Recent regulatory and guideline changes have established pretreatment DPYD genotyping as a critical strategy to prevent severe fluoropyrimidine toxicity. Following earlier European leadership by the European Medicines Agency, the US Food and Drug Administration added boxed warnings to capecitabine and 5-fluorouracil labels recommending genetic testing before therapy. Concurrent updates from the National Comprehensive Cancer Network and ASCO align US with European practice supporting universal testing. Fluoropyrimidines remain foundational treatments across multiple cancers but can cause life-threatening toxicity in patients with dihydropyrimidine dehydrogenase (DPD) deficiency, most commonly because of inherited DPYD variants. DPYD variant carriers receiving standard doses experience markedly increased risk of severe toxicity and treatment-related mortality, emphasizing the clinical importance of DPYD testing and genotype-guided dosing. Evidence demonstrates that dose individualization based on guidance from the Clinical Pharmacogenetics Implementation Consortium reduces toxicity risk while maintaining treatment effectiveness and potentially reducing overall costs. Patient advocacy, particularly efforts led by Advocates for Universal DPD/DPYD Testing, has accelerated policy change, increased clinician awareness, and highlighted ethical implications of preventable harm. Despite growing adoption, implementation challenges persist, including workflow integration, clinician education, and equitable access. Integrated health systems such as the Veterans Health Administration demonstrate how centralized infrastructure and clinical decision support can facilitate uptake. Barriers are more pronounced in resource-constrained settings, where limited infrastructure, reimbursement uncertainty, and insufficient pharmacogenomic education hinder implementation. Regional initiatives illustrate education-focused, context-adapted strategies to expand testing and address population-specific variant knowledge gaps. Collectively, emerging evidence, regulatory alignment, and advocacy efforts position DPYD genotyping as a patient-safety imperative necessary to achieve safer, more equitable fluoropyrimidine therapy worldwide.

Sulfamethoxazole-trimethoprim-induced Stevens-Johnson syndrome in a NAT2 slow acetylator: A case for pre-emptive pharmacogenomic screening?

Genomic profiling of patients for genetic variants that modify the effect of specific medications has many benefits, including the possibility of avoiding toxicities and ensuring an adequate effect of the medication. Our intention was to develop a comprehensive, high-quality pharmacogenetic test panel for clinical use with a less expensive technique than high-coverage whole-genome sequencing. We designed a targeted pan-pharmacogenomics (pan-PGx) panel based on Twist probe capture by applying Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines and aggregated data from PharmVar, PharmGKB and IPD-IMGT/HLA. Sequencing was performed using Illumina short-read sequencing. In-house computer scripts combined with freely available software, particularly PharmCAT, were used for the analysis. Validation was largely performed with Genetic Testing Reference Materials Coordination Program (GeT-RM) DNA from Coriell when applicable, otherwise with DNA from clinically well-documented material. The validation showed that the method is both accurate and well-suited for large-scale clinical testing of pharmacogenes. Calls of single-nucleotide variants, InDels, and structural/hybrid genes and copy number variants in all major pharmacogenes could be translated into dose recommendations, making the test appropriate for clinical use. This assay is suitable for clinical use and pharmacogenomic-guided drug treatments.

Clopidogrel is an antiplatelet agent widely utilized in cardiology. It is a prodrug activated in the liver by the cytochrome P450 isoform CYP2C19. Variability in the CYPC2C19 gene influences the activation and efficacy of clopidogrel. This is covered in guidelines from the Clinical Pharmacogenetics Implementation Consortium, the Dutch Pharmacogenetics Working Group, and more recently the UK Centre of Excellence in Regulatory Science and Innovation in Pharmacogenomics. Despite this extensive guidance, pharmacogenetic information is rarely used to guide clopidogrel prescription in cardiology patients. The present study assesses the visibility of the pharmacogenetic guidelines in the cardiology literature. We analyzed citations of the clopidogrel pharmacogenetic guidelines in the cardiology literature and in the cardiology guidelines/position statements on the treatment of acute coronary syndromes and stable coronary artery disease. Citations of these guidelines were found to be limited in the cardiology literature. Only 3 out of 19 cardiology guidelines/position statements refer to the pharmacogenetic guidelines. 58% of the cardiology guidelines/position statements mention clopidogrel pharmacogenetics but suggest that the use of pre-emptive genotyping for CYP2C19 variants to guide clopidogrel prescription is of limited clinical relevance. Genetically determined variation in clopidogrel efficacy has poor visibility in the cardiology literature and clinical guidelines. It is perceived to have limited benefits for clinical practice despite mounting evidence from randomized controlled trials and systematic reviews/meta-analyses.

