Case Study: Diaceutics standardizes clinical data labeling and speeds insights with KNIME

How Diaceutics automated & streamlined data labeling to increase speed to insights

Diaceutics, a data analytics and end-to-end services provider for the life sciences industry, needed a better way to standardize and label large volumes of clinical and diagnostic testing data. Using KNIME, the team aimed to streamline analysis, combine business rules with domain expertise, and make complex patient-level data easier for analysts to use consistently across projects.

KNIME implemented a standardized workflow using linked components, control files, and automated SQL generation to label data such as disease stage, biomarkers, methodologies, and other clinical variables. The result was a faster, more scalable process that reduced workflow complexity, improved quality control, and increased project throughput, while giving analysts and clients a common data foundation for quicker, more reliable insights.

Diaceutics

Isabel Stacey

Senior Data Analyst