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The field of pharmacogenetics (PGx) holds great promise in advancing personalized medicine by adapting treatments based on individual genetic profiles. Despite its benefits, there are still economic, ethical and institutional barriers that hinder its implementation in our healthcare environment. A retrospective analysis approach of anonymized data sourced from electronic health records was performed, encompassing a diverse patient population and evaluating key parameters such as prescribing patterns and test results, to assess the impact of pharmacogenetic testing. A head-to-head comparison with previously published activity results within the same pharmacogenetic laboratory was also conducted to contrast the progress made after 10 years. The analysis revealed significant utilization of pharmacogenetic testing in daily clinical practice, with 1,145 pharmacogenetic tests performed over a 1-year period and showing a 35% growth rate increase over time. Of the 17 different medical departments that sought PGx tests, the Oncology department accounted for the highest number, representing 58.47% of all genotyped patients. A total of 1,000 PGx tests were requested for individuals susceptible to receive a dose modification based on genotype, and 76 individuals received a genotype-guided dose adjustment. This study presents a comprehensive descriptive analysis of real-world data obtained from a public tertiary hospital laboratory specialized in pharmacogenetic testing, and presents data that strongly endorse the integration of pharmacogenetic testing into everyday clinical practice.

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Thiopurine methyltransferase (TPMT) is the rate-limiting enzyme in Azathioprine (AZA) metabolization. Although studies have discussed the association between the TPMT polymorphisms and myelosuppression, the data about the relationship between TPMT genotypes and hepatoxicity in Asian patients remain limited. This study investigated the correlation between TPMT polymorphisms and AZA-related hepatotoxicity. This study enrolled the patients who had prior exposure to AZA from the Taichung Veterans General Hospital (TCVGH)-Taiwan Precision Medicine Initiative (TPMI) cohort. Genetic variants were determined using a single nucleotide polymorphism (SNP) array. Participants were accordingly categorized into normal metabolizer (NM) and non-normal metabolizer (non-NM) groups. From the TCVGH-TPMI cohort, we included 50 TPMT non-NM patients, including 1 poor metabolizer (PM), 49 intermediate metabolizers (IMs), and 1000 NM patients. The non-NM genotype was associated with hepatotoxicity compared with the NM genotype (hazard ratio (HR): 3.85, 95% confidence interval (CI): 1.83−8.10). In the non-NM group, the 3-year cumulative incidence of hepatotoxicity was higher than that in the NM group at 8.5% in the first year and 18.6% in the second and third years (p < 0.001). A TPMT non-NM genotype was associated with the occurrence of hepatotoxicity following AZA therapy. Preemptive testing helps individualize AZA therapy by minimizing the risk of hepatotoxicity.

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BACKGROUND: Several type B adverse drug reactions (ADRs), especially severe cutaneous adverse reactions (SCARs), are associated with particular human leukocyte antigen (HLA) genotypes. However, pre-stored HLA information obtained from other clinical workups has not been used to prevent ADRs. We aimed to simulate the preemptive use of pre-stored HLA information in electronic medical records to evaluate whether this information can prevent ADRs. METHODS: We analyzed the incidence and the risk of ADRs for selected HLA alleles (HLA-B*57:01, HLA-B*58:01, HLA-A*31:01, HLA-B*15:02, HLA-B*15:11, HLA-B*13:01, HLA-B*59:01, and HLA-A*32:01) and seven drugs (abacavir, allopurinol, carbamazepine, oxcarbazepine, dapsone, methazolamide, and vancomycin) using pre-stored HLA information of transplant patients based on the Pharmacogenomics Knowledge Base guidelines and experts' consensus. RESULTS: Among 11,988 HLA-tested transplant patients, 4092 (34.1%) had high-risk HLA alleles, 4583 (38.2%) were prescribed risk drugs, and 580 (4.8%) experienced type B ADRs. Patients with HLA-B*58:01 had a significantly higher incidence of type B ADR and SCARs associated with allopurinol use than that of patients without HLA-B*58:01 (17.2% vs. 11.9%, odds ratio [OR] 1.53 [95% confidence interval {CI} 1.09-2.13], p = 0.001, 2.3% versus 0.3%, OR 7.13 [95% CI 2.19-22.69], p < 0.001). Higher risks of type B ADR and SCARs were observed in patients taking carbamazepine or oxcarbazepine if they had one of HLA-A*31:01, HLA-B*15:02, or HLA-B*15:11 alleles. Vancomycin and dapsone use in HLA-A*32:01 and HLA-B*13:01 carriers, respectively, showed trends toward increased risk of type B ADRs. CONCLUSION: Utilization of pre-stored HLA data can prevent type B ADRs including SCARs by screening high-risk patients.

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Currently, there is sufficient evidence for the use of pharmacogenetic information to optimize medication prescribing, but why has this information not been integrated into the drug prescribing process to improve patient care? A discussion about the major contributing factors that have limited the use of pharmacogenetic information in the drug prescribing process, the solutions to ensure widespread uptake, and a vision for the future of the pharmacogenetic field will be explored.

