The Computer Challenge of Personalized Medicine

In the past few years of hearing about personalized medicine, I have usually been told about molecular hurdles that needed clearing. For example, genotyping needed to be less expensive. Today, though, I hear more about the the challenge of using the data, rather than just getting them. In the May 2009 issue of Genome Medicine, for example John Belmont and Amy L. McGuire, both at the Baylor College of Medicine, wrote:

Cost-effective complete genome sequencing for individuals is very close. However, the interpretation and application of the resulting data now loom as critical challenges.

To Belmont and McGuire, those challenges hinge on the electronic health record. Nonetheless, they do not see an easy approach to making electronic health records effective for personalized medicine. For instance, they wrote that there will be:

… a great deal of uncertainty in the interpretation of genetic information because the penetrance of deleterious alleles in the general population is unknown.

Other experts also point out the challenge of handing these genomic data. For instance, Howard R. Asher, president and chief executive officer of Global Life Sciences in San Diego, told Scientific American Worldview that he envisions an automated telemedicine machine—much like a current ATM, but for medical records instead of financial transactions—that collects the needed date. He went on to say:

We could then look at how different drug therapeutics affected different phenotypes and so on. We could look at biomarkers and start harvesting real information associated with real disease. All of a sudden, we would have a goldmine of information that we would trust more when applying it to therapeutic compounds.

So molecular technology seems on the verge of providing the necessary data to make personalized medicine feasible, but hurdles remain between us and putting those data to use. There, both electronic and ethical challenges must be solved before medicine can be tuned for individuals.

Likewise, I suspect that economic challenges lie ahead. Creating a feasible business model of personalized medicine might prove to be the biggest hurdle of all.

To share this with colleagues ...

Close Bookmark and Share This Page

Save to Browser Favorites / Bookmarks