A new research institute at UCLA hopes to use “big data” and mathematical models to improve health care and minimize medical side effects, researchers announced today.
The Institute for Quantitative and Computational Biosciences will use multidisciplinary research to look at how molecules and genes interact. If researchers can unlock the biological basis of health and disease, it can custom tailor medicines to patient needs and predict positive outcomes.
UCLA Chancellor Gene Block said faculty from schools of medicine and applied sciences will work “at the forefront of research that will help usher in a new era of personalized health care.”
The institute is led by Alexander Hoffman, professor of microbiology, immunology and molecular genetics in the UCLA College. Hoffman’s research seeks to understand how genes interact to ensure health or produce disease and the roles played by food, environmental stress, infectious agents and pharmaceuticals.
His research may lead to progress in cancer and immune disorders, both caused by errors in cellular-level decision-making.
Hoffman expects math to revolutionize health care.
“Biology is entering a new phase,” Hoffman said. “So far, biology has been much less math-based than the other sciences. Since the sequencing of the human genome in the early 2000s, there has been an irreversible change in the way biology and biomedical research are being done. At UCLA, we will … connect basic and applied sciences in an unprecedentedly productive collaboration.”
Researchers will benefit from recent advances in available technology, said Victoria Sork, dean of the UCLA Division of Life Sciences.
“Technological breakthroughs are enabling scientists to analyze not only one gene at a time, but how hundreds or thousands of genes work together,” Sork said. “Combined with big data, new knowledge of critical gene networks will lead us to a better understanding of what makes humans healthy.”
Instead of relying only on their own experience or case studies in medical journals, doctors now have the ability to access large quantities of data on similar symptoms or disease patterns.
“We haven’t yet begun to fully tap into the knowledge we have about how we have treated millions of patients,” said Dr. Steven Dubinett, director of the UCLA Clinical and Translational Science Institute. “Now, with the rise of big data, we have the capability to utilize a network of brains in a highly sophisticated manner so that all our experience … can be brought to bear on patient treatment.”
An era of “precision medicine,” with doctors able to accurately predict patient outcomes, could be the result.
UCLA has established a doctoral program in bioinformatics and expects to be a national leader in personalized health care.
Much of the data UCLA faculty will work with will come from the University of California Research eXchange, which manages more than 12 million patient records. Patient identities will not be available to researchers.
“The challenge is how to make sense of a tsunami of scientific data, to discover the critical patterns and to tell the signal from the noise,” Hoffman said. “The power of combining big data computation tools with computational modeling based on hard basic science is leading a revolution in the bio- and health sciences that provide unimagined opportunities to humanity.”
