Top 5 pathways to personalized medicine
'Medicine is becoming synonymous with big data -- the data sets are just huge, now'July 22, 2013
If there’s one thing everyone in healthcare can probably agree on right now, it’s that there is an awful lot of data being generated each and every day. What to do with that data, however, is another question.
As Ted Driscoll, digital health director at venture capital firm Claremont Creek Ventures, sees it, the explosion of data is a definite boon for personalized medicine. Indeed, he said recently, “Medicine is becoming synonymous with big data – the data sets are just huge, now – but we had to wait for the IT revolution to happen and mature” in order to begin to put that data to use.
So how does he see big data facilitating the rise of personalized medicine?
- We’re able to make better and more specific diagnoses. “Tumors aren’t just lumps, anymore,” he said. “they’re a specific type of cancer.” That is, no longer are providers relegated to diagnosing cancers in general terms. Given the ability to determine what’s actually going on at a molecular level, Driscoll said, diagnoses can be much more precise.
- We’re able to prescribe better targeted therapies. With better diagnoses come better treatments. “Now that we understand the recipe for life,” Driscoll said, “we can develop more precise rifle shots to address disease. We can determine which drug will work with each individual patient, and we don’t have to settle for trial and error medications.”
- We can make better early predictions and determine predispositions. A big part of an individual’s health data, Driscoll suggested, involves “understanding what you’re starting out life with.” That is, genetic data, which can be collected even prior to birth via non-invasive pre-natal testing, can be used to determine what diseases a person may be more susceptible to over the course of his or her life. Which, of course, leads to the potential to offer pre-emptive treatment so the disease never develops.
- We can expect better development of generalized therapies. “We’re not going to end up with individualized headache pills,” Driscoll cautioned, “but we will be able to develop better drugs for a broad class of people” by looking at actual genetics that form the foundation of predispositions. Moreover, citing the example of an anti-epileptic drug that has been found to work in treating colitis, Driscoll said mining data to understand the particular structure of each disease will lead to greater understanding of where diseases overlap, which will lead in turn to the more precise use of a broader range of medications.
- We can engineer genetics. The future, Driscoll said, will involve not just reading and understanding genetic structures, but actually modifying them. Of course, he noted, every disease is different. “There are certain diseases that you can identify with just a genetic snip you can tell, while other diseases are determined by thousand of genes. The fact is, we’ve only begun to read the recipes.” That said, Driscoll said mining ever deeper into the mountains of data that will continue to pile up will facilitate inevitably result in medical assessment and treatment tailored to the circumstances and needs of individuals.
To be sure, Driscoll said, the road ahead will have no shortage of legal and ethical challenges as genetic information becomes more readily available, but “In the end, doctors want to know as much as possible to deliver the best treatment they can.”