‘Wonder at scale’: How Johns Hopkins Medicine plans to change the face of disease

The data is big. Its potential to find cures: even bigger.

At Johns Hopkins Medicine in Baltimore, scientists and physicians are collecting and tapping vast amounts of data from clinical care, genomics – even wearable devices – to better predict disease progression and pinpoint individual treatments.

“Precision medicine focuses on using revolutionary tools in measurement, computation and connectivity to reimagine and reinvent medicine,” says Dr. Antony Rosen, director of rheumatology and vice-dean of research at Johns Hopkins Medicine.

At the heart of that commitment to precision medicine, Johns Hopkins clinicians and technologists are peering deep within individual diseases – into the subgroups that comprise those ailments.

That’s because patients in the same disease subgroups likely have the same underlying biology and the same responses to treatment, Rosen says. This, in turn, can help researchers discover the mechanisms driving those diseases.

The team is conducting big data investigations of patients treated for prostate cancer, multiple sclerosis, pancreatic cancer, cardiac arrhythmias, amyotrophic lateral sclerosis, or ALS, and more – all to improve diagnoses, prevention tactics and cures.

“This really is a moment when the tools are going to allow humans to reclassify disease based on subgroups and totally change the face of disease,” Rosen says.

Johns Hopkins is relying on the cloud and machine learning, “to really enable the discovery of wonder at scale,” Rosen adds.

Within those terabytes of cloud data, the medical mission remains focused on patients, says Dwight Raum, chief technology officer for Johns Hopkins Medicine.

“The questions we are asking are generally in two different categories. The first is: How do we determine the best prognosis for this patient?” Raum says. “Where you are now? Where were you six months ago? Where will you be in the future?

“The second dimension is: What are the best interventions? If we know what your prognosis looks like, what are the tools we can deploy for you at different points of your disease?” Raum says. “We are able to use technology, for the first time, to redirect the way we’re providing patient care.”