Precision Medicine: A Contemporary Scientific Revolution

Thursday, October 20, 2016

In The Structure of Scientific Revolutions, Thomas Kuhn suggested that science did not progress linearly in a cumulative fashion. Rather, the history of science shows that science undergoes periodic dramatic changes or paradigm shifts resulting from new discoveries and theories. Precision medicine may be one such revolution.

The most basic definition of precision medicine (that avoids the more complex medical jargon} is that it is an approach to disease treatment and prevention that seeks to maximize the effectiveness by taking into account individual variability in genes, environment, and lifestyle. Simple, right? Well, the reality is anything but. When we talk about precision medicine, we are talking about harnessing the power of the very latest innovations in basic and clinical research, biomedical engineering technology, and big data science.

We certainly don’t like to think of current medicine as imprecise, nor is that really accurate—at least not in the sense that bloodletting, commonly performed for many centuries, was imprecise. Medicine is designed for the average patient. It results from large clinical trials in which success or failure is based on statistical probability. It has been a highly successful approach for determining best treatments.

Still, some patients don’t respond to the best treatments, or at least don’t respond as well. Plus, the best treatments sometimes cause debilitating or life-threatening side effects in some patients, and therefore, can’t be used at all. Precision medicine, however, eschews the idea of an average patient. In fact, in a future, fully realized state, precision medicine would be able to tailor treatment to the specific genetic make-up and biochemical composition of an individual as well as their lifestyle, environment, and personal history. 

Case in Point

Much of the current revolution in precision medicine has been enabled by advances in genetics. including The Human Genome Project (HGP), which is an international, collaborative research program whose goal was the complete mapping and understanding of all the genes of human beings. All our genes together are known as our genome. The project took more than 13 years to complete and cost over $2 billion dollars. It turns out that the human genome is big—20,500 genes, but that is not as big as previously thought.

Today, the human genome can be sequenced in less than a day and can cost as little as $1,000. But don’t expect human genome testing in your primary care practice. First, it is unclear if insurers will pay for it. In fact, they likely won’t cover it, because the clinical usefulness of it is far from being established. Plus, primary care health providers are not prepared to interpret such tests. It’s not like anyone can memorize, let alone know what to do about, the thousands of gene mutations that are present in any one individual. The decisional support tools simply don’t exist for primary care providers.

Also, and more importantly, we are not hard wired by our genes, which ratchets up the complexity of precision medicine substantially. How genes express themselves (think: do what they do) depends on many epigenetic factors. Epi means “above” in Greek, so these are biochemical factors that impact the work of the gene. Even gene mutations, such as those associated with some types of cancers, may express themselves differently depending on epigenetic factors. In fact, the number of things that may affect the epigenome are perhaps countless. They include diet, lifestyle factors, environmental exposures, and even the type of microorganisms such as bacteria and viruses that are present in the body.


Bottom line: True precision medicine would mean accounting for all the genetic and epigenetic factors in determining the right preventive or treatment approach for any given disease. 

Moving Forward

Given the enormous number of factors that must be considered, data science plays an integral role in the future of precision medicine. The idea of Big Data is now firmly ingrained in our culture. There is no better example of the idea than the data that must be analyzed to reveal patterns and associations in order for precision medicine to work.

Think about all the places these data are stored. Getting all the data to talk to each other is daunting, which is the non-IT way of saying that interoperability presents a significant barrier to the future of precision medicine. What’s more, in order for meaning to be made out of these data, they have to be widely available to scientists working on breakthroughs and clinicians who need decisional support tools.

And individuals are right to be concerned about their privacy in this area. What if data were breached? What are the ramifications of having one’s genome in unintended hands? The answer is not fully known, but the possibilities give pause.

To firmly address the future of precision medicine, President Obama announced the Precision Medicine Initiative in his 2015 State of the Union Address. The initiative is a $215 million effort to enable a new era of medicine through research, technology, and policies that empower patients, researchers, and providers to work together toward development of individualized care. The majority of the funding went to the National Institutes of Health to establish a million-person research cohort who will contribute genomic profiles, health records, lifestyle and environmental information, lab results, and even data from wearable devices and sensors. The hope is that this cohort will produce the database from which much evidence for precision medicine will emerge.

Money also was allocated to the Office of the National Coordinator of Information Technology to develop interoperability standards. There was progress in the first year, including the development of the initiative’s Privacy and Trust Principles, which received extensive public input and highlight the crucial roles these concepts play in the future of precision medicine.

Let’s return to Thomas Kuhn. He is often misread as a relativist who claims science progresses randomly. He actually argued just the opposite. Everything we knew before the revolution—the paradigm shift—wasn’t wrong; it’s just a special case of the new paradigm. And so it is with precision medicine. Everything that works still works, but now there is the opportunity to find what works better for each individual. Evolution follows revolution and we can’t even calculate where the finish line is, let alone see it.

For a deeper dive into this topic, Join me November 13-15 at the ATD 2016 Healthcare Executive Summit for the session: Precision Medicine: When “What ifs” Become “What Is.”

About the Author
Patrick Robinson, PhD, RN, ACRN, CNE, FAAN, is currently dean of the School of Nursing and Health Sciences at Capella University. He obtained his bachelors and masters in nursing from Indiana University and holds a PhD in nursing science from Loyola University Chicago. He completed a post-doctoral fellowship in biobehavioral nursing research at the University of Illinois at Chicago. Previously, he served as senior vice president of academics for Orbis Education, dean of curriculum and instruction at Chamberlain College of Nursing, executive assistant dean of the University of Illinois at Chicago College of Nursing and chair of the department of health management and risk reduction at the Niehoff School of Nursing at Loyola University Chicago.
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