Batch Data to Multivariate Analysis in 30s: Eliminating Data Silos in Process Development

Today's breakthroughs lie deep in the midst of complex, multivariate data sets that span scientific disciplines and time. Experimental anomalies and fundamental discoveries often go unnoticed because they are buried in uninterpretable spreadsheets, inaccessible databases, or excessive experimental noise. The cloud-based Riffyn software structures and links experimental designs and measurement data for analysis within seconds after it is collected. This talk will discuss examples how bioprocessing groups use these capabilities to integrate data, identify unexpected correlations, uncover root causes of error, improve process quality, and deliver right-first-time technology scale-up and technology transfer.