We teamed up with GSK to identify the molecular biomarkers for acute pancreatitis, a potentially fatal disease to which patients respond differently, making treatment unpredictable. It is the leading gastrointestinal cause of hospitalization in the US, and the ability to predict patient response to the disease greatly improves the effectiveness of treatment.
GSK were looking for better biomarkers for acute pancreatitis within a large, high-dimensional dataset, which brought about significant challenges. Project partners called upon Eagle’s combined platform and services expertise to firstly curate, catalogue then exploit the data through machine learning.
Our findings provided valuable insight, uncovering interesting disease/metabolite correlations that are being further researched to enable better testing and treatment of the disease.
Find out more about the project by reading the full case study.