Precision Medicine: The Need for a Mindset Change

By Sara Hou, Program Manager – Clinical Healthcare & IoT Technologies at Mazik Global

The concept of precision medicine, a clinical paradigm that accounts for each person’s genetic makeup, environment, and lifestyle to diagnose and treat disease, has risen to the forefront of thought-leadership in healthcare IT, hailed as a “new power to heal[1].” A massive budget of $309 million was proposed for fiscal year 2017 for the research and development of Precision Medicine[2], and more than 54,000 scholarly articles discussing the topic have been published online since 2015, when President Obama enacted the Precision Medicine Initiative. Many scientists, physicians, and patients today believe in the power of this new clinical approach to transform the traditional reactive methods of healthcare practice into proactive and individualized care for all.

While precision medicine has proven its potential in a few use-cases, such as cancer immunotherapy based on patients’ genetic mutations, the hard truth is that almost every precision medicine effort so far has failed to deliver substantial value, if any, to patients or care teams. One clinical trial that used patient genotypes to determine dosages for the anticoagulant warfarin showed better dosing results for the control group than the genomics-based group. Similarly, large scale public health initiatives have been more effective at curbing deaths from cancer or complex diseases than targeted genomic therapies – for example, diet and exercise can cut down the risk of converting pre-diabetes to diabetes by nearly two-thirds, and tobacco control can largely decrease lung cancer incident rates[3]. We have yet to define the methodologies for leveraging genetic data into prescriptive care plans. So far, precision medicine does not live up to the hype.

Why not? To answer this question, we must go back to the meaning of the term “precision medicine.” The National Institutes of Health (NIH) defines precision medicine as “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” While the definition identifies multiple influencing factors, most people, including healthcare professionals and researchers, relate this term only with the application of genetics-based, individualized therapies. While precision medicine does require extensive use of genomics in discovering new treatments, we cannot neglect environmental and lifestyle factors when working to turn our vision of precision medicine into a reality.

Although some clinical treatments work like mathematical formulas, most physical and mental illnesses stem from combinations of many different life factors and unknown variables, thus convoluting the underlying causes of many diseases. Tying genetics to clinical treatments holds the promise to empower patients to heal faster and even prevent disease, but we must remember one basic statistics lesson—our research identifies correlations between genetics and health, not causations. One person could get diagnosed with lung cancer after smoking for ten years, while another could smoke for his or her entire life and never develop lung cancer. Conversely, identical twins may develop different diseases based on where and how they live, despite sharing almost-exact genes. These divergences from correlative expectations point to the larger variabilities beyond genetics that impact our health. As appealing as it may feel to glorify genomics as the end-all-be-all to unlocking the power of precision medicine, to do so is to oversimplify the overwhelmingly-complex problem at hand to practice tunnel-vision problem-solving. To make precision medicine work, we need to take a holistic approach to discover how our genetic, lifestyle, and environmental factors interact with each other to create disease or sustain health.

Environmental and lifestyle factors are comprised of all the factors outside genetics that can affect health. They divide into two levels: macro and micro. The macro-level consists of higher-level factors mostly related to socioeconomic status, such as social class, financial standing, childhood neighborhoods, air pollution levels in nearby environments, and so on. Micro-level factors are unique and personal to an individual, like diet, exercise patterns, household dynamics, or even quality of childhood upbringing. Each of these macro- and micro-level environmental and behavioral factors can have lifelong impacts on health, especially in chronic conditions.

Research shows that the risk and development of common and chronic diseases, such as asthma, diabetes, cancer, or cardiovascular diseases in general depend more on environmental and lifestyle factors than on genetic ones[4]. For example, not completing high school and having a family income below poverty level were associated with a twofold higher mortality rate from diabetes than those with college or higher education degrees or those with higher family incomes. Thus, the effort to optimize personalized treatment of chronic diseases should not stop at testing and verifying genomic biomarkers but go even further to include constant monitoring of patients’ habits, environmental exposures, and other life factors. Care teams could use this information to further tailor patient care plans to individuals. We could detect and intervene with automated, patient-specific warnings when patients engage in potentially detrimental activities or enter hazardous locations. Similarly, we could also encourage health-improving or disease-preventing behaviors.

Today, we’ve entered an electrifying moment in the intersection of healthcare and technology. We can envision a future world in which we prevent disease before it develops, remove trial-and-error from treatment processes, and trust that our physicians have all the information they need to treat us as unique individuals and design care plans to fit our lives. We’re poised to minimize our pain and improve our overall enjoyment of life. It feels within our reach. In fact, we’ve already developed many of the tools that we need to tackle the challenges of precision medicine. Mobile applications that run in the background on our phones, inconspicuously collecting data. Internet of Things frameworks that connect devices, share data, and automate decision-making. Machine learning algorithms that will identify patterns to allow for predictive analytics, and ultimately, artificial intelligence. These technologies comprise pieces of a solution. The remaining work lies in combining these tools in the right way.

If we want the Precision Medicine Initiative to succeed, the healthcare IT industry needs to engage in collective, big-picture thinking to design a holistic framework that can support this movement. We will face huge challenges. To draw conclusions about how combinations of environmental, lifestyle, and genetic factors relate to health and disease, first we need to collect the right data on each of these factors—not just genetics—and then run machine learning on this data. Machine learning can identify patterns in the data provided, but we will not know what information has meaning until we run the algorithms. How can we collect consistent information on every potentially-relevant data point? How will we overcome socioeconomic barriers to technology adoption to account for the entire demographic spectrum? Furthermore, we must avoid the multiple comparisons problem, the statistical concept that some random associations will appear statistically significant when many variables are considered simultaneously. We will need millions, maybe even billions, of medical records to derive meaningful insights from so many variables. In the era of Big Data, how will we share information securely and ensure the privacy of patient records?

Amidst countless hurdles and skeptics, the responsibility falls on the healthcare IT community to work together to bring the precision medicine vision to life. Any viable framework will pull together a combination of technologies from numerous sources. Can we establish an industry ecosystem that incentivizes teamwork and collaboration across companies and individuals for the larger benefit of all? Our ability to solve such industry-wide challenges will make or break the future of the precision medicine era we imagine. We have the energy, the motivation, and many of the tools. Do we have the cooperation?

 

Sources:

[1] “Has Revolution Arrived?”. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101928/

[2] “HHS FY 2017 Budget in Brief – NIH”. https://www.hhs.gov/about/budget/fy2017/budget-in-brief/nih/index.html

[3] “Precision Medicine: Too Big to Fail?”. http://sites.tufts.edu/insight/2016/12/09/precision-medicine-too-big-to-fail/

[4] “Genes, the environment and personalized medicine – We need to harness both environmental and genetic data to maximize personal and population health”. http://onlinelibrary.wiley.com/doi/10.15252/embr.201438480/full

 

 

About the Author:

sara headshotSara Hou is the Program Manager for Clinical Healthcare & IoT Technologies at Mazik Global. With a degree from Northwestern University, she brings technological innovation to healthcare organizations for improved patient engagement and chronic care management. She has served as Outreach Captain & Cancer Support Specialist for Imerman Angels, an NPO providing personalized emotional support to those affected by cancer, as well as Vice President of Engagement for Relay For Life of Northwestern, an American Cancer Society fundraiser. Sara is passionate about incorporating emotional support into the standard of care and using technology to make healthcare personalized, engaging, and affordable for everyone.

 

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