In the past decade, regulatory expectation has been growing for the use of quality by design (QbD) in the pharmaceutical industry. QbD application improves product development and lifecycle management by building product and process knowledge, and their relationship. Most of the activities to create an information package are performed at the small-scale, rather than the commercial-scale. However, the suitability of small-scale models to support these critical activities is dependent upon successful verification of the model that appropriately represents the proposed commercial process. Here, we present case studies on the verification of small-scale models for various downstream unit operations. In contrast to the traditional approach of comparing the quality outcome against a pre-determined set of criteria, statistical analysis was applied for process performance and product quality attributes to determine scale differences and define confidence intervals. Additionally, observations in operational differences were used to better assess and account for scale differences in future activities. We will share how statistical analysis in conjunction with understanding operational differences enable us to characterize process performance and product quality that could potentially allow predicting performance at the commercial scale, as well as establishing process capability.

Verification of small-scale models to understand commercial-scale process and predict performance and capability

249th National Meeting (2015)

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