Tailoring Treatment with Big Data

Tailoring Treatment with Big Data

Mount Sinai

Read digital edition

Last year, the Icahn School of Medicine at Mount Sinai introduced the world to Minerva, a supercomputer which is among the most powerful at academic medical centers in the country. Named for the Roman goddess of wisdom, Minerva is designed to bring order to the ever-expanding "digital universe," and to make use of one of the most striking technological developments of recent years—big data.

Minerva's data of choice are genome samples, massively complex data sets which can be as large as 1 terabyte for a single patient. Minerva has access to such samples through Mount Sinai's BioMe Biobank Program, a clinical care cohort of 27,000 Mount Sinai patients who volunteered to share their genomic sequences and electronic health records for groundbreaking research.

Eric Schadt, chair of genetics and genomic sciences and the Jean C. and James W. Crystal Professor of Genomics at the Icahn School of Medicine hopes that Minerva will be able to see patterns in those genomes that lesser computers cannot—patterns like which patients are likely to develop cancer, heart disease, or Alzheimer's. Identify the patterns, and it becomes possible to stop a disease before it starts— an idea so revolutionary it would not be a stretch to call it the holy grail of 21st century medicine.

"We analyze big data from multiple levels—or scales—to build predictive models that offer novel insights on disease, and we apply these models in a clinical setting to improve diagnosis and treatment for our patients," says Schadt, also the director of the Icahn Institute of Genomics and Multiscale Biology at Mount Sinai,. "In the same way that sophisticated predictive mathematical models drive decision making in the global financial markets (what stocks to buy, how long to hold, when to sell), medicine has begun to rely on such models to derive meaning from vast amounts of patient data, with the goal of better understanding and treating human disease."

Using big data to achieve small-scale results, specific to each patient, is at the heart of precision medicine. Carlos Cordon-Cardo, Irene Heinz Given and John LaPorte Given Professor and chair of the Department of Pathology, says the aim of this movement is "to switch from group-management approaches—ones that stratify patients into disease categories and apply therapies based on pre-determined protocols—to an approach that uses patient-specific clinical and biological characteristics to predict treatment efficacy and drug sensitivity."

"In the same way that sophisticated predictive mathematical models drive decision making in the global financial markets, medicine has begun to rely on such models to derive meaning from vast amounts of patient data."

To this end, Mount Sinai has launched a new initiative, called PRECISE Medical Diagnostics™, or PRECISE MD™, designed to advance the field of systems pathology. The goal, says Cordon-Cardo, who is also professor, Department of Genetics and Genomic Sciences, at the Icahn School of Medicine, is "to translate data into knowledge, and use such knowledge to render more effective and efficient patient care and health management."

But medicine cannot become fully precise until the sort of genomic sequencing that Minerva relies on becomes widespread. After all, a physician can't use a patient's genome to make predictions about his future health if his genome has never been sequenced. Whole genome sequencing is currently too expensive to be routine—costing between $5,000 and $10,000, and rarely covered by insurance—but the technology, Schadt says, "is becoming more comprehensive and less expensive."

This is partly due to the work of non-profit organizations like the New York Genome Center, of which Mount Sinai is a founding partner. An independent research facility dedicated to making genome sequencing more affordable and more common, it is a joint partnership between a number of New York medical institutions—including the Albert Einstein College of Medicine, Columbia University, and The Rockefeller University. It is these kinds of organizations that led Dennis S. Charney, Anne and Joel Ehrenkranz Dean, Icahn School of Medicine at Mount Sinai, and president for academic affairs at the Mount Sinai Health System, to predict that New York will become "the Silicon Valley of the east coast, certainly in terms of innovation in biomedical research and health information technology."

Mount Sinai alone has invested more than $100 million in multi-scale biology, confident that the eventual savings from precision medicine will more than make up for the cost.

"In light of the current healthcare crisis, and with federal research funding facing dramatic cuts, academic medical centers need to invest in big data and its infrastructure," says Charney. "While costly up front, investing in big data will provide significant long-term return because it will help us better prevent, diagnose, and tailor treatment for disease, which will reduce the cost burden on health systems and the nation as a whole."

Schadt is dreaming of a day when, as he puts it, "the practice of medicine will be so personalized that physicians will be able to pinpoint what disrupted the network that caused a person's disease, predict the course of the disease, and determine how best to treat or even prevent it."

In some cases, it may be possible to deliver a cure before a disease even strikes—a feat truly worthy of a Roman goddess.


Photo: Researchers work on an experiment at the Icahn School of Medicine at Mount Sinai.