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BACKGROUND: Thiopurine methyltransferase (TPMT) gene variants have achieved limited success in predicting the outcome of thiopurine therapy, which shows wide inter-individual variations. The literature indicates a strong association between the NUDT15 gene variant and thiopurine-induced toxicity in Asian patients. The present study intends to explore the role of the NUDT15 variant (C415T) in Indian patients on thiopurine therapy. METHODS: NUDT15 and TPMT genotyping were performed using amplification-refractory mutation system-polymerase chain reaction (ARMS-PCR) and the restriction fragment length polymorphism (RFLP) technique. RESULTS: Of 370 samples received for TPMT testing, 206 samples were available for NUDT15 genotyping. The NUDT15 risk allele frequency was 10.7%, with the frequency of wild, heterozygous and mutant genotypes being 80.6%, 17.5% and 1.9%, respectively. TPMT variants were seen in 13 of 370 (3.5%) patients, whereas the NUDT15 variant was seen in 40 of 206 (19.4%) patients. Thiopurine-induced toxicity information was available for 101 patients, among whom 10 developed leukopenia and all harbored the NUDT15 variant (p<0.0001). NUDT15 was clinically more relevant than TPMT in terms of sensitivity and specificity, as well as with a statistically significant difference in thiopurine dose requirement for patients with the NUDT15 variant. CONCLUSIONS: A preemptive NUDT15 genotyping approach can therefore help identify high-risk patients (NUDT15 C415T positive) who could benefit from thiopurine dose reduction, thereby preventing fatal thiopurine-induced toxicity.

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The incorporation of precision medicine into the clinical setting is becoming increasingly feasible with the availability of more affordable genetic sequencing technologies and successful genetic associations with phenotypes, especially in the pharmacogenomic field. Although substantial progress has been made to ensure successful uptake of pharmacogenomic testing in the clinical setting already, many challenges still remain for sustainable implementation. The importance of pharmacogenomic information in patient care, identifying key barriers, and proposed solutions for advancing pharmacogenomic implementation will be discussed.

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Pharmacogenomics, once hailed as a futuristic approach to pharmacotherapy, has transitioned to clinical implementation. Although logistic and economic limitations to clinical pharmacogenomics are being superseded by external measures such as preemptive genotyping, implementation by clinicians has met resistance, partly due to a lack of education. Pharmacists, with extensive training in pharmacology and pharmacotherapy and accessibility to patients, are ideally suited to champion clinical pharmacogenomics. This study aimed to analyze the outcomes of an innovative pharmacogenomic teaching approach. Second-year student pharmacists enrolled in a required, 15-week pharmaceutical care lab course in 2015 completed educational activities including lectures and small group work focusing on practical pharmacogenomics. Reflecting the current landscape of direct-to-consumer (DTC) genomic testing, students were offered 23andMe genotyping. Students completed surveys regarding their attitudes and confidence on pharmacogenomics prior to and following the educational intervention. Paired pre- and post-intervention responses were analyzed with McNemar's test for binary comparisons and the Wilcoxon signed-rank test for Likert items. Responses between genotyped and non-genotyped students were analyzed with Fisher's exact test for binary comparisons and the Mann-Whitney U-test for Likert items. Responses were analyzed for all student pharmacists who voluntarily completed the pre-intervention survey (N = 121, 83% response) and for student pharmacists who completed both pre- and post-intervention surveys (N = 39, 27% response). Of those who completed both pre- and post-intervention surveys, 59% obtained genotyping. Student pharmacists demonstrated a significant increase in their knowledge of pharmacogenomic resources (17.9 vs. 56.4%, p < 0.0001) and confidence in applying pharmacogenomic information to manage patients' drug therapy (28.2 vs. 48.7%, p = 0.01), particularly if the student had received genotyping. Student pharmacists understanding of the risks and benefits of using personal genome testing services significantly increased (55.3 vs. 86.8%, p = 0.001) along with agreement that personal genomics would likely play an important role in their future career (47.4 vs. 76.3%, p = 0.01), particularly among students who participated in genotyping. The educational intervention, including personal genotyping, was feasible, and positively enhanced students' reflections, and attitudes toward pharmacogenomics in a professional pharmacy program.

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AIMS: Interindividual variability in drug response and adverse effects have been described for proton pump inhibitors, anticonvulsants, selective serotonin reuptake inhibitors, tricyclic antidepressants, and anti-infectives, but little is known about the safety and efficacy of these medications in patients with sickle cell disease (SCD). We genotyped the CYP2C19 gene which has been implicated in the metabolism of these drugs in an SCD patient cohort to determine the frequencies of reduced function, increased function, or complete loss-of-function variants. MATERIALS AND METHODS: DNAs from 165 unrelated SCD patients were genotyped for nine CYP2C19 (*2, *3, *4, *5, *6, *7,*8, *12, and *17) alleles using the iPLEX® ADME PGx multiplex panel. RESULTS: Three CYP2C19 alleles (*2, *12, and *17) were detected with the following frequencies: 0.209, 0.006, and 0.236, respectively. The predicted phenotype frequencies were distributed as extensive (31.5%), intermediate (24.8%), poor (5.5%), ultrarapid (30.3%), and unknown metabolizers (7.9%). DISCUSSION: Prognostic genotyping is potentially useful for identifying SCD patients with allelic variants linked to proven clinical pharmacokinetic consequences for several drugs metabolized by the CYP2C19 gene. However, the main challenge to implementing a genetics-guided prescribing practice is ensuring concordance between CYP2C19 genotypes and metabolic phenotypes in SCD patients.

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