Personalized medicine is a common buzzword these days, usually referring to the use of a patient’s genetic profile to customize an approach to disease prevention, diagnosis, treatment and management. But that definition limits the patient’s role to the molecular level. Personalized medicine should be viewed as part of the broader concept of “personalized health,” which uses genetics, family history, environmental factors and other information to guide individuals – long before they become patients – to make better, more informed health decisions.
At the Health 2.0 conference in San Francisco last week, there was a dizzying array of mobile applications and other innovations on display, all designed to more effectively engage individuals in taking control of their health. The number of developers showcasing new applications in competitive demonstrations is evidence of the booming mHealth market and the creative start-ups who are fueling it.
As we move along the continuum – from evidence-based medicine to information-enabled medicine to intelligence-based medicine – we create the opportunity for truly personalized health.
From controlling stress to managing diet and fitness goals to adhering to medication regimens and communicating with your health insurance company – there’s definitely an app for that and more. Some of the apps even integrate with existing platforms to allow users to create personal dashboards that monitor progress on a number of fronts. I also saw examples of tools designed to improve provider-patient communications, indicating that care is moving beyond the parameters of the traditional office visit.
Technology and social media are also having an impact on drug development and clinical trials. There are literally hundreds of disease-specific online groups where patients can share information, including details on adverse reactions and side effects. Platforms such as PatientsLikeMe are amassing large amounts of real-world, outcomes-based data that can be leveraged to improve the care that patients receive, and the industry is beginning to see value in these nontraditional sources.
There are dozens of public and private initiatives exploring the relatively new field of translational genomics, which employs the innovative advances arising from the Human Genome Project and applies them to the development of diagnostics, prognostics and therapies for cancer, neurological disorders, diabetes and other complex diseases. Genome-based research – such as the study of biomarkers – is already enabling medical researchers to develop more effective diagnostic tools, to better understand the health needs of people based on their individual genetic make-ups and to design new treatments for disease.
I am personally involved in working with the Translational Genomics Research Institute (TGen) to support a clinical trial for pediatric cancer patients conducted by the Neuroblastoma and Medullobastoma Translational Research Consortium (NMTRC). A secure cloud infrastructure – both a high-performance computing resource and a data exchange/collaboration resource – is being used to investigate new technologies that accelerate genetic analysis and identification of targeted treatments for individual neuroblastoma patients. In addition to increasing TGen’s gene sequencing and analysis capacity by more than 1,200 percent, the cloud is also improving collaboration among the researchers and medical professionals working on the trial by allowing them to access massive amounts of information, analyses and results regardless of where they are physically located.
A process that once took months to complete (and often required overnight shipment of hard drives from one clinical site to another) has been reduced to just days – meaning that patients can begin receiving effective, personalized treatments that much sooner. Think how important that is for a child dealing with cancer.
Technology is helping to bridge the gap between patient and provider, science and medicine. We are improving communication, engaging patients in their own care and creating real-time knowledge repositories that will help us identify the most effective treatments for a variety of diseases in the future.
What role do you see technology playing in personalized health?