Personalized medicine becomes personal for me
I recently had one of the biggest “aha” moments I’ve had in a while. It was an experience that made personalized medicine very real to me.
In early September, our Microsoft Health Asia team attended and presented at Hospital Management Asia in Yangon, Myanmar. While I was there, I had the privilege of meeting many brilliant and forward-thinking people. One of the mornings of the conference, Dr. Andrew Winnington—whom I’d met the previous day and who is the brainchild behind XY Leap, an exciting health IT startup—took a swab of saliva and cells from the inside of my mouth. He put it in a vial, labeled it, and said, “In three weeks’ time, I’ll send you an analysis report that will show you what XY Leap does.”
And sure enough, three weeks later, I receive an incredibly comprehensive report predicting how my body will likely respond to various medications, exercises, and foods given my genetic profile. It predicts my genetic risk of diseases such as Type 2 Diabetes and heart disease and how I can best prevent these chronic conditions. It provides information about how I would typically respond to surgery or injury and the best recovery methods for my genetic makeup. Plus, much more.
The XY Leap analytic platform brought together my genetic data with thousands of medical research papers to derive the predictive insight provided in the report. What’s more, the report is constantly updated as new research comes out. It’s stored online and only I have the ability to access it at this point.
Nothing is absolute, of course. But the report basically tells me that research has shown that other people with similar gene markers have had this level of disease risk, or responded to certain pharmaceuticals, exercises, diets, injuries, and so on, in these ways.
Now that we have the capability to do this type of analysis, what does it mean for the future of healthcare?
Incorporating genetic predictive insight into their decision-making process can help clinicians provide personalized treatment and guidance for their patients. For example, they can use such insight to help them prescribe the most effective medication for a patient’s genetic profile. They can also use it to avoid prescribing a medication to people more likely to suffer from an adverse reaction to it based on their genetic markers as discussed in this recent article in The Atlantic.
As the field of genomics analytics evolves and clinicians become increasingly confident about using it as part of their decision-making processes, how can the right insight be surfaced at the right time for health professionals? In other words, how could this type of genetic guidance for personalized medicine be part of the standard clinical process and built into the clinical applications that health professionals use? How could it be tied together with the patient information that clinicians capture? And how do we make sure that we can simultaneously gather and combine all this personalized information, while protecting patients’ privacy?
As science and technology progress, we’ll need to answer these questions and so many more. But it’s an incredibly exciting future that holds the promise of empowering doctors and patients alike with personalized, predictive insight that could lead to better clinical outcomes, healthier lifestyles, fewer chronic conditions, and reduced medical and drug complications.
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