Today's research and development breakthroughs lie deep in the midst of complex, multivariate data sets. 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 SDE software structures experimental designs and links it to measurement data for machine learning within seconds after it is collected in the lab. We will demonstrate how biotech companies are using this capability to identify unexpected correlations in animal studies, uncover root causes of error in screening experiments, and deliver right-first-time technology scale-up in bioprocess development.
Research shows that data scientists spend up to 80% of their time performing low value activities (data collation, organization, and cleaning), and only 20% of their time doing the important part — analyzing and learning from that data.
The goal of the webinar is to illustrate how Riffyn automates data joining, annotation, and collation, shifting the rate limiting step from data organization and cleaning to data analysis, allowing scientists to truly harness the power of machine learning.