Personalized medicine has arrived and it’s about more than just completing genome-wide association studies. Personalized medicine is about using patient data to connect the right patient with the right treatment at the right time.
It’s the practice of:
- Developing targeted diagnostics and therapeutics based on an individual’s genetic profile and other clinical and demographic information
- Improving patient outcomes by reducing the potential for adverse drug reactions
- Eliminating ineffective treatments, and
- Focusing on the most effective treatments and therapeutics
From blockbuster drugs to targeted disease discovery and treatment, we are now entering the era of personalized medicine where technology is enabling the analysis of vast, complex layers of genomic, proteomic, clinical and environmental patient data, to identify the mechanisms of disease and the right treatment for every patient. We at GNS Healthcare believe this is the future of medicine – predictive, personalized and technology-driven. (For detailed outline of the opportunities associated with Personalized Medicine, visit PWC report)
Personalized medicine has become a reality through increased data access and the pressing need for more effective treatments. It’s no longer sustainable or ethical to treat patients with expensive, ineffective interventions. Technology has evolved to help identify biomarkers and allow sophisticated patient modeling to create safer, more effective therapies. Learn how GNS Healthcare and Biogen Idec collaborated to identify novel, patient-specific drug targets for Rheumatoid Arthritis (RA) from genetic data.
Why Personalized Medicine Now?
The healthcare industry has been awash with data for years: from biological data such as gene expression, SNPs, proteomics, metabolomics and more recently next generation gene sequence data to patient data such as clinical insights, prescription claims, and demographic information. While the healthcare industry, from Big Pharma to payers to hospitals, certainly suffers from no shortage of data, until now it has not been data-driven or enabled.
But thanks to the continuation of Moore’s Law coupled with advanced machine learning development, we are at the dawn of a new era in personalized medicine where we can interpret massive, disparate data sets in parallel to drive the more efficient delivery of healthcare and improve patient outcomes. Personalized medicine goes beyond just genomics- it’s about understanding how all the variables are interconnected and uncovering the right intervention for the right patient at the right moment.