Why Precision Medicine?
In the world of medicine, trial and error is largely the norm today. Doctors make a “most likely” diagnosis consistent with symptoms and prescribes treatment accordingly — treatment that might include drugs, devices or surgery. If the treatment doesn’t work, the doctor most likely alters dosage or prescribes something else. This iterative cycle is repeated until the diagnosis and treatment present the desired clinical outcome.
The bad news is that this paradigm has reached a point of diminishing returns, as evidenced by the fact that most drugs prescribed in the United States today are effective in fewer than 60% of treated patients! The good news is that new technology could transmute trial-and-error medicine, replacing it with an evidence-driven paradigm — one where each and every patient receives care, medication and treatment predicated on his or her unique genomic profile and attributes thereof.
I was first introduced to this concept many years back by Dr. Raju Kucherlapati, Professor of Genetics at Harvard Medical School, and one of the ‘preeminent thought leaders of Personalized Medicine’ in the US and across the world. Dr. Kucherlapati founded the ‘Personalized Medicine Conference’ at the Harvard Medical School, a seminal event that drew practitioners, thought leaders and aspirants from all over the world to Harvard Medical School every year to learn about the state-of-the art of Personalized Medicine. I was fortunate to have been invited by Harvard Medical School and the Partners Healthcare Center for Personalized Medicine to attend and author the official summary of the 2010 Personalized Medicine Conference, that paved the way for my learning, and my ongoing fascination for this “disruptive innovation in healthcare” that can rightfully be called ‘the Holy Grail of Medicine’ [1, 2].
President Barack Obama has championed ‘Precision Medicine’ in a recent state of the union address, and has funded the ‘Precision Medicine Initiative’ to support and transform this paradigm from the laboratory to the patient bedside.
So how does one define ‘Personalized or Precision Medicine’?
‘Precision Medicine’ is essentially the ability to tailor treatments, as well as prevention strategies, to the unique characteristics of each person. Meanwhile, the closest real-world analogy to this process would be a recruitment system that matches a person’s job to his or her education, experience and skill sets as laid out in a profile (ahem, resume) to ensure the best fit for the job.
How does Precision Medicine work?
The first step of precision medicine is mapping a person’s genomic profile. Then, by analyzing and correlating vast pools of genomic data, researchers and doctors can identify variances and bio-markers for potential diseases, that will shape what treatment is best, assuring the best therapeutic outcome with minimal adverse effects. This type of treatment is made possibly by genomic profiling platforms, electronic health records (EHRs), analytics tools for self-service data discovery, visual and predictive analytics with machine learning and other new tools.
In recent years, precision medicine has attracted significant hype and sometimes pessimism from a number of quarters (including, perhaps unsurprisingly, the pharma industry). It’s sometimes perceived as “avant garde” –– a grandiose vision that is way out there and not yet ready for useful value delivery to real-world patients and consumers. But considering we can already move beyond a real-world analogy to real-world examples, it’s clear that precision medicine holds promise and is poised to continue replacing the old-school trial-and-error approach.
Where is Precision Medicine being applied today?
One of the preeminent areas of application of Precision Medicine for personalized healthcare delivery, pertains to the diagnosis and treatment of Cancer. When it comes to cancer, personalization can take several different forms such as:
* Looking at the person’s genomic profile to determine if he/she has certain genetic mutations that could put them at a higher risk for developing cancer, and whether they can handle specific drugs and treatment protocols, or
* Testing a patient’s tumor or cancer to figure out the best treatment protocols that will deliver the optimal outcomes
One real-world example comes with regards to breast cancer treatment. Certain kinds of breast cancer are not candidates for chemotherapy alone. But Herceptin — a monoclonal antibody delivered by Genentech (often recognized as the pioneer of the bio-tech industry) — has been found to be particularly efficacious as a first-line treatment chemotherapy for aggressive forms of breast cancer in women whose tumors have an overabundance of HER2 — a protein that promotes cell growth [1,2].
