Dr. Melissa Haendel and team receives $5 million NIH award for Monarch Initiative

Monarch

September 27, 2016

Melissa Haendel, Ph.D., associate professor of medical informatics and clinical epidemiology, OHSU School of Medicine, associate professor, OHSU Library, and fellow researchers on the Monarch Initiative team have been awarded a $5 million grant from the National Institutes of Health Office of the Director to increase the utility of animal models and improve scientific understanding of human diseases. 

The Monarch Initiative is a global, translational consortium, which includes researchers from OHSU, the Lawrence Berkeley National Laboratory, the Jackson Laboratory, the University of Pittsburgh, Charité Hospital, Queen Mary University of London, and the Garvan Institute of Medical Research. It provides sophisticated algorithms for phenotype comparison within and across species, leveraging a large corpus of deeply integrated and structured information about genetics, descriptions of resulting malformations, clinical signs and symptoms. 

The $5 million award over four years will support extension of the scope and precision of Monarch disease modeling by including a greater diversity of species and sources that focus on a broader range of common and complex diseases and new categories of clinical data. This work will enhance the team's capabilities to inform diagnostics, mechanism discovery, and improved phenotyping.  

"We are deeply excited to continue this work in translational phenomics and are dedicated to making more basic research data available for clinical applications," said Dr. Haendel. "With this funding, we will be developing new, user-focused tools for maximizing the utility of the data for patients, researchers and clinicians."

Without a big-picture view of phenotype data, many questions in genetics are difficult or impossible to answer. Monarch's computational tools, bioinformatics analyses and interactive visualizations provide clinicians and researchers with previously unavailable insight from numerous information sources to shorten the path of information exchange between the bench and clinic, with the ultimate goal of advancing rare disease diagnosis and personalized medicine.