In 2015, Dr. J. Sunil Rao, interim chair and professor at the University of Miami Department of Public Health Sciences, and colleagues developed a method called the classified mixed model prediction (CMMP) – the first work to layout the framework under which predictions using a precision medicine framework can work.
“An interesting example of CMMP includes looking for matches in an electronic health record that might provide clues about potential drug repositioning targets for patients who have not responded to standard therapies,” Dr. Rao said.
The scenarios under which it currently operates, however, are limited and many real-life situations fall outside its scope.
Dr. Rao will serve as principal investigator on a National Science Foundation (NSF) project that will make methodological advances to CMMP into other types of subject-level prediction problems, as well as to develop new inferential methods to add a measure of confidence in the predictions. Dr. Rao will work with Dr. Jiming Jiang, from the University of California at Davis, as well as with Dr. Thuan Nguyen, from Oregon Health and Science University.
“The solutions will all involve developing new theory, such as estimation techniques, study their optimality properties, and develop new computational algorithms, run extensive simulations and then work with two subject matter collaborators in testing the methods out on real data,” Dr. Rao said.
The focus will be on precision medicine and health disparities centering on the prediction of epigenetic markers using high dimensional genotype profiles. The other will involve an area of family economics. They will use a large survey of data from China and focus on households as a primary interest.Friday Letter Submission, Publish on October 11