and tamoxifen, respectively. in cardiovascular disorders, the main concern is response to drugs including warfarin, clopidogrel, beta blockers, and statins. in patients with cyp2c19, who take clopidogrel, cardiovascular risk is elevated, leading to medication package insert updates by regulators. in patients with type 2 diabetes, haptoglobin (hp) genotyping shows an effect on cardiovascular disease, with hp2-2 at higher risk and supplemental vitamin e reducing risk by affecting hdl. in psychiatry, as of 2010, research has focused particularly on 5-httlpr and drd2. clinical implementation further information: education in personalized medicine initiatives to spur adoption by clinicians include the ubiquitous pharmacogenomics (u-pgx) program in europe and the clinical pharmacogenetics implementation consortium (cpic) in the united states. in a 2017 survey of european clinicians, in the prior year two-thirds had not ordered a pharmacogenetic test. in 2010, vanderbilt university medical center launched pharmacogenomic resource for enhanced decisions in care and treatment (predict); in 2015 survey, two-thirds of the clinicians had ordered a pharmacogenetic test. in 2019, the largest private health insurer, unitedhealthcare, announced that it would pay for genetic testing to predict response to psychiatric drugs. in 2020, canada's 4th largest health and dental insurer, green shield canada, announced that it would pay for pharmacogenetic testing and its associated clinical decision support software to optimize and personalize mental health prescriptions. reduction of polypharmacy a potential role for pharmacogenomics is to reduce the occurrence of polypharmacy: it is theorized that with tailored drug treatments, patients will not need to take several medications to treat the same condition. thus they could potentially reduce the occurrence of adverse drug reactions, improve treatment outcomes, and save costs by avoiding purchase of some medications. for example, maybe due to inappropriate subscribing, psychiatric patients tend to receive more medications than age-matched non-psychiatric patients. the need for pharmacogenomically tailored drug therapies may be most evident in a survey conducted by the slone epidemiology center at boston university from february 1998 to april 2007. the study elucidated that an average of 82% of adults in the united states are taking at least one medication (prescription or nonprescription drug, vitamin/mineral, herbal/natural supplement), and 29% are taking five or more. the study suggested that those aged 65 years or older continue to be the biggest consumers of medications, with 17-19% in this age group taking at least ten medications in a given week. polypharmacy has also shown to have increased since 2000 from 23% to 29%. example case studies case a – antipsychotic adverse reaction patient a has schizophrenia. their treatment included a combination of ziprasidone, olanzapine, trazodone and benztropine. the patient experienced dizziness and sedation, so they were tapered off ziprasidone and olanzapine, and transitioned to quetiapine. trazodone was discontinued. the patient then experienced excessive sweating, tachycardia and neck pain, gained considerable weight and had hallucinations. five months later, quetiapine was tapered and discontinued, with ziprasidone re-introduced into their treatment, due to the excessive weight gain. although the patient lost the excessive weight they had gained, they then developed muscle stiffness, cogwheeling, tremors and night sweats. when benztropine was added they experienced blurry vision. after an additional five months, the patient was switched from ziprasidone to aripiprazole. over the course of 8 months, patient a gradually experienced more weight gain and sedation, and developed difficulty with their gait, stiffness, cogwheeling and dyskinetic ocular movements. a pharmacogenomics test later proved the patient had a cyp2d6 *1/*41, which has a predicted phenotype of im and cyp2c19 *1/*2 with a predicted phenotype of im as well. case b – pain management patient b is a woman who gave birth by caesarian section. her physician prescribed codeine for post-caesarian pain. she took the standard prescribed dose, but she experienced nausea and dizziness while she was taking codeine. she also noticed that her breastfed infant was lethargic and feeding poorly. when the patient mentioned these symptoms to her physician, they recommended that she discontinue codeine use. within a few days, both the patient's and her infant's symptoms were no longer present. it is assumed that if the patient had undergone a pharmacogenomic test, it would have revealed she may have had a duplication of the gene cyp2d6, placing her in the ultra-rapid metabolizer (um) category, explaining her reactions to codeine use. case c – fda warning on codeine overdose for infants on february 20, 2013, the fda released a statement addressing a serious concern regarding the connection between children who are known as cyp2d6 um, and fatal reactions to codeine following tonsillectomy and/or adenoidectomy (surgery to remove the tonsils and/or adenoids). they released their strongest boxed warning to elucidate the dangers of cyp2d6 ums consuming codeine. codeine is converted to morphine by cyp2d6, and those who have um phenotypes are in danger of producing large amounts of morphine due to the increased function of the gene. the morphine can elevate to life-threatening or fatal amounts, as became evident with the death of three children in august 2012. challenges consecutive phases and associated challenges in pharmacogenomics. although there appears to be a general acceptance of the basic tenet of pharmacogenomics amongst physicians and healthcare professionals, several challenges exist that slow the uptake, implementation, and standardization of pharmacogenomics. some of the concerns raised by physicians include: limitation on how to apply the test into clinical practices and treatment; a general feeling of lack of availability of the test; the understanding and interpretation of evidence-based research; combining test results with other patient data for prescription optimization; and ethical, legal and social issues. issues surrounding the availability of the test include: the lack of availability of scientific data: although there are considerable number of dme involved in the metabolic pathways of drugs, only a fraction have sufficient