(661d) New Trends in Materials-Sparing and Modelling Approaches Towards Pharmaceutical Development
AIChE Annual Meeting
Thursday, November 17, 2016 - 9:33am to 9:54am
In this talk, examples of how materials-sparing approaches have been used for the development of both an oral solids drug product (OSD) and a biologic drug product will be presented. For the OSD case, plastic/elastic material properties were leveraged to develop an empirical heuristic used to predict the feasibility of two materials to successfully yield a bilayer tablet. The primary tool used to develop this assessment was a compaction simulator fitted with an instrumented die. The materials-sparing work-flow efficiently guided the formulation development of bilayer tablets (using <50g of material); the approach was validated at pilot and commercial-scales and during accelerated stability testing. For the biologic drug product, an FEM-based model was used to optimize commercial lyophilization cycles by leveraging knowledge of heat and mass transfer principles. Lyophilization, which involves freezing a product and then reducing the surrounding pressure to remove the frozen solvent via sublimation, is used to increase the shelf-life of biologic products by enabling products to be stored as dry powders instead of in solution. Thus, heat and mass transfer rates during both freezing and sublimation processes impact product quality and stability. However, technology transfer and scaling approaches typically utilize large DOEs (design of experiment) to determine cycle parameter ranges through a trial-and-error approach, which is costly both in terms of material needs (API) and resources (time, utility costs). By developing an understanding of how heat and mass transfer rates change with scale, the transfer of a product from lab to commercial scale was successfully completed using only two engineering runs. The presentation will focus primarily on key decisions made during the development process that were enabled by the use of materials-sparing laboratory techniques or modelling predictions and discuss how the propagation and acceptance of these capabilities can streamline the development of future products.