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About Computational Modeling

Just as weather simulation programs have dramatically improved our ability to track and prepare for major storms, powerful computer simulations of brain disorders - based on many types of integrated data (see below) - will transform our ability to predict who will develop diseases like multiple sclerosis (MS), how the disease will progress in a particular person, and who is likely respond to specific medicines.

Predicting the weather requires collection of many kinds of data over time, from wind speed to ocean temperatures. These data feed into high-performance computers, where sophisticated algorithms (mathematical models) simulate scenarios like the probability of a hurricane.

Similarly, to develop predictive computer simulations of brain disease, many sets of data that provide a comprehensive picture of the disease need to be collected over time. These data include clinical measures (e.g., disease worsening), biomarkers (e.g., genes and proteins), imaging (e.g., MRI), and measures of impact on the individual (e.g., ability to do everyday tasks). Computer modelers then convert the data into powerful simulations of disease to predict disease course and response to medicines, as well as identify potential new targets for treatment.

As new data are collected and added to the disease simulations, their predictive power - and their value as research tools - will grow. This has the potential not only to change how we care for people with brain disorders, but also to speed the development of new ways to diagnose, prevent, treat, and potentially cure them.

Further Reading