Precision medicine, primarily highlighted as a term and a central strategic objective by President Obama in 2015, aims to apply therapeutic solutions based on synthesizing large-scale information from patients’ genomes, environmental factors, and individual habits.
It’s clear that precision medicine, as a significant new reality, owes a great deal to the development of genomic and proteomic technology, as well as the advancements in collecting and analyzing large amounts of information (Big Data) and the algorithms for machine learning data analysis.
When analyzing the importance of precision medicine and the scientific fields that comprise or will evolve to comprise this new reality, the following points need to be emphasized:
- Different categories of internal medicine diseases, such as cancer, cardiovascular diseases, rheumatic conditions, gastrointestinal problems, etc., will likely be approached by precision medicine based on varying technologies and prerequisites. In the case of cardiovascular medicine, a new set of digital health technologies and devices is expected to contribute to optimizing therapeutic outcomes. For example, in arrhythmogenic hereditary diseases, implantable loop recorders (ILRs) provide valuable and reliable information that can lead to the evaluation of therapeutic results.
- Precision medicine in cardiovascular care has focused on conditions caused by a dominant, monogenic genetic factor. However, this focus on relatively rare hereditary myocardial diseases is invaluable as it acts as a “magnifying glass,” revealing mechanisms that concern not only monogenic hereditary conditions but also polygenic ones, such as coronary artery disease, atrial fibrillation, and many other cardiovascular diseases.
- To date, the first, highly encouraging steps of precision medicine in cardiology have been taken. A characteristic example is the drug tafamidis, which promises significant results in transthyretin amyloid cardiomyopathy. In the case of hypertrophic cardiomyopathy, the drug Mavacamten, a myosin ATPase inhibitor, appears exceptionally promising.
- Alongside genomic and proteomic technologies, artificial intelligence (AI), and specifically deep machine learning algorithms, are expected to play a significant role in precision medicine. It’s evident that it’s only a matter of—perhaps little—time before digital neural algorithms manage to analyze a significant number of digital biomarkers and group specific categories and sets of patients, or non-patients, advancing precision medicine. A characteristic example of a rapidly evolving reality is that electrocardiography, a technology over a hundred years old, is entering an era of evolution. What digital neural networks can recognize in an electrocardiogram surpasses our imagination.
In conclusion, the era of precision medicine allows us to envision a new, more precise, and pluralistic medicine. A time when, most likely, a smart wristwatch in a remote village of a low-GDP country will detect a range of clinical and subclinical diseases via an electrocardiogram, contributing to some extent to the “democratization” of medicine globally.
This publication can be found on the following page: https://www.tovima.gr/2021/10/04/science/stin-kardia-ton-genetikon-kardiaggeiakon-nosimaton/