Even though online data (such as pH trends in a bioreactor or UV traces in chromatography columns) are easily accessible, offline data (such as analytical results) are still needed to tell the complete story of a batch. A method for organizing and managing online and offline data associated with a biopharmaceutical drug substance batch will be presented. This method is based on a relational model of the workflow involved in a typical monoclonal antibody process. We will discuss why relational databases are a useful tool for this purpose and provide applications of this tool for data trending, periodic product reviews, investigation of deviations, etc. Designing and implementing the relational model requires investment up front, but it makes data and knowledge management more effective than spreadsheets or paper.

Using relational modeling as a tool for data management in bioprocesses: A case study

243rd National Meeting (2012)

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