WHEN, WHERE, AND WHY
Dating back to 1999, Francis Collins, an American physician, published a foundational document “Medical and Societal Consequences of the Human Genome Project,” laying out the ideas of precision medicine. In this document, Collins predicted how the human genome would be used to predict, prevent, and treat diseases in 2010. More importantly, in 2000, he suggested in the next 15 or 20 years, our society will experience a complete transformation in therapeutic medicine [B-I1].
HOW THE TECHNOLOGY WORKS
Precision medicine is the creation and adaptation of a treatment for a disease in order to offer the most effective treatment. Using the patient’s genes, nongenetic personal characteristics, and molecular characteristics of the disease, precision medicine produces the best results while avoiding unnecessary treatments; it develops therapies to target specific tumors and/or cellular pathways that lead to tumor growth. Additionally, precision medicine identifies the groups of people who will respond best to specific treatments [B-I2].
The term precision medicine, also known as personalized medicine, is deceiving. Specifically, the term is not personalized for each person; instead, it is precise to a group of individuals with similar genes.
Rising technology including artificial intelligence and blockchain technologies are integrated into precision medicine. Dealing with the enormous data on a population's genome structure, blockchain technology works on distributed networks and shared ledgers, which can be used to ensure that the data is ethical and secured. Ultimately, blockchain technology protects a patient’s genetic information. Artificial intelligence is used to analyze patterns in the data, providing insight to medical professionals about a patient’s condition. Quickening the process of genome sequencing, AI is also implemented for clustering the population into groups, allowing patterns to be easily recognized, aiding the production of personalized medicine [B-I3].
MODIFIED AND IMPROVED
Doctors use two ways to treat diseases: traditional medicine and precision medicine. Traditionally, medicine would follow a “one-size-fits-all” treatment plan, solely based on the patient’s symptoms. With this plan, drugs and other therapies are offered to treat large groups of people with the same diseases; however, not everyone reacts to treatment the same way. Thus, precision medicine uses the patient’s genes, lifestyle, and environment, to choose the best treatment that has the most potential in working for the patient.
Rooting back to the beginning, the Human Genome Project is the prime foundation for precision medicine. The map of our genes helps determine the causes behind diseases, seeing how certain gene mutations cause specific diseases [B-I4].
The idea of precision medicine has resulted in the discovery of significant developments, specifically biomarkers. Identified biomarkers “explain the phenomenon of long term learning” and can help with the understanding of symptoms. The data collected from blood transcriptomics and metabolomics can be used to develop models to construct a stronger understanding of the immune system and pathways to treat diseases [B-I3]. Therefore, biomarkers play a crucial role in understanding the symptoms of diseases in order to create the best precision medicines.
CHALLENGES AND HOPES
Although precision medicine has huge hopes in our future, there are also major hurdles it must overcome. This idea of precision medicine is not only the idea of genomics. Indeed, it includes technology, politics, and policy issues [B-I5].
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Precision medicine also includes the creation of mobile apps where patients can enter in data that will be combined with genomic and lab data in new ways. Described by Dr. Steven Steinhubl, Scripps Translational Science Institute's (STSI) director of digital medicine, “despite its promise, efforts to implement precision medicine can be slowed by the limitations of the current systems of care, which are not necessarily designed to take advantage of newer digital technology. Any solution that is going to change the practice of medicine is going to require a brand-new data infrastructure and a lot more use of clinical decision support and alerting system." In other words, systems need to to take account of the large amounts of genomic and lab data collected; otherwise, the data will be useless. Including STSI and the Mayo Clinic, the National Institutes of Health All of Us Research Program aims to collect and share health data on 1 million US residents in order to advance precision medicine. Steinhubl hopes to seek a digitally scalable infrastructure, emphasizing that “it goes beyond precision data to precision implementation of that data” [B-I6].
The picture to the right describes precision medicine, the importance of it right now, and the near term goals.
