Int. J. Environ. Res. Public Health 2009, 6 508 A fourth area that could be increasingly important to consumer personalized medicine is predictive biosimulation. This is using empirical biological data and mathematical modeling to create an electronic version of an individual, a virtual patient on which to test simulated treatments. Predictive biosimulation is not targeted at consumers yet, other than in the case of a few high-price pilot projects, but could become a valuable personalized medicine technology for individuals. An example of the virtual patient biosimulation is shown in Figure 11, illustrating the baseline case (x-axis) as compared to the expected improvement from a potential intervention (diagonal line). Creating a low-priced or open source version of predictive biosimulation platforms for the self-tracking and software development communities could speed adoption and draw upon the wisdom of crowds to find useful relevant applications as people plug in their various forms of self-obtained data to generate future health scenarios. Two existing predictive biosimulation and virtual patient technology companies are Entelos (http://www.entelos.com) and Optimata (http://www.optimata.com). In December 2008, the U.S. Food and Drug Administration (FDA) announced plans to use the Entelos biosimulation technology to study three heart-related drugs to identify safety and effectiveness issues before the completion of late-stage human trials by testing far more simulated patients than could be included conventionally and obtaining computer-generated test results in days or weeks instead of years [19]. 2.3. Quantified self-tracking 2.3.1. Quantified self-tracking introduction The increasing ease of capturing, storing and manipulating data has given rise to a variety of websites for sharing datasets and visualization tools, for example IBM’s ManyEyes (http://manyeyes.alphaworks.ibm.com/manyeyes), used here to visualize this paper (Figure 12, word use frequency is indicated by font size), Swivel (http://www.swivel.com) and FlowingData (http://flowingdata.com). In the past, the cost and expertise required for working with large-scale datasets and visualizations generally limited access to institutional professionals, but cost decreases and tool improvements have made data collection and manipulation more available to the individual. Figure 12. Many Eyes data visualization of this paper. One of the most interesting areas for individuals to measure is the self. At least two interest groups formed in the second half of 2008 to explore, brainstorm and share their self-tracking experiences, the Quantified Self group (http://www.quantifiedself.com) in the San Francisco area and the HomeCamp