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FIGURE 3-1 In silico modeling of disease mechanisms for drug development.
SOURCE: Ramon Felciano. 2011. Presentation at IOM workshop; AdvancingRegulatory Science for Medical Countermeasure Development.

and holistic, Felciano said, using computer-based tools and techniques to model and understand complex biological function. Experimental designs are typically comparative in nature (e.g., healthy versus disease, disease versus treatment, dose response). The complexity and volume of the data that are generated by these approaches typically require fairly sophisticated computational and statistical modeling for analysis and prediction. Research teams are often interdisciplinary by necessity, with therapeutic area researchers, computer scientists, statisticians, and others working together.

Primary benefits of this approach, Felciano said, include better understanding of disease progression, generation of novel hypotheses for therapeutic or diagnostic targets (i.e., biomarkers), and characterization of plausible mechanisms that correlate with these diagnostic and prognostic markers.

Compared with other therapeutic areas, there has been relatively little research done in the area of MCMs using a systems biology approach, Felciano noted. He cited one retrospective study of yellow fever vaccine that



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