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Personalized genomics, the study of individualized genetic information by conducting whole scale exome sequencing or genome sequencing to identify the variation and polymorphism of DNA by comparing with the library of known sequences is rising as a missing puzzle for the cure of rare diseases that arise from the genetic disorder. Researchers found many treatments and therapeutics for known diseases caused by viruses and bacteria; however, a cure for diseases arising from genetic disorders is still yet to be explored. Many rare diseases are often caused by multiple mutation sites. Hence, known therapeutics can only alleviate the symptoms of those diseases. It was hard to diagnose the causal link of DNA variants and phenotypic effect due to limitations of formal sequencing but, improvements in DNA sequencing enabled massive amounts of sequencing work. Not only the improvement of sequencing technology but also, application of personalized genomics together with evolving Artificial intelligence and computing biology opened a new pathway to develop more efficient and effective treatments for rare diseases by solving the mystery of the gene mutation site. It was a novel area of study but now the effectiveness of personalized genomics has been widely admitted and recently, future-oriented changes in policies, infrastrastructure and prices are made to readily adopt and emerge this area into other fields.

Genome Analysis
Personalized genomics includes the analysis of the genome of individuals. To analyze the genome, basic knowledge of genetics is required. Briefly explaining essential knowledge to understand genome analysis, there are DNA building blocks that are called nucleotides and those nucleotides are annealed to form a strand. Two strands of DNA are supercoiled into double helix form and that is what people think of first when they imagine the DNA structure. These DNA are very important as they contain genetic information. The order of nucleotides determine the genomics of individuals and individuals have different genomics. Therefore, people have different characteristics such as eye colour. Not only characteristics but different causes of unique disease can be revealed by determining the order of nucleotides, DNA sequencing.

To analyze personal genomics, a technique called DNA sequencing is needed and it is used to determine any disorders or polymorphism of DNA sequence. There are two methods to conduct DNA sequencing, Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS). Formal way of sequencing, sanger technique has some limitations that it was costly and time-consuming. It has been automated and it is suitable for the lab work but not suitable to sequence every DNA in our human genome. The recent development of Next Generation Sequencing (NGS) has dramatically remedied Sanger sequencing’s shortcomings in time and reduced the cost.

NGS enabled the sequencing of large loads of DNA. There are pieces of genes that transcribe the proteins. These pieces of gene give instructions to make complementary proteins and are called exons. Exons are known to make up 1 percent of a human’s genome. All the exons in a genome together are called the exome. Whole Exome sequencing is the method to sequence all exons in genomics. As proteins produced by the exons are crucial for human metabolism and the endosomal environment, if mutations occur at the exons, it will lead to a critical genetic disease. Hence, most mutations that cause known genetic diseases are in the exon area. WES is a more efficient way to sequence possible disease-causing mutations.

WGS, on the other hand, literally stands for the method that sequences every nucleotide of an individual’s DNA and can detect any variations in any location in the genome. Researchers have found that mutation at outside of exon areas also can influence the gene transcription and the protein production. In other words, DNA variation at the non-exon area can induce genetic disorders that WES may not detect. Hence, there are studies that conduct both WES and WGS together for population to increase the quality of data to identify genetic disorders that may cause the unique diseases.

By WES and WGS, various genetic variations can be observed compared to select gene sequencing but the significance of the information obtained is mostly unknown. This is because there is no 100% causal link between the genetic variation and health. There are some mutations that do not affect human health or cause disease. It is very ambiguous to say identified genetic change is an inducing factor of the disease of interest. Hence, large sample size is needed to be analyzed to identify the causal variants. Once in a while, there are some cases where variants that have already been identified are associated with another genetic disorder that has not yet been discovered. Researchers call this finding a secondary finding or incidental finding.

Genetic Medicine
Genetic medicine refers to the application of genetics to the medical care in the detection and treatment of several phenotypic rare hereditary disorders, and this discipline incorporates an emerging area in the medicine such as personalized medicine.

Personalized medicine is a type of tailored medical treatment to the individual patients’ characteristics based on their expected response or resistance to particular diseases or disease risk assessment. While traditional medicine follows ‘one-treatment-fits-all’ approach, which is designed to be treated a large population of patients with the certain diseases, personalized medicine is prescribed to the patient group sorted by molecular diagnostic and analysis techniques relating to their genetic information in order to minimize adverse effects and to maximize treatment effectiveness.