scientific data to validate their use within a clinical setting; and demonstrating the cost-effectiveness of pharmacogenomics: publications for the pharmacoeconomics of pharmacogenomics are scarce, therefore sufficient evidence does not at this time exist to validate the cost-effectiveness and cost-consequences of the test. although other factors contribute to the slow progression of pharmacogenomics (such as developing guidelines for clinical use), the above factors appear to be the most prevalent. increasingly substantial evidence and industry body guidelines for clinical use of pharmacogenetics have made it a population wide approach to precision medicine. cost, reimbursement, education, and easy use at the point of care remain significant barriers to widescale adoption. controversies race-based medicine there has been call to move away from race and ethnicity in medicine and instead use genetic ancestry as a way to categorize patients. some alleles that vary in frequency between specific populations have been shown to be associated with differential responses to specific drugs. as a result, some disease-specific guidelines only recommend pharmacogenetic testing for populations where high-risk alleles are more common and, similarly, certain insurance companies will only pay for pharmacogenetic testing for beneficiaries of high-risk populations. genetic exceptionalism in the early 2000’s, handling genetic information as exceptional, including legal or regulatory protections, garnered strong support. it was argued that genomic information may need special policy and practice protections within the context of electronic health records (ehrs). in 2008, the genetic information nondiscrimination act (gina) was enacted to protect patients from health insurance companies discriminating against an individual based on genetic information. more recently it has been argued that genetic exceptionalism is past its expiration date as we move into a blended genomic/big data era of medicine, yet exceptionalism practices continue to permeate clinical healthcare today. garrison et al recently relayed a call to action to update verbiage from genetic exceptionalism to genomic contextualism in that we recognize a fundamental duality of genetic information. this allows room in the argument for different types of genetic information to be handled differently while acknowledging that genomic information is similar and yet distinct from other health-related information. genomic contextualism would allow for a case-by-case analysis of the technology and the context of its use (e.g., clinical practice, research, secondary findings). others argue that genetic information is indeed distinct from other health-related information but not to the extent of requiring legal/regulatory protections, similar to other sensitive health-related data such as hiv status. additionally, evans et al. argue that the ehr has sufficient privacy standards to hold other sensitive information such as social security numbers and that the fundamental nature of an ehr is to house highly personal information. similarly, a systematic review reported that the public had concern over privacy of genetic information, with 60% agreeing that maintaining privacy was not possible; however, 96% agreed that a direct-to-consumer testing company had protected their privacy, with 74% saying their information would be similarly or better protected in an ehr. with increasing technological capabilities in ehrs, it is possible to mask or hide genetic data from subsets of providers and there is not consensus on how, when, or from whom genetic information should be masked. rigorous protection and masking of genetic information is argued to impede further scientific progress and clinical translation into routine clinical practices. future computational advances have enabled cheaper and faster sequencing. research has focused on combinatorial chemistry, genomic mining, omic technologies, and high throughput screening. as the cost per genetic test decreases, the development of personalized drug therapies will increase. technology now allows for genetic analysis of hundreds of target genes involved in medication metabolism and response in less than 24 hours for under $1,000. this a huge step towards bringing pharmacogenetic technology into everyday medical decisions. likewise, companies like decode genetics, md labs pharmacogenetics, navigenics and 23andme offer genome scans. the companies use the same genotyping chips that are used in gwas studies and provide customers with a write-up of individual risk for various traits and diseases and testing for 500,000 known snps. costs range from $995 to $2500 and include updates with new data from studies as they become available. the more expensive packages even included a telephone session with a genetics counselor to discuss the results. ethics pharmacogenetics has become a controversial issue in the area of bioethics. privacy and confidentiality are major concerns. the evidence of benefit or risk from a genetic test may only be suggestive, which could cause dilemmas for providers.: 145 drug development may be affected, with rare genetic variants possibly receiving less research. access and patient autonomy are also open to discussion.: 680 web-based resources web resources for pharmacogenomics data sourcemain usecitation pharmvara central repository for pharmacogene variation that focuses on haplotype structure and allelic variation supercyp bioinformatics toolcontaining 1170 drugs with more than 3800 interactions, and approximately 2000 known snps. these snps are listed and ordered according to their effect on expression and/or activity. pharmgkbthe pharmacogenomics knowledge base (pharmgkb) is an interactive tool for researchers investigating how genetic variation affects drug response. dbsnp databasea repository of snps and other variants that have been reported after discovery, compiled and officially named. these are snps across the board. findbaserepository of allele frequencies of pharmacogenetic markers in different populations pharmacogenomics biomarkers in drug labellinga table that identifies which fda-approved drugs have pharmacogenomics-related warning labels snpediaa wiki-based bioinformatics database of snps pharmacogenomics research network (pgrn) the pgrn hosts resources and information to stimulate collaborative research in pharmacogenomics and precision medicine.