BioScreen Takes the Guesswork Out of MS Treatment Plans

Researchers at the University of California, San Francisco (UCSF) are developing an application called BioScreen to compile data culled from the past decade’s worth of multiple sclerosis (MS) studies. Inputting genetic profiles, brain images, and medication history from volunteers, a statistical picture of MS patients as a group is beginning to emerge.

MS is an unpredictable disease, and no two people experience the same symptoms or level of disability. Just 20 years ago, there was no effective treatment for MS. Patients were diagnosed and sent on their way, powerless to alter the course of their disease.

Now there are 10 disease modifying therapies (DMTs) to choose from, but no clear criteria on which to base that choice. It can be a confusing and frustrating process for doctors and patients alike, as the only way to assess the proper therapy was through trial and error.

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Stephen Hauser, M.D., Chair of Neurology at the UCSF School of Medicine, and his co-investigator Pierre-Antoine Gourraud, Ph.D., MPH, have been gathering data from 800 patients over more than eight years. The enormous amount of information they’ve compiled resides in a database. Using an algorithm they developed, BioScreen processes the data into a visual interpretation of the MS population as a whole, allowing individuals to compare their symptoms and disease course to those of other patients.

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There Will Soon Be an App for That!

Originally, BioScreen was developed to aid researchers, but the UCSF team is partnering with the Patient-Centered Outcomes Research Institute (PCORI) to make the tool accessible to all.

The application will empower patients and their doctors in the decision-making process. Similar to the chart used by pediatricians to plot where your child falls within average growth percentiles, BioScreen will give patients an idea of how their disease measures up to that of others with MS in a user-friendly, interactive format.

“With BioScreen, we can say, ‘We have five possibilities for picking a drug for you. Let’s look at patients who two years ago were at the same stage as you now,’” Gourraud explains in a press release, “Your personal decision is now informed by real data. The more patients we add to the BioScreen, the more this evidence base will grow—and the more accurately we can predict the future of every patient.”

Though the focus of this project is MS, the researchers are excited about its implications for other chronic conditions as well. Combining all the known variables and measurements taken from patients could reveal hidden clues about disease and point the way to new research strategies.

Where medicine, technology, and big data intersect, amazing gains are ripe for the taking.

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