Opinion: Predicting Perfect Storms

SXC.HU, SACHYNLong before Hurricane Sandy made landfall on the US Atlantic coast last October, meteorologists had predicted its course and likely impacts. Although the storm caused enormous damage, the early warnings allowed people to prepare or evacuate areas that were directly in its path. If the storm had caught coastal residents completely by surprise, there is no doubt that the death toll and devastation would have been far worse. The development of computer simulations of weather has transformed our ability to predict the severity of “perfect storms” like Sandy. The accuracy of these predictions is based on the simulations’ ability to piece together many different kinds of data—including air pressure and temperature, water temperature, wind speeds, and ocean currents—into a faithful model of the extremely complex phenomenon that is weather. Within the last decade, computer simulations have similarly revolutionized the fields of mechanical design, finance, ecology, and aerospace operations, among many others. Brain disorders like multiple sclerosis (MS) are “perfect storms” too. They should, therefore, be amenable to similar computer simulations. In MS, genetics, environment, and hundreds of other factors come together to elicit the immune system attack on neurons of the brain and spinal cord, which are hallmarks for the disease. The issue is that we don’t yet understand how all these factors integrate to form a consensus map and a comprehensive picture of the disease. Thus, despite the impressive efforts of global academic research centers and patient advocacy groups to gather data from people with MS, we still have a very limited understanding of how MS works, who will develop it, or what it might do next. Trying to predict the course of MS—or any complex disease—based on a few kinds of disconnected data is like trying to track a hurricane by measuring air temperature and wind speed alone. How can we get there? We are now at a unique crossroads in biomedical research history. Advanced technologies such as gene sequencers and functional and volumetric MRI have given us access to an unprecedented amount of biological information. Mobile technologies now enable patient engagement and deep profiling of the disease experience. Biosensor nanotechnologies can give us real-time readouts on environment. Meanwhile, the revolution in high-performance computing has provided us with the ability to make sense of all this information and turn it into predictive disease models—disease maps we can actually use. At the same time, scientists everywhere are embracing a more open, collaborative approach to research that transcends the walls of individual laboratories and builds connections across disciplines, geographies and industries. Like forecasting weather, the solution for predicting the storm of MS is the establishment of a global, virtual network of sensors and experts that feed information to supercomputers and computer modelers to enable the interpretation of complex data at the speed of thought. Earlier this year, we at Orion Bionetworks launched a cooperative research alliance committed to transforming the study of brain disorders such as MS and accelerating the discovery of new diagnostics, treatments, and cures. The success of this enterprise depends on building a growing community—or network—of organizations that will contribute to every aspect of the research. New partnerships and community-building efforts in the pharmaceutical and biopharmaceutical industry provide data and funding support, while collaborators who specialize in building sophisticated computer models of brain disorders offer technology and expertise. Information technology partners help create access, plus integrate and handle enormous volumes of data. Patient advocacy partners provide long-term data from people with MS, as well as help define long-term research goals. Lastly, partners in academic and government laboratories will help validate our simulations and generate new data to improve the predictive power of this approach. The foundation of such a network is the assembly of many different types of data—from gene activity to daily symptoms and response to medicines—from people with disorders like MS to determine how they are connected. After integrating the data, we build computer simulations that will allow clinicians and researchers to predict how disorders like MS will affect an individual. Our first MS simulation has already generated insights into novel MS-associated genes already known to be important in other CNS disorders. We are now launching pathway analysis studies to interpret what functional role these genes may have. Much as weather models allow the mitigation of storm damage, we hope to improve how we care for people with MS, and making the search for new therapies less expensive and more productive. It’s time to embrace the full potential of technology and scientific collaboration. By forming communities dedicated to using supercomputing and big data to understand MS and other brain disorders, we can achieve what’s been done with weather prediction, and then some. Unlike the weather, which we cannot change, we may be able to use these powerful new disease research tools not only to predict the approach of the perfect storm, but possibly to stop it entirely. Magali Haas is the founder and CEO of Orion Bionetworks.