The necessity of personalized medicine becomes particularly evident with the development of a future individualized healthcare system. According to the BBC news interview by Allen D. Roses, a former senior vice president at GlaxoSmithKline, he criticized that 90% of drugs have a therapeutic effect on only 30-50% of patients. A standardized treatment was applied to the specific disease, but different therapeutic efficacy was observed among patients due to the unique variations of their genome. In the case of cancer, tumor heterogeneity has been observed to be associated with the clinical outcome of cancer immunotherapy, so personalized medicine with the help of accurate diagnostic techniques would be necessary.

Accurate diagnosis on patients’ circumstances must be performed in order to apply personalized medicine. Biomarkers are required to select patients eligible for certain treatments via genomic, proteomic and metabolome analysis. Biomarker refers to the biological measurable characteristic as an indicator of drug resistance and response or current status of disorders. Biomarkers can also be used in the clinical trials for the development of new pharmaceuticals and in the selection of eligible patients who are expected to be treated with certain drugs.

Personalized medicine can be applied in the field of pharmacy as an example of anticoagulant, Warfarin. Warfarin may lead to acute cardiac failure, hemorrhage, necrosis, and osteoporosis depending on the genetic variations in CYP2CP and VKORC1 gene. Since the doses of prescribed warfarin vary by about 10-fold based on the genetic variation of each patient, U.S. Food and Drug Administration (FDA) recommends that prescription dose should be measured through genetics testing of patients when prescribing warfarin. Furthermore, gefitinib, which is an inhibitor of EGFR-tyrosine kinase used for particular breast, lung and other cancers, has a therapeutic efficacy on only breast cancer or non-small cell lung cancer that their cell signal transduction pathways of EGFR-tyrosine kinase are activated by individual’s genetic variations. Thus, gefitinib is only prescribed to patients who are in urgent need after genetic testing.

Cost of the sequencing
Price of DNA sequencing was very expensive until recently. Whole genome sequencing cost about $20,000 during the 2010s. WGS and WES are relatively recent technologies in clinical practice. Current data of health economic evidence to encourage use of WES and WGS in clinical research is restricted. Hence, there are not enough studies that carefully evaluate and indicate the cost-effectiveness of these technologies and components that are included in cost estimates. This made only developed countries like the USA or Great Britain were able to conduct population genetics study using WES and WGS. It was time-consuming and expensive. However, the development of Artificial Intelligence and the knowledge of big data and machine learning, enabled researchers to analyze massive loads of DNA sequencing faster and efficiently. Now the price of Whole genome sequencing fell to the lowest $1500. Single tests for WES range from $555 to $5,169 for WES and from $1906 to $24,810 for WGS. It is decreasing with the time and development of technologies. Currently, due to the notable decrease of the cost, countries apart from the developed countries, are planning to do WGS of the unique patients or by conducting joint study to get a foundation to form a big data of population genetics.

Shift in infrastructure
The importance of engineering and computation has been brought to the attention of clinics and the marketplace in compliance with their incorporation into the medical field and growing public demand for individualized health care services. Computer-based analytical platforms using Artificial Intelligence (AI), and Machine Learning (ML) are practicable for clinical trial use. They were able to determine patient-specific optimal treatments and therapies based on subpopulation-specific stratifications classified by genome sequencing. According to the study carried out by the AI platform, liver transplant immunosuppressant prescriptions were successfully recommended depending on the patient’s genetic information, and it confirmed that there was less inter-patients variance in AI-derived drug recommendation compared to control cohort patients. Computational analytical platforms predict patients’ response towards drugs and accelerate the process of reconstructing medical drugs and device validation. The integration of computer programming and personalized medicine enables a large number of patients to receive personal care in a short period of time with greater efficiency.

Political Change
Medical community follows an increasing trend of translating traditional medicine into personalized medicine, and long-held regulatory policies are obstacles to be resolved for its public usage. The United States took action via the enactment of the 21st Century Cures Act in 2016. This enforcement provided financial aid to U.S. Food and Drug Administration (FDA), allowing to accelerate the emergence of newly personalized products such as cell therapy and medical devices into the marketplace. Also, National Institutes of Health (NIH) benefited from the resource allocation. Many countries have introduced legislation for the improvement of personalized medicine. In Singapore, AI Singapore, a national AI initiative supported by National Research Foundation, was able to enhance national AI capabilities in drug development and patient-centered care. In addition, the Innovative Medicines Initiative (IMI) was established between the European Union (EU) and pharmaceutical companies with the purpose of developing medical devices, drugs, and vaccines to tackle major challenges that will imperil the EU.