Herceptin has been found to reduce the likelihood of cancer spreading to other parts of the body in such patients by a remarkable 53% compared with traditional chemotherapy alone. This is compelling from both an outcomes perspective and a cost-benefit perspective. The tests to detect whether a breast cancer patient has an overabundance of HER 2 protein (and thereby is a candidate for Herceptin) cost a mere $400. Plus, the test potentially saves thousands of dollars by preventing the cancer in HER2 patients from spreading to other parts of the body and by not treating HER2-negative patients with a drug that won’t do anything.
“In essence, this kind of precision medicine means the “mass customization” or the “targeted treatment” of cancer.”
Case Study: Precision Medicine at the Inova Translational Medicine Institute (ITMI)
Another game changing example comes from the Inova Translational Medicine Institute (ITMI) located in Virginia, which is at the forefront of precision medicine delivery in the United States. ITMI captures genomic profiles of every new born infant and their parents, then analyzes these for variances and mutations using visual analytics software from Tableau Software. By visualizing the data, doctors can proactively identify bio-markers for chronic diseases like heart disease, COPD, Cancer, Alzheimer’s at birth. This helps physicians and clinicians tailor the treatment each infant receives.
Personalized Healthcare at the Inova Translational Medicine Institute (ITMI). Video courtesy ITMI and WUSA 9.
A biomarker is a biological molecule found in blood, tissue or body fluids that can be used to identify the presence of an abnormal process or disease. For example, a biomarker may be secreted by a certain type of tumor, or it could be a physical response by the body’s immune system to the presence of a tumor. By identifying biomarkers, researchers and physicians can determine whether a specific treatment is appropriate for a specific tumor type and track their ongoing presence or absence as a measure of how well the body responds to a treatment .
ITMI is also a leader with regards to integrating genomic data with patient information from their Epic Electronic Medical Records (EMR). This helps ITMI track progress over time to ensure that chronic diseases can actually be prevented before they occur, which is key to bending the cost curve.
Figure 1. A map view using Tableau Software, of where Inova patients are born, allowing researchers to view where exactly their patients are coming from, and giving them an idea of potential environmental factors in their diagnoses .
These are just two examples that show how precision medicine can have a tangible impact — not just on health and outcomes, but on cost. And as already demonstrated, healthcare IT and analytics — including EHRs, self-service data discovery, visual and predictive analytics leveraging machine learning– are core and mission critical to making precision medicine a reality.
I had the good fortune of being invited to speak on a thought leader panel discussion on‘Genomics and Precision Medicine‘ at the ‘Digital Health Summit’ at the CES in Las Vegas in January 2016, (the largest consumer electronics show on the Planet – see below) with Aaron Black, Director of Bio-Informatics at the Inova Translational Medicine Institute (ITMI) that was very well received.
Here is the video recording of the panel discussion below for your reference.
Panel Discussion: ‘Look Who’s Talking: Newborn Genomic Data Enables Precision Medicine’ @ Digital Health Summit CES 2016, featuring Aaron Black, Director of Bio-Informatics at ITMI, and Andy Dé
How can ‘Patients Like Us’ leverage Precision Medicine to improve Health and Wellness?
Given advances in sequencing the Human Genome, it is feasible today for any patient to order a genomic profile for providers like 23andMe or Veritas Genetics based on a saliva sample, for around $ 1000 or less ($ 199 for 23andMe). Other companies that offer similar genomic profiling services at a comparable price point include Illumina,and Sure Genomics.
Veritas, a spinoff of a non-profit call the Personal Genome Project, founded at Harvard University, can deliver your genomic profile on an iPhone app (see figure below), from a test ordered by your doctor, and you will need to undergo a genetic counseling session on the phone or thru the app. [6, 7]. It will include all six billion letters of a person’s genome, analyzed by an algorithm to highlight medical predispositions. Consumers would learn facts ranging from the silly (is their earwax wet or dry?) to the potentially scary, like whether they have “highly pathogenic germ line mutations” that cause things like malignant hyperthermia. They’ll also learn whether their genomes harbor mutations in 150 genes linked to cancer susceptibility, such as the BRCA breast cancer genes [6, 7].
