Since the ancient Greek civilization, physicians have sworn to uphold certain ethical standards. In the modern version of the Hippocratic Oath, doctors swear, among other commitments, “I will remember that I do not treat a fever chart, a cancerous growth, but a sick human being, whose illness may affect the person’s family and economic stability. My responsibility includes these related problems if I am to care adequately for the sick. I will prevent disease whenever I can, for prevention is preferable to cure.” . This mantra is upheld in progressive medicine, where clinicians strive to provide more accurate, precise, and personalized care. Specifically, during the last decade, the medical community has seen significant gains across electronic health records, big data analytics, supercomputing, analysis, genomics, and other technologies (high‐dimensional biology aimed primarily at genomics, transcriptomics, proteomics, and metabolomics) . Without such advancements in medicine, physicians and scientists would lack the essential tools and approaches necessary to push the envelope of contemporary healthcare.
Joel Arun Sursas, Medical Doctor and Health Informatician, is at the forefront of bridging the gap between doctors and engineers to improve patient care. His extensive collaboration with other doctors and engineers resulted in designing and implementing the largest Electronic Medical Record (EMR) system in Singapore, spanning 53 medical centers, as well as developing a data analytics platform to trend epidemiological data.
The aforementioned concept of utilizing tech and genetics for disease diagnosis, treatment, or prevention is commonly recognized as precision or personalized medicine. While the two terms overlap in several areas, their evolving definitions distinguish subtle yet noteworthy differences.
In this article, Doctor Sursas reviews the basic concepts of precision medicine and personalized medicine as well as the intersection of each classification.
Historically, the terms personalized medicine and precision medicine were used interchangeably. Per the National Research Council (NRC), the former preceded the latter, but as both started to play a more prominent role in clinical decision-making, misinterpretation became a considerable concern . Generally speaking, administrative and medical professionals primarily regarded the phrasing with genomic and cancer research, whereas consumers associated the lingo with therapeutic practices tailored to the individual . Consequently, the NRC issued a report in 2011, detailing the delineation between the two and its preferred terminology .
According to the National Institute of Health (NIT), the Genetics Home Reference (GHR), and the Precision Medicine Initiative (PMI) precision medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person,” [1, 3, 8]. This approach is in contrast to a one-size-fits-all mentality. Instead, it enables doctors and researchers to predict and develop more accurate treatment and prevention strategies for a particular disease and patient demographics.
Let’s assume that precision medicine in action can be deconstructed into two elements: research and application. The research phase relies heavily on the assemblage of genomic data or Genomics (the study and analysis of the structure and function of genomes) . For example, genetic sequencing, an aspect of genomics, “is the process of determining the four chemical building blocks of DNA” . Thankfully, due to more efficient and cost-effective methods, genetic testing is becoming more common. As a result, clinicians are collecting more substantial amounts of genetic material. The bulk of information currently available comes from the 100,000 Genomes Project, though private companies are amping up their research efforts . Identifying and understanding individual traits on a molecular level could prove extremely beneficial, especially for the treatment of childhood developmental disorders.
Pharmacogenomics is part of the application phase of precision medicine. It combines pharmacology (the study of a drug or medication action), and genomics to develop medications fitted to a person’s genes [2, 4]. Technological wonders aside, this approach is groundbreaking since, until recently, scientists created drugs under the assumption that the medication worked the same in everyone. Although this field is still nascent and somewhat limited, it is experiencing rapid growth. Currently, pharmacogenomics is helping improve human immunodeficiency virus (HIV) treatment by screening patients for a genetic variant that makes them more susceptible to adverse side effects from the antiviral drug abacavir (Ziagen) .
The use of personalized medicine has fallen out of favor since President Barack Obama announced the PMI in 2015 . As a result, when physicians talk about personalized care today, it generally encompasses the broader picture of decision making and treatment. However, much of the public still assume that personalized medicine implies that unique treatments can be designed for each individual . A highly customized test or direct-to-consumer (DTC) genetic testing may, given time, improve an individual’s health and help prevent common diseases, but this has yet to be clinically proven . While precision medicine classifies diseases using traditional phenotypic and genetic approaches across various genetic datasets, personalized tests, especially for uncommon diseases that lack effective drug therapies, often deliver uncertain information and create false expectations.
Healthcare has merely scratched the surface of precision medicine. Long-term, researchers and doctors hope that technology, in conjunction with genetic data analysis and pharmacogenomics, will cultivate a more personalized approach for a subgroup of patients and accurately reveal which treatment and prevention strategies are most viable for a particular disease. Thus elevating care and improving the dialogue between physician and patient.
Joel Arun Sursas holds a Bachelor’s Degree in Medicine and Bachelor’s Degree in Surgery from the National University of Singapore and is continuing his education to obtain Certificate in Safety, Quality, Informatics and Leadership from the Harvard Medical School, and Masters in Applied Health Science Informatics from the Johns Hopkins University (both expected in 2020). His technical skills include SPSS, RevMan, and Python.
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