In recent years, there has been a continuous drive from pharmaceutical companies and regulatory bodies to develop more robust pharmaceutical formulations and processes based upon knowledge. This has resulted in requests to excipients suppliers to help de-risk the use of their excipients, in line with Quality by Design principles. Quality by Design emphasizes that robust formulations and processes should be able to accommodate typical variation seen in APIs, processes, and excipients, without compromising the product’s manufacture, stability or performance.
All production processes, including excipient production, have some inevitable degree of variation. The functionality of excipients can be affected by this intrinsic variation, and the impact of this variation on the final dosage form should be understood. To understand the effect and interaction of different factors on product performance, big data sets can be utilized.
Variability in the data describing excipient properties can originate from the raw material, the manufacturing process, the analytics, sampling and reporting. Not all these types of variability are however relevant. Careful analysis of the data can help to develop a formulation in which what varies doesn’t matter and what matters doesn’t vary. This can however only be done in conjunction with subject matter experts, who are required to reveal the cause and way forward with observed variability. Discussion of the data should be performed to evaluate if a change in an excipient data represents an actual change in the product, and if excipient changes also impact the final dosage form.
Learning Objectives:
Describe how data analysis can be used to identify sources of variation in a dataset.
Define how to investigate if what varies doesn’t matter and what matters doesn’t vary.
Understand how excipient suppliers can support in de-risking the use of excipients.
