The approach to healthcare is evolving again. Health care began as bedside medicine in the 18th century, in which care was provided directly to patients using a holistic approach. Doctors and health workers would assess the patient's overall well-being in order to provide treatment. Health care providers often did not know the etiology of diseases and, as a result, treatments often had no scientific basis. Health care then evolved into hospital medicine in the 19th century. In this phase of health care, hospitals have become the place of medical knowledge and training. Doctors held all medical knowledge and patients were largely excluded from medical decisions. The next phase of health care was the laboratory phase, which began in the late 19th century. With the invention of the microscope, much of medical knowledge and treatment relied on laboratory tests and pathology. In this era of medicine, treatments are based on methods to which an average number of people will respond positively. This treatment strategy does not take into account individual differences and can lead to people receiving ineffective treatment. In addition, these therapeutic treatments can cause adverse reactions in the patient. Currently, the focus is on moving the healthcare system to an era of precision or personalized medicine. Jameson and Longo (2015) define precision medicine as “treatments targeted to the needs of individual patients based on genetic, biomarker, phenotypic, or psychological characteristics that distinguish a given patient from another patient with similar clinical presentations.” . Transitioning to a precision medicine approach in healthcare can increase the effectiveness of treatments for patients and reduce the number of unwanted side effects attributed to treatments. Additionally, precision medicine offers healthcare the opportunity to be more proactive. Healthcare often takes a reactive approach, in which interventions are only offered after the onset of disease, but precision medicine can provide a better assessment of an individual's risk of developing a disease. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get an original essay A critical element for the development of precision medicine is the incorporation of biomarkers. Biomarkers are defined characteristics that have the ability to identify normal or abnormal biological functions. Biomarkers may have the ability to diagnose disease, monitor its progression, identify people at risk of developing disease, and evaluate the safety of treatments. Biomarkers can be obtained from molecules present in body tissues and fluids, physiological characteristics or tissue imaging. Biomarkers should be as objective as possible to eliminate any potential bias in interpretation. Therefore, biomarkers do not measure how a person feels. In precision medicine, biomarkers can be used to identify a person's individual characteristics, which can guide healthcare and treatments specific to the individual. Biomarkers associated with genomics are of particular interest in precision medicine. However, other omics approaches, such as transcriptomics, proteomics and metabolomics,can also be very useful. Additionally, wearable technology capable of continuously monitoring biomarkers in an individual and detecting changes. It can also help guide precision medicine and enrich health databases. Health databases can be used to monitor an individual's health throughout their life and can be a valuable asset for research. Although precision medicine has countless benefits, there are also many issues and concerns that need to be addressed before precision medicine can be fully implemented in healthcare systems. For precision medicine to be most effective, adjustments must be made to all aspects of healthcare and biomarker development. This involves making changes to practices and education for patients, healthcare providers, academia, industry, regulators and policy makers. Since the Human Genome Project successfully mapped the entire genome, there has been great interest in the roles DNA and DNA play. RNA plays a role in disease processes. With the advent of better and more sensitive technology, genetic testing can be used to diagnose diseases, predict individuals with increased susceptibility to developing a disease, and predict the success of a particular treatment or response to a medicine. Genetic biomarkers look for variations in DNA and RNA sequences, as well as overall RNA expression. Variations and differential expressions of genetic material can have a significant impact on how an individual will develop a disease and respond to treatments. These differences are the target of biomarkers. However, despite the many possible applications of genomic biomarkers, there is concern that too much emphasis is placed on the development of genomic biomarkers. First, although DNA sequences are able to show variations in the genome, they do not correlate with the amount of protein actually produced. Therefore, sequences may not be used to prove causality. Second, knowledge of genetic sequences and the functions they encode may be incomplete. Many genome-wide association studies (GWAS) have reported associations between variations in genetic sequences and diseases. However, many of these studies had small sample sizes and the results are not reproducible. Third, genetic biomarkers are very effective in diagnosing diseases like cystic fibrosis, which result from a single genetic mutation. However, when it comes to more complex chronic diseases, such as cancer and obesity, genetic biomarkers have limited ability to predict disease. In chronic diseases, several alleles contribute to the development of the disease. As a result, the impact of single genetic variations on disease development is very small and is not an effective method for identifying the causes of chronic diseases. Additionally, there is evidence demonstrating that environmental and behavioral factors have a greater impact on the development of the disease. Integrating genomic approaches with other omics approaches can help address these issues. Transcriptomics, proteomics, metabolomics and understanding the immune response can complement genomic testing results to provide more reliable disease associations. Overall, the combination of severalapproaches can contribute to the production of more valid biomarkers. A combined approach is demonstrated in integrative personal omics profiles (iPOPs). Genome, transcriptome, metabolome and autoantibody profiles are generated and combined to create the iPOP. The generated iPOPs can be used to monitor healthy individuals and detect abnormalities associated with diseases. Specifically, iPOPs have been shown to be effective in monitoring and identifying diabetes and viral infections. iPOPs are valuable in the development of precision medicine, as they can greatly contribute to the monitoring and diagnosis of diseases in individuals. Digital biomarkers and wearable technology also have great potential to impact precision medicine. Currently, wearable technology is primarily used in the context of fitness monitoring, but there are many opportunities for integrating wearable technology into healthcare. Wearable technology has the ability to take continuous biomarker measurements that are normally limited by the lack of portability of measurement tools. Biomarkers that can be measured with wearable technology include heart rate, respiratory rate and lung function, blood pressure, temperature and sweat. Heart rate, respiratory rate, blood pressure, and temperature are common measures of health that are monitored during routine doctor visits. As a biomarker, sweat can be used to measure stress, electrolyte metabolism disorders and cystic fibrosis. Wearable technology for healthcare is not readily available to the public. One reason for this is that few wearable devices for health monitoring have been approved. Additionally, it is difficult to produce devices that can accurately measure biomarkers, are easy to use, and are comfortable to wear. A major concern associated with wearable technology is the production and maintenance of large data sets. Especially with devices that take measurements continuously, large data sets will be quickly generated and continue to grow perpetually. For epidemiological purposes, these large datasets are very useful. However, problems can arise when trying to maintain data security, and rigorous protocols will need to be in place to ensure that the rights of individuals contained in the dataset are not violated. Additionally, inaccurate data from wearable technology can lead researchers to discover associations between biomarkers and diseases that don't actually exist. Overall, the development of sophisticated and validated biomarkers has been essential for the transition to precision medicine. However, many obstacles still need to be overcome before precision medicine can be fully implemented in healthcare practice. Implementation of precision medicine may be constrained by everyone involved in healthcare, including patients, clinicians, academia, industry, regulators, and policy makers. From a patient perspective, social and cultural issues, including lack of access to reliable healthcare, will determine the effectiveness of precision medicine approaches. Additionally, patients must be able to trust the results of biomarker tests and act accordingly. Currently, genetic testing can give patients information about their risk of developing.