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Personalization in practice

Dynamic computational modeling integrated with experimentation can enable precision medicine Last month, an advisory committee released recommendations for recruiting at least 1 million individuals to participate in the U.S. National Institutes of Health's Precision Medicine Initiative. This bold approach to disease treatment and prevention seeks to account for an individual's genes, environment, and lifestyle to improve health outcomes. The ability to collect, integrate, analyze, and model relevant data streams is central to this effort. Moving beyond “just” massive data collection will require structured convergence among various disciplines. So, how should data be gathered? Here, computational modeling can be a useful guide. Modeling at the molecular, cellular, tissue, and organismal level will be essential to identify the molecular interactions that underlie progressive diseases and to generate a comprehensive and dynamic picture of the individual.