Figure 2. The Veritas MyGenome App with your genomic profile enabled thru a $ 1000 genomic profiling test and analysis. Source: Veritas Genetics.
By sequencing your entire genome, you’ll not only be able to utilize what you learn about your health today, but also for years to come. In future, you can refer to your genetic sequencing to stay on top of any health issues you may have or are concerned about having. Parents will know what inherited genetics they may pass on to their children. And, someday soon, it is entirely within the realm of possibilities we’ll all be carrying full genome cards and using them to select our food, personal care products, and fitness routines.
How can Precision Medicine enable Population Health Management going forward?
One of the fundamental tenets of healthcare reform and the affordable care act (ACA) has been the transformation of the economically unsustainable ‘fee-for-service’ model into a ‘pay-for-performance’ paradigm that indeed has far reaching implications for the healthcare delivery system in the US. Key to this paradigm shift has been the advent of the ‘Accountable Care Organization’ (ACO) responsible for ensuring population health management (PHM).
According to the Centers for Medicare and Medicaid Services (CMS), Accountable Care Organizations (ACOs) are groups of doctors, hospitals, and other healthcare providers, who collaborate voluntarily to deliver coordinated high quality care to their Medicare patients. It can also be defined as a set of health care providers—including primary care physicians, specialists, and hospitals—that work together collaboratively and accept collective accountability for the cost and quality of care delivered to a population of patients. This in essence is the concept of population health management (PHM) – collaborative and accountable care delivery and interventions to defined groups of individuals across the continuum of care with the express objective of improving their health and wellness at the lowest cost of care delivery [8,9].
“From a healthcare provider perspective, PHM can also be defined as an overarching set of capabilities which support the delivery of and adherence to evidence-based and integrated clinical care activities tailored to individual patients and populations.”
In my previous blogpost, ‘The Six (6) Pillars of Population Health Management’,  I have articulated a pragmatic healthcare IT (HIT) framework for enabling population health management.
In my blogpost, “Retail inspired Innovation in Population Health Management‘ , I have articulated how Healthcare can learn from best practices in retail for customer segmentation, to stratify patients using a risk based approach for population health management.
In this perspective, I will present my vision for how Precision Medicine can be deployed as a strategic enabler of Population Health Management (see figure 3 below) using the Inova Translational Medicine Institute (ITMI) best practice example above.
Caveat emptor: while this model may not be deployable at scale today, it is not far fetched to imagine that this is feasible at scale over the next ten years.
Figure 3 . Precision Medicine as an enabler of Population Health Management. Copyright Andy Dé. All rights reserved.
The current model for a ‘Risk based approach to Population Health Management’ being embraced by many industry leaders today, is illustrated in figure 3 above.
Strategic: Population Health Segmentation (PHS) and Community Health Assessment (CHA) is critical to assess the state of health of the population being served. Community Health Assessment (CHA) that is also referred to as ‘Community Health Needs Assessment (CHNA) refers to the process of community engagement, collection, analysis and interpretation of data on health determinants and health outcomes, health disparities, and identification of resources to fulfill these needs and ensure superior patient and population health outcomes. The CDC has identified and articulated 42 metrics for health determinants and health outcomes that if measured and analyzed, will provide healthcare providers with an accurate blueprint of the health of the population being served. These can then be leveraged to segment the population based on risk and cost to serve, to drive a pragmatic PHM strategy to deliver the highest quality of care cost effectively while managing risk [8,9].
