In the first of a three-part series on how technology is transforming healthcare, Greg McStravick, GM and global head, SAP Platform GTM, takes a look at the potential of personalized medicine. Technology has the potential to create real value, but short-term challenges are significant. Find out more about technology and healthcare challenges and opportunities in Parts 2 and 3:
- Part 2: Personalized Medicine and Big Data–Opportunities and Pitfalls of IT Innovation
- Part 3: The Risks, Challenges–and Rewards–of Ensuring Medical Data Privacy
As we observe National Heart Month (#NationalHeartMonth) this February, it is both encouraging and exciting that a new effort is underway to create tailor-made medicine and medical treatments by drawing on exceptionally detailed and extensive biomedical data. The effort is ambitious and challenging–and possible. The goal: wide availability of personalized medical care (aka precision medicine) that can be customized based on an individual’s genetic makeup and other factors.
But collecting this level of personal health care information, while it holds the possibility of game-changing personalized drugs and treatments, is not without major challenges–including those in the realms of patient privacy and data storage. Highly individualized diagnosis and treatment available on a large scale requires collection and management of petabytes of data, including but not limited to patient histories, genetic data, data from wearable health monitors, and information on individual microbiomes (bacteria, fungi, and viruses in and on the body). Privacy is of utmost concern, and even current big data standards could be strained by massive amounts of genetic data.
The possibilities are compelling, and the upside is huge. But personalized medicine is a challenge with real, difficult, and perhaps intractable problems attached.
Are we there yet?
We’ve been able to sequence the human genome for about 15 years. In certain specialties, such as oncology, we’re already seeing tremendous advancements thanks to genometrics. Cancer used to be thought of in terms of a cell gone wrong that affected the tissue around it, with treatments based on affected area – for example, lung, breast, or skin. Now, researchers are looking to treat each mutation by responding to its genetic fingerprint. The same treatment might be applicable regardless of the organ or tissue affected, and, for example, one patient’s lung cancer treatment might differ from another’s due to genetic differences in each person’s mutation.
However, along with important breakthroughs and new therapies to treat formerly untreatable diseases, we’ve also seen the need for exponentially more complex understanding – from not just researchers but front-line doctors. Now that we can sequence the DNA, we must understand and transcribe epigenomes, proteomes, metabolomes, and more. This poses a huge challenge for on-the-ground medical personnel, including primary care providers and specialists whose focus is broadly defined quality care.
Friend or foe?
The majority of physicians believe that personalized medicine will eventually create real value for individuals as well as entire populations. But in the short term, what will the average family practitioner get for her efforts? Physicians are under stress, working more and seeing patients less. Many doctors have just completed mandatory transitions to electronic medical records (EMRs), which has required more work but yielded little in tangible results. Privacy laws, insurance paperwork, and the shift to value-based pricing are requiring more data input and creating more hoops to jump through, lengthening the workday but providing minimal tangible value for patients and doctors. The fear here is that personalized medicine could mean more of the same for the vast majority of providers. Would primary care doctors need to verify even more information when a person is sick, taking into account all the additional characteristics that drive a doctor toward different therapies? Will all the new inputs yield equivalent benefits?
Outside the office
I believe that in order for personalized medicine to take off, we’ll need to capture not just genomic information, but accurate information about individual patients that falls well outside current hospital or clinical settings. How do patients live in their homes? What do they eat, drink, and smoke? What’s their documented level of physical and social activity? And even more important, how do we engage patients, especially those with chronic illness, in ways that support real change of unhealthy habits? I believe that for personalized medicine to reach its full preventative potential, the medical profession will have to engage with patients in their homes.
Also, correlating such lifestyle data is critically important to understanding and applying genomic data when predicting risk factors for certain diseases. But how will this lifestyle data be captured and stored? What infrastructure will be needed, and how will it be funded? Before we can consistently, accurately, and cost-effectively collect this data, we need a technology infrastructure and payment model in place.
Best practices: A final challenge
It can be a major challenge for the medical profession to implement best practices. Even when best practices are proven in controlled, randomized trials, it has often taken up to 20 years for a practice to be consistently adopted. Given this challenge, for personalized medicine protocols to really work for–and be consistently adopted by–doctors, they must:
- Be time-neutral
- Integrate into current workflows
- Drive clear value for both doctors and their patients
It’s only when we address all these challenges–both technological and human-based–that we will be able to truly take advantage of the benefits that personalized medicine can offer.
Learn more about the SAP Foundation for Health and Personalized Medicine
SAP is passionate about creating transformative technology that can advance healthcare. The SAP Foundation for Health includes a sophisticated platform and advanced analytic solutions that can help unlock the value of biomedical data–from genomes to electronic medical records to clinical trials. Supporting deeper insights and enabling collaboration, the SAP Foundation for Health helps connect data silos and bring together mission-critical biomedical data, advancing personalized medicine to new levels.