One of our healthcare system’s biggest challenges is moving beyond the current break-and-fix model, where physicians’ hands are tied until abnormalities arise. Only when an illness or condition presents itself does the system spring into action. Reacting to an adverse medical event after it has progressed to causing the patient to seek medical help is the least opportune time to address the underlying disease. Today’s science allows far more intelligent approaches that enable interdiction before the disease develops or early in the disease process when it is most easily dealt with.
The changing demographics of our society demand a smarter way of delivering healthcare. People are now living longer, and data suggests that chronic diseases (i.e., hypertension, diabetes mellitus, cancer, chronic lung disease, etc.) are on the rise and occurring earlier in life than previous generations. Healthcare could be looking at the perfect storm. In fact, the number of individuals 50 years and older with one chronic disease is expected to increase by 99.5% within the next 25+ years — and that’s on top of the 133 million people already living with one chronic condition. Complicating matters further is that almost half of individuals with a chronic illness are dealing with more than one.
Improving patient outcomes will be key to relieving the inevitable strain on the healthcare system, and the area that holds the most promise is precision medicine.
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What Is precision medicine?
Precision medicine is a relatively new approach to preempting, diagnosing, and treating disease. Thanks to human genome sequencing, healthcare data analytics, and an increased understanding of how genetics impact intracellular processes, healthcare teams can now consider a patient’s genetics, lifestyle, environment, and a host of other factors to personalize care delivery, improve patient outcomes, and lower overall healthcare costs. Multi-omics in precision medicine is an emerging field that greatly contributes to this promise by integrating genomic, proteomic, and metabolomic information to provide a more comprehensive understanding of an individual’s health status.
For example, with cardiovascular disease, much is known about how this disease develops and how to detect it at its earliest onset. This is key because much is known about preempting the condition — or slowing its onset and progression, at the very least. By applying algorithms derived from machine learning (ML) trained on the data sets of genetic variation and outcomes for thousands of people, it is possible to make predictions of future risk of coronary artery disease and events for the individual based on their unique genetic code. This allows physicians to build individualized prevention, detection, and treatment plans that can address heart disease far more effectively than the current system, which waits for the sentinel event, which may be sudden cardiac death or a life-changing heart attack.
As healthcare data analytics and technology advances, precision medicine will become the norm. However, at this point, it’s rarely found in day-to-day primary care, where it could make a staggering difference. Precision medicine adoption in primary care has been slowed by the need for physicians to learn this new science, regulatory institutions not built for the speed of today’s technology advancements, and stakeholders seeking to maintain the status quo. Advances in healthcare data analytics, including machine learning and artificial intelligence algorithms, are poised to catapult precision medicine into the mainstream.
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Moving beyond one-size-fits-all
Precision medicine is beginning to take the stage. Pharmacogenomics, which assists physicians and pharmacists in selecting medications and dosing based on individual genetic makeup, is making its way to the fore. Precision oncology, with analysis of the mutational burden of tumors that allow for targeted therapies, is slowly becoming the standard of care. The detection of early cancers by detecting epigenetic modifications of DNA fragments found in the circulating bloodstream is beginning to revolutionize our approach to screening for cancer. It is true that these are early days for the “liquid biopsy,” but it is unequivocal that this new technology is a big step forward. Only a decade ago, liquid biopsy was the stuff of science fiction.
AI is accelerating the rate of scientific discovery involving both normal cellular processes and disease pathways. This is at a time when the ability to analyze large data sets using massively parallel cloud computing is exploding. This confluence of technologies — along with AI, increased computing capability (including quantum computing), advancement of basic science concepts, and individual genetic sequencing done cheaply and at a large scale — will bring about a healthcare revolution. This revolution will end the break-and-fix system and usher in the age of precision medicine, which will be personalized, predictive, proactive, and preventive.
In addition to machine learning discovering patterns of genetic variation predictive of future health risks, other scientific advances such as detecting epigenetic modification of DNA, other markers of gene expression including biomarkers indicative of gene activity, and advanced imaging technologies will layer upon each other, allowing for a truly exponential increase in our ability to predict and early detect disease onset. It is worth noting these technological advancements are here. Attempts to implement this revolution in healthcare are lagging.
Take something like the “Alzheimer’s” gene, which would indicate an increased risk if found in a patient’s genetic makeup. The presence of the gene doesn’t equate to a certainty of the condition’s development. To inform where someone is on the risk spectrum, researchers can add another layer of technology, which looks at what biomarkers are present in the blood with a fine-tooth comb. A particular biomarker, coupled with the Alzheimer’s gene, might indicate more accurately the risk of Alzheimer’s disease.
The true benefits of proactive healthcare
When physicians access an individual’s unique genetic profile, it can revolutionize care delivery. Healthcare teams can make more informed decisions and take a more proactive approach to disease prevention, diagnosis, and treatment. Here are just a few of the benefits of proactive healthcare:
1. Early detection of genetic risks.
Greater genetic testing in healthcare would allow for the early detection of any number of diseases, and physicians would then have the opportunity to take more proactive measures to preempt or mitigate risk. If, for example, a patient was found to have a predisposition to blood clots, a condition not usually evident through standard medical examinations, that individual would be forewarned and take additional precautionary steps when exposed to situations that increase risk. These include more frequent stops to walk around on long car rides and moving around on long plane flights. They may also be briefed on symptoms to look out for, such as asymmetric swelling in the lower extremities and other early signs of a blood clot. Also, surgical teams would value this information and may modify post-operative protocols to mitigate peri-operative increased risk of clot due to immobility.
2. Informed risk analysis and stratification.
The multi-omics of precision medicine offers a more detailed risk analysis, helping patients understand their inherited risks of heart disease, diabetes, cancer, and other chronic diseases. This knowledge can empower the individual and improve patient engagement in healthcare, making it more likely that they’ll take proactive steps to delay or prevent the onset of a given condition or disease. Though somewhat dated, one study found more than 86% adherence to care plans in patients given a genetic diagnosis. Prior to genetic testing, adherence was only 38%.
3. Tailored medication management.
Safety and efficacy are always top of mind with medication management. However, not everyone metabolizes a prescription drug in the same way — and that’s precisely what precision medicine can help identify. It can uncover individual gene variants affecting how someone will react to medication. These insights can take some of the trial and error out of dosing. A slow metabolizer, for instance, might require a reduced dose of a particular drug, while fast metabolizers could benefit from higher doses. Genetic testing in healthcare can improve drug safety and effectiveness while reducing the potential risk of adverse drug interactions.
4. Increased patient engagement in healthcare.
By providing detailed information about their health risks and medication responses, precision medicine encourages patients to be more engaged in their healthcare. This heightened awareness can lead to better compliance with preemptive measures and treatment plans, ultimately improving health outcomes, minimizing readmission rates, and reducing healthcare costs.
Answering the question of what precision medicine is can be complex. There’s a multitude of components involved in its application. However, the ultimate goal is to personalize healthcare, and personalization can improve engagement, adherence to treatment plans, and patient outcomes — all of which can go a long way to relieving the strain on the healthcare system and reducing healthcare costs.
Photo: Getty Images 700275630 SusanneB
Dr. William P. Stanford is co-founder of Biography Health. Inspired by recent advancements in biomedical science and medicine, Dr. Stanford completed professional certification through Stanford University’s Department of Genetics in 2018, further advancing his role as a true physician-scientist.
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