The National Center for Advancing Translational Science (NCATS) https://ncats.nih.gov within NIH is developing a computational platform to enable connections among data types. The aim is to bring these connections together to better understand disease and to come up with more effective treatment options.
The inability to see connections among data can be frustrating especially in translational science. For example, researchers might find by screening for drugs, that a drug that is known to treat one disease is useful against another disease. If scientists look further, they might find the connection between that drug and that specific disease.
According to Noel Southatt, PhD, Program Leader in NCATS Division of Pre-Clinical Innovation, “It is sometimes difficult for researchers to see relationships among different data types and this can affect clinical outcomes.”
The demonstration projects are especially collaborative. For example, three groups of researchers with different areas of expertise have combined their resources to study a rare inherited disease affecting the bone marrow which can cause developmental problems and cancer.
This project has data analytics experts experienced in environmental data collaborating at the University of California, San Diego https://ucsd.edu, scientists at the Renaissance Computing Institute http://renci.org, and the University of North Carolina at Chapel Hill www.unc.edu.
The researchers working with clinicians and scientists from Oregon Health & Science University in Portland www.ohsu.edu are testing a computational strategy to study variations in genes affected by environmental exposure and how they may cause disease.