(522a) Modeling of Active Ingredient Loading in Microparticle Controlled-Delivery Systems | AIChE

(522a) Modeling of Active Ingredient Loading in Microparticle Controlled-Delivery Systems

Authors 

Kouskoumvekaki, I. - Presenter, Technical University of Denmark


Microparticle controlled-delivery systems consist of a polymeric matrix and an encapsulated active ingredient, which could be a flavour, a pharmaceutical, or a pesticide, to list only some of the diverse applications of such systems. The design of an effective microparticle control-delivery system requires ? among others ? special understanding of the thermodynamics of multicomponent systems and has been the subject of significant research in the recent years. The present study focuses on the solvent evaporation manufacturing process. In this process an organic phase consisting of a volatile solvent with dissolved polymer and the AI to be encapsulated, is emulsified in an aqueous phase containing dissolved surfactant. The surfactant is utilized in order to stabilize the polymeric droplets and usually concentrations above the CMC are employed, which means that surfactant micelles are also present in the manufacturing solution. The most serious challenge with encapsulating hydrophilic materials is loss of AI to the external aqueous and micellar phases during the formation of the microparticles. The quantitative prediction of the final amount of AI in the polymeric droplets (AI loading) at the end of the manufacturing process is the goal of this work. We have applied thermodynamic, group-contribution models (GC-Flory, Entropic-FV) in the calculation of the active ingredient (AI) loading and have evaluated their performance against a previous work with UNIFAC-FV (Tse et al. 1999), as well as some limited experimental data from the literature. We have further simplified the earlier treatment of Tse et al. (1999), by assuming constant equilibrium factors that are obtained via the infinite dilution activity coefficient values of the AI in the equilibrium phases. Furthermore, the GC-Flory parameter table has been extended in order to include the missing (C)3N group parameter for the surfactant. Further optimization of the method is expected to lead to the development of a valuable tool for the process and product design during the manufacturing of microparticle controlled-delivery systems and would significantly assist in the optimization of polymer screening, solvent selection or optimization of the manufacturing conditions, in order to obtain desired release characteristics.

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