in nearly all processes involving dry granular and powder mixtures. The extent of segregation directly influences the eventual rejection of a considerable percentage of the final product in the majority of pharmaceutical processes; among these are those mixtures destined for powder compression processing for the production of tablets. Although the parameters influencing segregation are relatively well-known qualitatively, there are, so far, no widely accepted quantitative prediction tools that permit process improvement and optimization of production as a function of the mixture's composition and the particulars of individual processes (e.g., geometry of the vessels). Thus, within present practice, only general design considerations and the technical expertise of engineers and operators are relied upon to optimize these processes on a case-by-case basis. It is in these circumstances that a study of the tendency towards segregation in free flowing granular materials was conducted, using a simple tool previously developed for the study of the behavior of continuous chemical reactors with classical fluid flows. The measurement of average residence times and their variance is used to calculate the deviation of chemical reactors from the ideal behavior of a perfectly mixed vessel or a plug flow pattern. In this work, these measurements are adapted to evaluate the tendency of a granular mixture to segregate. The method consists of introducing a pulse perturbation (of another material) to the established regular flow of a single granular material or a granular mixture and to then calculate the response of the system in terms of the concentration of the pulsed material at the process outlet. The average granular particle residence time and its standard deviation are then related to the segregation tendency.
authors.affiliation: Department of Chemical Engineering, Université de Sherbrooke, Sherbrooke, Quebec, Canada.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Abatzoglou
authors.forename: Jean-Sébastien
authors.initials: JS
authors.lastname: Simard
mesh_terms: D002626:Chemistry, Pharmaceutical / Q000295:instrumentation / Q000379:methods*; D005544:Forecasting; D008956:Models, Chemical; D004364:Pharmaceutical Preparations / Q000032:analysis / Q000737:chemistry*; D011208:Powders
chemical_list: D004364:Pharmaceutical Preparations; D011208:Powders