The Mount Sinai Medical Center is continuing its tradition of fostering breakthrough biomedical discoveries by nurturing a new breed of scientists. These scientists, both faculty and students, are exceptional men and women who have committed themselves to furthering medical science through innovation and are driving translational medicine using new tools, models, and approaches.
I am delighted to be part of this vision, which, combined with Mount Sinai’s history of world-class biomedical research, is now drawing students and faculty from quantitative sciences such as engineering and computer science, as well as other non-traditional backgrounds, to join in the process of creating new technologies for the prevention and treatment of human disease. For example, our recent academic affiliation with Rensselaer Polytechnic Institute, pools our expertise in biomedical research and patient care with Rensselaer’s talent in engineering and computational science. This unique partnership offers tremendous possibilities as it will enhance the infrastructure needed for translationally-focused faculty and students to develop novel biomedical technologies.
At the Icahn School of Medicine at Mount Sinai, we have taken a bold new approach to our pursuit of breakthrough discovery and innovation by forming an academic affiliation with Rensselaer Polytechnic Institute. Designed to pool our expertise in biomedical research and patient care and Rensselaer’s in engineering and invention prototyping, this affiliation will accelerate collaborations that support educational programs, research, and the development of diagnostic tools and treatments that promote human health.
With technology playing an increasingly important role in the diagnosis and treatment of disease, high competition for research funding, and the pharmaceutical industry investing less in research and development, Mount Sinai and Rensselaer are leveraging complementary strengths to revolutionize biomedical research and accelerate the pace of innovation and entrepreneurship across the health sciences. Read more
How do we continue to make giant leaps in medicine? What new treatment or approach will allow us to make the greatest gains for patients, in the most effective and efficient ways possible? Where will the next breakthrough come from? These are questions that academics, clinicians, hospital CEOs and medical school deans are constantly asking as we seek to meet the challenges of modern healthcare.
People and technology have a clear role in the answer, but there is another critical factor that is often overlooked: space, and the spontaneity and ideas generated when scientists and clinicians have the ability to work side-by-side.
A great example of this came up during a recent panel discussion at our SINAInnovations conference. Eric M. Genden, MD, and Chief of the Division of Head and Neck Oncology, discussed his experience on a recent case in which a patient had distant metastatic disease that he and his team could not get to surgically. While working on the case, he happened to bump into Ross Cagan, PhD and Associate Dean of the Graduate School of Biomedical Sciences. Through their conversation, Dr. Cagan suggested getting a biopsy of the tumor, sequencing it, dropping it into fruit flies, and crossing it with 150 different types of chemotherapeutic agents to see what kills the tumor. Over their chance meeting and a cup of coffee, they mapped out a targeted solution to treat the patient.
The entrepreneurial spirit that brought us personal computing, mobile technology and social networks has fundamentally changed the ways in which we shop, do business, communicate with others and generally connect with our world. Yet it has left medicine largely untouched. Electronic medical records are in their infancy, mobile applications for health are disconnected, and we’re just beginning to scratch the surface when it comes to applying the power of Big Data to medicine.
At our SINAInnovations Conference held November 12-14, Jeffrey Hammerbacher, who led the original data team at Facebook, and is currently Assistant Professor at the Icahn School of Medicine at Mount Sinai and Founder and Chief Scientist of Cloudera, was asked why health care and biomedicine are so far behind when it comes to entrepreneurship and the data revolution. His answer: “Failure hurts a lot more here.”
He could not be more right. Hammerbacher’s experience in data science comes from a place where new applications are built to be broken so that better solutions can emerge. Success is measured in clicks. Failure is a pit stop on the way to the next breakthrough. In health care and medicine, lives hang in the balance of all we do. Success is measured in lives saved. It is our moral obligation to proceed with caution when introducing new surgical techniques, therapies or different ways of doing business.
Mount Sinai School of Medicine recently unveiled its new supercomputer that is helping researchers unlock the intricate mechanisms that lead to human diseases, and hasten the discovery of treatments for them. The computer, named Minerva, after the Roman goddess of wisdom and medicine, was custom-built by Patricia Kovatch, the school’s first Associate Dean for Scientific Computing.
Minerva provides 64 million hours of computation per year. It has 7,680 processing cores, a peak speed of 70,000 gigaflops, and 30 terabytes of random access memory, making it one of the nation’s highest-performing computers in academic medicine.
“With its tremendous strength and speed, Minerva enables scientists to analyze and manipulate large data sets by running longer, more complex simulations,” says Ms. Kovatch. “This state-of-the-art technology will empower Mount Sinai’s researchers to expand the boundaries of their scholarly inquiry.” The computer’s ability to provide researchers with real-time computation of advanced molecular models and a quick analysis of genomic patterns will help Mount Sinai usher in a new era of personalized and precision medicine. Eric Schadt, PhD, Director of the Institute for Genomics and Multiscale Biology, and his researchers have been using Minerva extensively in their work.