As biopharma manufacturers incorporate more data-driven monitoring and control systems in production processes, the quality of the data, as well as integrating, interpreting, and protecting it, become more important. One solution is to build quality features into these systems during process development.
As a process scales, “there is a need to transfer or integrate process development (PD) data; therefore, building data quality into these activities right from the start is important. Management of data quality always facilitates integration with other systems irrespective of the scientific or business purpose,” observes Chris Andrews, a senior solution consultant with Dassault Systèmes BIOVIA.
“In the case of monitoring data during process development, it is critical,” Andrews says, “to identify and segregate valid data intended for technical transfer and to ensure that data are clean (i.e., have few invalid results or records) as possible. Higher quality data will minimize integration time, improve the ability to quickly interpret those data, and offer assurance of data integrity and provenance.”