Case Study: GSK advances acute pancreatitis biomarker discovery with Eagle Genomics e[datascientist]

GSK advances acute pancreatitis biomarker discovery with Eagle Genomics in a study of under 100 patients and over 1,000 measurements per patient

GSK faced the significant challenge of predicting the progression of acute pancreatitis, a common and often fatal disease with no reliable clinical tests. Their objective was to identify molecular biomarkers in a unique, high-dimensional dataset from a small patient cohort to discriminate between severe and mild forms of the disease. To tackle this, they partnered with Eagle Genomics and employed its e[datascientist] platform.

Eagle Genomics implemented a systematic machine learning approach, applying multiple methods to the curated data to maximize the discovery of biological signals. This process identified features with discriminative accuracy indicative of clinical utility. The results provided GSK with biologically-relevant insight that improved their molecular understanding of the disease and are now being used to justify investment and guide the design of ambitious, more powerful follow-up studies, representing significant progress towards a prognostic test.

GSK