Medical genomic can be defined as the utilization of genome-based information in the making of clinical decisions. A broader concept, personalized medicine, is often used to describe the models of healthcare that emphasize the application of an individual’s unique environmental, genomic, genetic, and clinical information to the treatment and prevention of diseases (Brunicardi; Offit). In their practice, doctors combine the results of patient data, which include individual genomic information, family history, medical history, conventional test results, and symptoms. The combination of the data allows the physicians to diagnose diseases accurately and personalize treatment strategies (Alzu’bi et al.). Typically, health information management professionals play critical roles in personalized healthcare practices because they focus on the management of patient data. In recent years, biotechnologies have improved significantly and the time and cost of DNA sequencing has decreased rapidly. Consequently, genomics-based individualized medicine has been implemented in many healthcare settings (Manolio et al.; Weitzel et al.). Moreover, physicians continue to order the sequencing of the whole genome for their clients whereas other healthcare practitioners perform genomic data analyses to determine the genetic causes of certain disorders (Kerschner 224). Different hospitals, particularly “Children’s Mercy Hospital in Kansas City and the University of Pittsburgh Medical Center” have taken considerable steps towards genomics-based individualized medicine (Alzu’bi et al.). In 2013, FDA (Food and Drug Administration) authorized the marketing of the genomic sequencer identified as Illumina’s MiSeqDx (Alzu’bi et al.). The authorization marked a significant step in the application of genomic information to healthcare settings because it allowed the utilization and development of numerous novel genomic-based tests (Collins and Hamburg). Also, the “FDA and the National Institute for Standards and Technology” continue to collaborate in creating genomic references for performance evaluation, including the “whole human genome DNA and the best possible sequence interpretation of such genomes” (Alzu’bi et al.). A wide utilization of genomic information in healthcare is likely to allow connections between the information and current systems of electronic health records in various ways (Hazin et al.; Kannry and Williams). For example, the connections may occur as a single component of data sets or as external links to stand-alone databases of genomic information. In both cases, professionals dealing with health information management will be required to manage and protect the genomic sets of data and extract useful information (Alzu’bi et al.). Presently, many such experts have the needed knowledge and skills to manage genomic information. For instance, they possess the knowledge of ethical issues associated with patient records, policies and procedures for handling ethical and legal issues, regulations related to patients’ data, statistical analysis, sensitive data decryption and encryption, and database management. In the present paper, the relationship between personalized medicine and genomics is examined. The applications of personalized genomics are then examined.
Usually, conventional clinical genetics focuses on the identification of monogenic disorders, which are often pre-specified based on the patient’s medical history, ethnicity, and family history (Ropers; Becker et al.; Gallati). Typically, the variants or mutations have high penetrance, which increases the likelihood that a person with the mutation will develop the disorder. With regards to service culture and organization, departments of medical genetics involve specialist units that may be located in a tertiary care facility, linked with well-equipped testing laboratories, or staffed by specialists in medical genetics and well-trained genetic counselors (Wilson and Nicholls). Additionally, patients are often referred based on reports about unusual medical or family history or diagnoses of suspected genetic conditions. In clinical genetics, the process of genetic evaluation is painstaking because it concentrates on examining patients’ family history comprehensively. Moreover, genetic counseling includes the assessment of the emotional needs of a patient. Nonetheless, the process is non-directive because doctors must individualize the balance of harms and benefits. On the other hand, personalized medicine has broader applications across the healthcare industry. In particular, it incorporates genetic profiling with the aim of providing personal risk information concerning multifactorial disorders, such as diabetes, cancers (Pogribny 132), and cardiovascular disease (Lotta 74), which result from the interaction between non-genomic elements and polygenic factors.
Genomics has made significant impacts on pharmacogenomics and continues to influence the development of novel treatment modalities. Basically, pharmacogenomics involves the examination of genetic variations linked to the variable reactions that individuals show towards a particular drug treatment (Bloss et al.). The responses include differences in the efficacy of drugs and individuals’ susceptibility to various adverse effects. Pharmacogenomics offers one of the clearest examples of the utilization of genomics in the development of individualized and targeted treatments, as well as the influence of genomics on clinical care. Over the last several years, researchers have made numerous associations among genetic variants with many studies clarifying the differences in drug response that occur in different people. The progress has included the now “well-known association between CYP2C9 and VKORC1 gene variants and Warfarin” (Bloss et al.). Warfarin is commonly used as an anticoagulant medication that helps to prevent venous thromboembolism and stroke. Studies, however, have demonstrated that the dosing of Warfarin involves clinical complications resulting from drug-drug and dietary interactions, as well as genetic factors like “variants in the genes CYP2C9 and VKORC1” (Bloss et al.). Estimates have shown that genotypes across the gene variants and factors like body size and age account for approximately 35 to 60 percent of the variability in the dosing requirements of Warfarin. In the recent past, the understanding of the role of such variants in Warfarin metabolism has prompted the “U.S. Food and Drug Administration (FDA) to update the labeling of Warfarin in 2007” to incorporate statements acknowledging the potential and importance of genotyping in the early stage of dosing (Bloss et al.). Further research has led the FDA to update the Warfarin labeling to include particular ranges of the initial dose assigned to different genotypes to represent the “expected steady state maintenance doses” (Bloss et al.). As such, research efforts in pharmacogenomics and the resulting FDA updates have improved drug efficacy and safety significantly. The improvement is a representation of the ongoing progress in the application of genomics to disease treatment, as well as in the prevention of harmful effects and the development of individualized medicine.
Recently, the Institute of Medicine described several case studies involving genomic-based drug development and discovery. One of the studies reported the application of FDA-approved crizotinib to the “treatment of non-small-cell lung cancer” (Institute of Medicine). The development of the drug demonstrates that approaches based on genomics can yield novel diagnostics and drugs with beneficial implications for global health. Crizotinib was initially identified as PF-02341066 with the brand name XALKORI. The drug consists of tiny molecules that bind to the kinases’ catalytic site and compete with ATP resulting in the inhibition of kinase activity. The drug’s primary targets include the “receptor tyrosine kinases known as c-MET, ALK, and ROS” (Institute of Medicine). Following the successful treatment of first patients who were considered “anaplastic lymphoma kinase (ALK)-positive,” FDA approved crizotinib within four years (Fig. 1) (Institute of Medicine).
Figure 1. Crizotinib’s Rapid Development (Source: Institute of Medicine). The figure shows that the development of Crizotinib proceeded swiftly from the identification of the compound through target discovery and clinical result to approval by the FDA.
Although pharmacogenomic findings and research have prompted the FDA to take significant forward steps in the translation of genomic research findings into individualized and better treatment modalities, there is a need for further research into the heritable traits that cause adverse reactions to medications like antipsychotics and antidepressants.
In conclusion, medical genomic involves the utilization of genome-based information in clinical decision-making processes. Personalized medicine, however, is a broader concept referring to healthcare models that emphasize the application of patients’ unique environmental, genomic, genetic, and clinical information to the treatment and prevention of various diseases. The present study has demonstrated the important impacts of genomics on the future development of novel treatment modalities. Nevertheless, there is a requirement for further research into prevailing problems such as the gene-related adverse reactions that individuals experience towards certain drugs.
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