[learn_more caption=”Morten Allesø”] Biography: Since 2008 Morten Allesø (MA) has been working as QbD specialist in the ”Pharmaceutical Technology & Innovation” section at H. Lundbeck A/S. MA holds a Master’s degree in pharmaceutical science and received his PhD in Process Analytical Technology in 2009 at the Faculty of Health and Medical Sciences, University of Copenhagen. MA has authored more than 10 peer-reviewed publications and has one patent. His daily work at H. Lundbeck includes novel uses of QbD, PAT and efficient data analysis at various stages of tablet formulation development and manufacturing. In addition, the work conducted is manifested in Lundbeck’s technology platform and used to streamline formulation development of future Lundbeck pharmaceuticals.[/learn_more]

Abstract: Identifying the optimal composition of a solid dosage form and choosing the most effective process technology for manufacturing is a multi-disciplinary task. The relationship between attributes of the active ingredient, excipient functionality and processing environment should be understood in order to provide a robust formulation and manufacturing process. As described in Quality by Design guidelines (ICH Q8, Q9), initial risk ranking of influencing factors, designed experiments, and timely (and proper) application of analytical tools (either PAT or off-line), are key tools in establishing this relationship. While correct application of Quality by Design (QbD) principles delivers assurance of product quality, carrying out a full QbD program on an NCE does not necessarily provide an effective development workflow. In spite of risk ranking of factors, QbD opens up for potentially many variables to investigate. Active pharmaceutical ingredients (API) may be highly potent, and are thus present in low concentration in the tablet product (e.g. <20% w/w). Consequently, several of the tablet technical properties depend on excipient functionality (e.g. compression characteristics) as well as physical parameters of excipient and API (particle size and morphology) which affect the distribution between active and excipient in the blend/tablet.  A large part of the process understanding may therefore be acquired in advance and described in a more general context by distinguishing between API-specific product properties and excipient-related properties. This work presents case studies on roller compaction (dry granulation) and fluidized bed wet granulation, describing how general formulation and process knowledge of a well characterized API model substance is accumulated in so-called platform formulations, as means to provide a more effective workflow for NCE formulation development.