Marzieh Nabi

“When this perfect storm of data fusion occurs, it will forever change how medicine is practiced.” – Marzieh Nabi, research scientist and technical lead at PARC, A Xerox Company

By Marzieh Nabi

Precision medicine matches medical treatment and prevention plans with a person’s specific DNA make up, as well as lifestyle and environmental variables. It’s still a vision, but it stirred up a lot of buzz at a recent conference of the Healthcare Information and Management Systems Society (HIMSS).

As a research scientist, I am particularly interested in what we can learn from analyzing the data in electronic medical records, and how chronic conditions in any particular patient are related. I am at the heart of some of the challenges in working with clinical data.

That’s why one thread at HIMSS that caught my interest was the idea of integrating the record of a person’s complete set of DNA (genome) with electronic medical records. When this perfect storm of data fusion occurs, it will forever change how medicine is practiced. Treatment and prevention plans will be more precise; individually tailored to your exact physical make up.

Sequencing human genomics is becoming more affordable, and research is expanding. Avera Health, for example, is conducting big experiments in the new field of pharmacogenomics, the study of how genes affect a person’s response to drugs. Startups such as Syapse have created software that allows healthcare providers to integrate genomic information into medical records, and use insights to diagnose, treat and track a patient’s health.

Here are just a few of potential gains from integrating medical records with genomics:

  • Treat rare diseases.
  • The right care at the right time with the right treatment path.
  • Efficient prevention plans.
  • Match the right medications to the right patients.
  • Minimize side effects and adverse effects of the medications.
  • Validate and explain complex causal relationships between comorbidities(the co-occurrence of multiple chronic conditions).

Much work remains. Solutions must account for inconsistencies and uncertainties in the data, protect patient’s privacy and secure the data. We must yet figure out thoroughly how predictive and prescriptive analytics can develop more efficient prevention and treatment plans.

Early last year, President Barack Obama unveiled $215 million plan to collect genetic information from a million American volunteers. The goal is to develop personalized genetics-based medical treatments. A few months later, the National Institutes of Health announced funding for research to integrate genomics into electronic medical records.

On the heels of these announcements, the excitement around personalized medicine seemed to outpace the science. But from what I saw at HIMSS, that’s changing fast.