Tactical: Patient Risk Stratification (PRS) using a risk-based management approach: is arguably, one of the most challenging aspects of PHM, demanding sophisticated machine learning, advanced predictive analytics software leveraging complex models to predict risk not only at an aggregate population level, but also at a discrete patient level. Leveraging solutions like JVION, industry leaders are stratifying their patients based on 30 day re-admission rate risk, risk of overshooting their length of stay (LOS) and other key performance indicators (KPIs) into high risk patients (multi-morbid, catastrophic conditions like heart attacks, heart failure and cancer), medium risk (chronic conditions like diabetes, arthiritis, Alzheimers, Parkinsons et al) and low risk (preventable conditions) [8,9].
Operational: Risk based Treatment and Case Management as illustrated in figure 3 above, involving care coordination, intervention by nurse case managers, and a care ecosystem comprising family, friends and social workers for the highest risk patients.For medium risk patients, this would involve enrolling them into a health plan funded wellness and disease management program for managing chronic conditions like diabetes to ensure that these can be managed well without exacerbation. Treatment oflow risk patients would be ‘business as usual’ with primary care and preventive services.
Vision: Deploying Precision Medicine for Targeted Patient and Population Health Management
To further enhance this risk-based approach, what if we can capture the genomic profiles of children and their parents at birth (or shortly thereafter) like they are doing at ITMI as described earlier? Imagine the impact of including the complete genomic profile and clinical analysis as part of every patient’s electronic health record that provides the basis for ‘personalized healthcare treatment’ across ‘the life-time of the patient’.
The benefits for ‘patients-like-us’ by way of superior patient outcomes, and for physicians and clinicians to move from ‘trial-and –error’ medicine to ‘real evidence based care’, would be amazing, measurable and life impacting. Equally compelling for pharmaceutical and medical devices companies would be the able to target and recruit patients with exotic diseases meeting multiple qualification criteria, as basis for higher efficacy and efficiencies with clinical trials and biomarker, drug and devices development.
From a cost-benefits perspective, the savings from proactive, early detection of potential diseases and chronic conditions, and preventing these, or minimizing their debilitating impact thru “targeted treatment”, will measurably contribute to “bending the cost curve”, and deliver 10 -10,000 X ROI on the initial cost of capturing, analyzing, and uploading the genomic profile into every patient’s electronic health record, in the foreseeable future.
“While not “deployable at scale” today, the promise and efficacy of Precision Medicine, demonstrated by visionary leaders like ITMI renders this a provocative, disruptive, yet pragmatic innovative paradigm for improved patient outcomes thru personalized healthcare treatment, whose time has come!”
As always, I welcome your comments and feedback here, and on Twitter at @HITstrategy.
If you have found these insights valuable, please subscribe to my blog with your email address or RSS reader.
Disclaimer: The perspective and views expressed in this Blog post are my own and do not represent those of my current or previous employers.
1.‘Personalized Medicine – Myth, Pipe Dream, or Realizable Promise’, Andy Dé, Blogpost, Health Science Strategy Blog, April 2008.
2. ‘Personalized Medicine- The Time is Now – are we there yet?’, Andy Dé, Blogpost, Health Science Strategy Blog, January 2010.
3. ‘Oncology’s matchmaker: How biomarkers in Immunotherapy bring Precision Medicine to the fight against Cancer, Eric Groves, Quintiles Blog, July 14, 2015
4. ‘How Analytics empowers Precision Medicine’, Andy Dé, Health Data Management (HDM), March 28th, 2016.
5. ‘Visual Analytics makes Genomics in Healthcare possible’, Kirsten Lee, Search HealthIT, July 2015
6. ‘For $ 999, Veritas Genetics will put your genome on a Smartphone App’, Antonio Regalado, MIT Technology Review, March 4th, 2016.
7. Veritas Genetics – My Genome, Web-site.
8. ‘The Six (6) Pillars of Population Health Management’, Andy Dé, Blogpost, Health Science Strategy Blog, November 2015.
9. ‘Retail inspired innovation in Population Health Management’, Andy Dé, Blogpost, Health Science Strategy Blog, April 2015.