Predictive Model

Dr. Ryan Lilien of the University of Toronto in Canada will work to computationally model the structural and functional effects of point mutations on a target protein's active site. With the development of predictive models of pathogen evolution and the spread of resistance, this information can be used to guide drug development and optimization.

Aurelius Wakube of Egerton University in Kenya will work to determine geographical patterns in the occurrence of polio cases in Kenya, develop models for predicting future patterns of the disease, and perform genetic typing of the polio strains found in Kenya in an effort to develop effective approaches for eradicating the disease in this country.

Rebecca Katz of George Washington University in the U.S. will identify the most cost-efficient and effective way to integrate the existing mass drug administration program for the parasitic disease schistosomiasis with the control program for malaria in Yemen. Both diseases are widespread in Yemen, but control efforts are currently separate, so combining them would pool financial and human resources.

Diane Joseph-McCarthy of EnBiotix Inc. in the U.S. will use a systems biology approach incorporating gene, protein and metabolic data to computationally model the complex interplay between specific microbes in the gut and the host response, and the effect of phage, to enhance our understanding of pathogenic diseases and identify new treatments. They will use a mouse model of enteropathogenic E.

Christopher Mason of Weill Medical College of Cornell University in the U.S. will generate a global map of antimicrobial resistance by using biochemical and computational methods on available samples taken monthly over one year from 24 developed and developing cities across six continents. Each city will be sampled from both high-density (e.g. train stations) and low-density (e.g. parks) areas.

Simon Reid and colleagues at the University of Queensland in Australia will develop a combined metric using Multi-Criteria Decision Analysis to integrate divergent values on impacts of disease interventions from the agricultural, animal husbandry, and human health sectors. These sectors are involved in addressing similar issues such as disease control, but they each have different priorities.