Among the biggest challenges to the widespread adoption of “big data” tools in healthcare is that many in the industry simply don’t know what valuable secrets the data could hold.
In other words, “People don’t realize what’s possible with all the big data we have, so no one even asks the question,” said Tim Kulbago, CEO of imaging clinical research organization ImageIQ, a Cleveland Clinic spinoff that “extracts scientific data from pictures.”
Kulbago shared an example of a pharmaceutical client that’s developed a drug to treat polycystic kidney disease. The pharma company supplied ImageIQ with terabytes of images from its clinical trials, and asked the CRO to figure out why its drug works and exactly what’s happening to patients who are treated with it.
From that mountain of images, ImageIQ’s software has been able to extract data to describe the number of cysts, as well as their dimensions, shape and growth rate, Kulbago said.
In general, the pharma client didn’t know that it was possible to obtain that type of data from the medical images – an obvious limitation that could’ve prevented the drug developer from ever deriving any sort of benefit from those terabytes of images.
“People don’t even know that they can ask the question,” Kulbago said. They have little knowledge of “the art of the possible.”
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
Once the health industry learns that’s its possible to get answers to some questions it previously didn’t know to ask, the potential impact of big data on healthcare could begin to be realized.
