Multivariate analysis to enable product understanding in a QbD era – Presentation @ ExcipientFest Americas 2017

Multivariate analysis to enable product understanding in a QbD era – Presentation @ ExcipientFest Americas 2017

ABSTRACT: In the pharmaceutical industry excipients are added to pharmaceutical dosage forms for multiple reasons. Commonly, they are included to aid the processing or enhance stability and/or bioavailability of a drug in a patient. Excipients do not exhibit a medical function, but are proven essential in both biopharmaceutical and technical aspects. A key attribute of excipients besides functionality is their consistency. In recent years, the pharmaceutical industry is not only evaluating the lot-to-lot variability but also analyzing excipients from a quality-by-design ‘QbD’ perspective. This as the pharmaceutical industry is more and more researching the effects of variation of critical quality attributes (CQAs) of excipients used in their formulations. This trend is in light of the Food and Drug Administration (FDA) request for understanding the impact of raw material variation on the performance and manufacturability of new drug products[1,2]. Also the principles of QbD described in the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human use (ICH) guideline Q8 are key[3]. Main objective of this work is to present an excipient supplier’s view on how to support ‘QbD’ using Multivariate Analysis (MVA) utilizing large multi-year excipient data sets. MVA has been successfully applied to (experimental) data, since the 1970’s and are ideally suited to deal with large complex data sets.

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