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Jan 15, 2013 (Vol. 33, No. 2)

The Schadt Equation

Mathematics + 21st Century Computational Power = Safer and More Effective Healthcare

  • Key Challenge

    Click Image To Enlarge +
    The workflow that the Icahn Institute for Genomics and Multiscale Biology employs to construct predictive models of disease and then to use those models to identify drug targets and biomarkers. In this example, the goal is to elucidate the complexity of Alzheimer’s.

    For Dr. Schadt, one of his biggest challenges is how to unify mathematically different modeling approaches to develop better models of disease. As he sees it, data-driven, hypothesis-free modeling approaches, i.e., structured learning approaches that assume we don’t know the rules of complex systems but must learn them from big data, are largely pursued independently of more hypothesis-driven modeling, i.e., approaches for which we assume we know the rules and how things are connected.

    “We are seeking to integrate these approaches so that we get the best of both worlds while minimizing the weaknesses of each,” notes Dr. Schadt.

    Dr. Schadt has some impressive resources available for his quest. The institute currently uses roughly 40,000 square feet, which includes a CLIA-certified sequencing core, a super computer (Minerva), wetlabs for sample preparation and running of molecular biology experiments, and dry lab space for different computational groups (statistical genetics, bioinformatics and sequence informatics, and network modeling/systems biology).

    The institute also has some unique capabilities, including computing power that can manage petabytes [one quadrillion (1015) bytes] scales of data, and the presence of worldclass information technology personnel.

    About half of the institute’s current faculty of 30 are experts in network modeling, predictive modeling, or machine learning. The other half is focused on sequence informatics, disease biology, and building interfaces. Dr. Schadt hopes to create the right ecosystem so that the diversity of talent across disciplines is all in the same space, learning and working with each other.

    He’s still looking for additional talent. “We have staff scientist positions, faculty positions, post-doctoral positions, and we are recruiting students for our computational biology Ph.D. program.”

    Interestingly, five years ago virtually none of these areas of expertise would have been required in any medical center. Today, they are essential to one of the institute’s key missions: handling large volumes of data, with the goal of developing information and creating understanding that can be translated rapidly into the clinical setting.

  • Biobank Facility

    Mount Sinai’s biobank is another resource available to the institute. Dr. Schadt is impressed that Irwin Bottinger, M.D., head of the biobank, made the far-sighted decision to change the biobank’s tissue collection efforts to an opt-in system in which, instead of de-identifying and aggregating the information, every tissue donor specifically gives his or her consent.

    Since consent was required, it took longer to build the database to its current size of nearly 30,000 tissue donors, but the enormous benefit is that the institute’s researchers can go back to the tissue donors. Because the data is linked to the donor, it’s possible to find the ideal research candidates for a particular study.

    In the case of those databanks that have chosen the opt-out model, they may have been able to acquire large numbers of tissue donors quickly, but by de-identifying the donors, the link between the individual and the information is broken, making the information far less useful.

    The data Mount Sinai collects is also valuable because the population it serves is unusually diverse. Last year, the Mount Sinai Hospital treated nearly 60,000 inpatients and there were more than 500,000 outpatient hospital visits. The population the hospital draws from includes one of the country’s poorest zip codes on its northern border and, to the south, the population comes from one of the richest zip codes. The data collected reflects great socio-economic and ethnic diversity.

    “When we want to understand different diseases, this is the perfect place. It’s almost like a mini world,” says Dr. Schadt.

    Mount Sinai may have extraordinary resources, but Dr. Schadt and the Institute also collaborate with other institutions, including Stanford, Harvard, MIT, Yale, UCLA, and others. Further, he mentions that, “We are seeking to partner with different pharmaceutical and biotech firms. Such companies are eager to partner and leverage our disease models and clinical setting to carry out human proof of concept studies.”

  • Before Mount Sinai

    The network of events that came together to bring Dr. Schadt to Mount Sinai itself involves considerable complexity. As a child in Stevensville, Michigan, population 1,000, he hardly seemed destined for a scientific career. His stepfather was a beautician when the future scientist was a boy, and the family members were all creationists.

    Education wasn’t valued, and Dr. Schadt was an indifferent student. It wasn’t until he joined the Air Force and took a battery of aptitude tests that anyone realized his potential as a mathematician. The Air Force provided him with a scholarship to Cal Poly, and in this new and exciting world, he majored in computer science and applied math, followed by studying for a doctorate in pure math at UC Davis.

    Although he finished the course work and exams for a Ph.D. at Davis, pure math became less and less satisfying. Wanting to do something that would more directly help people, he enrolled as a Ph.D. candidate in UCLA’s biomathematics program. That eventually led to a career at Merck.

    While at Merck, he and some of his similarly minded colleagues came to understand that drugs targeting one gene may marginally solve one problem, e.g., diabetes, but as the drug perturbed the network that the target gene operated in, it might well cause additional problems.

    For instance, in the case of diabetes, one promising drug turned out to help mitigate the effects of a gene for diabetes, but it also created additional risks for obesity and cardiovascular disease. Further, targeting single genes was not enough to effect the right type of change over the vast molecular networks that operate within any given individual.

    Instead, Dr. Schadt believed that to effectively treat most common disorders, networks of genes must be targeted. Merck, however, balked at adopting his network approach to drug development and, in 2009, he and his fellow Merck colleague, Stephen Friend, left to start Sage Bionetworks. Then came the offer to head Mount Sinai’s Icahn Institute for Genomics and Multiscale Biology.

  • Reluctant Transplant

    Dr. Schadt moved from California to New York in 2011. Although he now finds Mount Sinai and New York a perfect location for himself and his family, he was reluctant to leave California. His family loved the Golden State and no one wanted to leave.

    However, professionally, he realized that Mount Sinai would be perfect for him, considering the leadership, the vision, and the financing that were available. When he added to that the opportunity to head an institute that included a major genetics research enterprise embedded in a large clinical setting, it wasn’t really a choice.

    One day he told his family, “Too bad, we’re coming to New York!” To the surprise of all, they ended up loving the city and enjoying life on the East Coast.

    Dr. Schadt has many reasons to be pleased with his new environment, but one is the ethic of philanthropy that pervades New York. “This city has some of the most philanthropic people I’ve ever met,” he marvels. “Carl Icahn, for example, has given $200 million to Mount Sinai. The impact of a gift like this is without compare.”

    Eric Schadt may be a scientist who is fascinated by the mathematical tools and techniques of big businessmen and money managers, but fortunately for science and genetics, they—Carl Icahn is an example—are fascinated and supportive of him as well.

    With the vast new computational and mathematical tools now available at Mount Sinai, plus the unprecedented financial resources, Dr. Schadt and his institute are on the road to something transformational, something that can touch the lives of every person: faster, safer, more effective healthcare.

    To see a list of Dr. Schadt's top five genomic predictions, click here.


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