As precision medicine evolves, scientists are learning that the human genome map they’ve been using is limiting their ability to provide truly custom medicine. How could this happen with a $3 billion program?

The problem is that the genome map sequenced only represents one way a person’s genome could look. It doesn’t rule out the 3 billion variables and combinations with them that scientists have to consider!

How do they plan to solve this? The simple answer: hardcore mathematics to reach a conclusion, and advanced supercomputing to crunch all the data.

There’s a technique scientists plan to employ called “graph theory.” With it, they can map out every possible alternative of the human genome within man’s 46 different chromosomes. The end state is to find the best path through the genetic letters that match your own.

This will make precision medicine even more precise. With so many path options to consider, scientists will have better references to issue custom medicine based on an individual’s genome. Right now, they’re still using that dated genome map from the early 2000s. Eventually this will lead to a new standard for meeting a patient’s exact medical needs.

A geneticist from the University of Utah even thinks this technology will be mainstream within the next five years!

Right now, there are a number of academic and commercial institutions becoming involved in this advanced technology, including genetics firm 23andMe, which Google has their eye on.

I’m expecting this cutting edge technology to deliver some exciting market plays as it gets some serious financial backing. You can follow along in those market plays in my BioTech Intel Trader service.

As always, I will continue to monitor the market’s latest health and biotech technology trends via my social media collective intelligence tool and keep you updated on the latest.

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Ben Benoy

Editor, BioTech Intel Trader

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Ben Benoy
Ben Benoy is a veteran of the U.S. Marine Corps and has been an active retail trader since 2006. He identifies investment opportunities based on key social media trends. He first identified the concept in 2008 and has since developed a tool for tracking investment “chatter” between social media users. His proprietary Social Media Stock Sentiment system has developed into a state-of-the-art platform that identifies and classifies chatter about stocks through algorithms and other indicators to forecast stock-price direction. Ben’s track record speaks for itself — over the past 12 months, his system boasts a win rate of 82.2% on 112 stock trades.