The Center for Individualized Medicine and the University of Illinois are teaming up to translate data-heavy genomics research into customized clinical care.
Fifty thousand. That’s how many people have enrolled in the Mayo Clinic Biobank, a collection of samples and health information donated by Mayo Clinic patients for use in ongoing biomedical research. Multiply that number by 180,000, or the number of exons — regions of DNA that direct the human body to make essential proteins—contained in a single human genome, and you get 9 billion. Through statistical analysis, researchers and physicians at the Mayo Clinic for Individualized Medicine (CIM) are using those 9 billion data points to translate genomic medicine into clinical practice.
But they can’t do it with just pencil and paper. Crunching that much data requires high-performance computers and people who can run them — like Arjun Athreya. A third-year Ph.D. candidate in Electrical and Computer Engineering at the University of Illinois at Urbana–Champaign (UIUC), Arjun is supporting pharmacogenomics research at CIM this summer through an institutional partnership that brings together top thinkers in technology and medicine.
Established in 2010, the Mayo-Illinois Alliance for Technology-Based Healthcare is a research collaboration that leverages the resources of UIUC and CIM to advance research and clinical treatment options in individualized medicine. The Alliance funds translational research activities and education opportunities in genomic medicine, point-of-care diagnostics — and, increasingly, information technology and computational engineering applied to health care.
For young statisticians, computer scientists and engineers intrigued by the growing possibilities for big data in health care, the chance to collaborate on cutting-edge research at Mayo Clinic holds obvious appeal. “You can’t be working on medical data and not know what people at Mayo are doing, or miss an opportunity to work with their clinical experts,”says Athreya, who has an M.S. in Electrical and Computer Engineering from Carnegie Mellon University and is advised by Ravishankar Iyer, Ph.D., and Zbigniew Kalbarczyk, Ph.D., both of UIUC’s Coordinated Science Lab.
Likewise, Mayo researchers need the informatics infrastructure and powerful minds housed at UIUC, a world leader in engineering and computational sciences. Without this technology expertise, says Athreya, teasing out biological patterns from the chaos of numbers would be daunting.
“When you look at analyzing these data, a lot of these experiments can take hours to days to complete,” he says. “Today it might seem trivial when we say something takes hours to run for one patient, but if every hospital and every clinic starts to do this for every patient that comes in, the scale becomes pretty messy very quickly.”
If engineers can write more sophisticated software programs and make them run on the right kind of hardware, they can reduce the entire computation time needed for data analysis in experiments, Athreya explains. Millions or billions of unintelligible data points can quickly assume meaning. That makes research in individualized medicine more efficient, which ultimately translates into clinical care that better meets the patient’s needs.
For a glimpse at the Alliance’s integrated approach to research, consider Athreya’s contributions to cancer treatment studies in CIM’s Pharmacogenomics Program, which is led by Richard Weinshilboum, M.D., and Liewei Wang, M.D., Ph.D. To understand why standard drugs work effectively in some cancer patients but not in others, CIM investigators are collaborating with UIUC researchers like Athreya to study how variations in genes affect patients’ response to medications.
Within the Pharmacogenomics Program, Athreya is working with Krishna Kalari, Ph.D., to develop and apply computational models to statistically analyze the impact of metformin, a drug used to manage type 2 diabetes that also shows promise in treatment of certain breast cancers. Their models are helping CIM researchers identify genetic mutations in tumors that affect a patient’s response to metformin. The goal, says Athreya, is to “narrow down the impact of the drug to specific genetic biomarkers. Then we will know which patients would respond to this drug.”
Though the CIM research on metformin will continue after he returns to UIUC, Athreya says his summer at Mayo has given him a lasting gift: greater appreciation for how his analytical skills can harmonize with the knowledge of health care experts.
“There were times when from our engineering perspective, we generated some results that made no sense to us,” he says. “And then the physicians and biologists looked at it and they said, ‘We know exactly what this is saying, and we can narrow down our research base.’ Those moments when we put up some results and there is a huge biological story behind what they see, those moments are pretty exciting.”
In those moments, he says, he sees the power of data to transform medicine.
— Shea Jennings
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Shea Jennings is an intern with the Mayo Clinic Department of Public Affairs which supports the Center for Individualized Medicine. A senior at Yale University, she is studying political science and health politics.