The Mathematical Sciences in Obesity Research

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Project Summary/Abstract The mathematical sciences including engineering, statistics, computer science, physics, econometrics, and mathematics qua mathematics are increasingly being applied to advance our understanding of the causes, consequences, and alleviation of obesity. These applications go beyond routine approaches easily implemented in available commercial software. Rather, they increasingly involve computationally demanding tasks, development of novel analytic methods and software, new derivations, and an exceptional degree of interdigitation of two or more existing techniques. Moreover, these methods and applications continue to advance; the techniques and questions today are not identical to those from five years ago and continuing to refresh curricula is essential. Advances at the interface of the mathematical sciences and obesity research require bilateral training for investigators in both disciplines. Yet, our existing proven course is, to our knowledge, the only ongoing resource to provide such training by scientists. Our successful five day short course features some of the world’s finest scientists working at this interface to fill the unmet need by providing multiple, topic- driven modules designed to bridge the disciplines. The demand for and success of the course we offered annually for the last five years is evidenced by the facts that over 100 people have enrolled in our course, that over 1300 users have accessed our course video archives, and that over a dozen collaborations have resulted in successful grant applications or peer-reviewed publications from our course participants and faculty. The first module serves as a common orientation for investigators approaching the interface predominantly from a quantitative or obesity lens, followed by 8 modules with topics such as modeling weight change using energy balance, modeling effects in populations, genomic analysis in obesity, modeling behavioral responses to obesity, sensor and engineering models, and scaling laws and obesity. Lectures are video-recorded and posted to our course website for free viewing, thereby extending the reach of our course. Because individuals learn best in complex tasks when they can interact with the material, we include a number of interactive sessions designed to engage the participants in active learning. These sessions include panel discussion, debates with audience participation, question and answer periods, and discovery-based learning activities. These have been refined by us over the prior funding cycle to be those that best serve and are most highly appreciated by our participants. Senior faculty offer lectures and lead small group and individual consultations with participants on topics such as grant acquisition and navigating an interdisciplinary career. The new Mathematical sciences in Obesity Research Excellence (MORE) Prize will engage participants beyond the course to identify an outstanding publication on quantitative obesity research to be honored at the following years’ course. The NIH and the scientific community at large have voiced the need for more training at the interface of the mathematical sciences and key biomedical domains, and we request the opportunity to continue to be part of the solution.