5-hydroxytryptamine type 3 (5-HT3) receptor antagonists are used to treat nausea and vomiting and in the prevention of chemotherapy-induced, radiation-induced, and postoperative nausea and vomiting. Most of the 5-HT3 receptor antagonists (i.e., ondansetron, tropisetron, dolasetron, palonosetron, and ramosetron) are metabolized by CYP2D6, but the extent of CYP2D6 involvement varies. CYP2D6 genetic variation can influence the metabolism of these medications, particularly ondansetron and tropisetron, thereby affecting drug efficacy. This guideline is an update to the 2016 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 genotype and use of ondansetron and tropisetron and includes updated information on CYP2D6 genetic testing and evidence tables. We summarize evidence from the published literature supporting these associations and provide therapeutic recommendations for 5-HT3 receptor antagonists based on CYP2D6 genotype, particularly where genetic variation is associated with reduced drug efficacy (updates at https://www.clinpgx.org/guideline/PA166251457).

(1) Background: This follow-up retrospective analysis used electronic medical record (EMR) data from a health system to identify patients and medications prescribed in accordance with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. (2) Methods: This analysis included EMR data from a clinical research data warehouse encompassing 928,291 patients seen at an academic medical center between 2020 and 2024. The study evaluated 75 commercially available medications linked to 52 evidence-based CPIC pharmacogenomic (PGx) guidelines. (3) Results: Of the 928,291 patient encounters, 709,673 medication orders were recorded, with 416,621 patients (44.8%) prescribed at least 1 of the 75 CPIC-associated medications. This compares with 845,518 patients who had an encounter in 2015-2019 with 590,526 medication orders, and 335,849 (56.9%) patients had medication orders represented by CPIC-associated medications. One to three CPIC-associated medications accounted for 76.6% of patients in 2020-2024 compared to 75.6% in 2015-2019. (4) Conclusions: The findings demonstrate that the proportion of patients prescribed a CPIC-actionable medication remained just under half of those evaluated within a single institution's EMR. About three-quarters of patients over the ten-year period had between one to three CPIC-associated medications identified, and the top five classes of medications remained the same in the two periods. This understanding of patient volume may help organizations as they begin to assess the implementation of PGx services.

Introduction:: Pharmacogenetics is revolutionising psychiatric care by providing insights into how genetic variants, particularly in CYP2D6 and CYP2C19, affect drug metabolism, efficacy, and side effects. These insights help clinicians tailor treatment for drugs such as SSRIs, tricyclic antidepressants, and antipsychotics, reducing trial-and-error prescribing and improving patient outcomes. This study aims to investigate the influence of genetic variations, particularly in CYP2D6 and CYP2C19, on drug metabolism, therapeutic effectiveness, and adverse effects in psychiatric treatment. Methods:: This systematic review integrates information from PharmGKB and the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, as well as data from PubMed, Medline, Scopus, Web of Science, Google Scholar, and reputable health organisations using keywords related to the study topic. Inclusion criteria encompassed peerreviewed articles, studies in English, and research published within the last 10 years. Exclusion criteria included non-relevant or duplicate studies. The selection process followed PRISMA guidelines, with data extraction focusing on study design, outcomes, and reliability to ensure transparency and credibility. The review also examines new findings, such as polygenic risk scores and expanded multigene testing platforms, and highlights clinically relevant gene–drug interactions, including the effect of CYP2D6 polymorphisms on risperidone metabolism. Results:: This study emphasises the significant role of pharmacogenetics in psychiatric treatment, specifically regarding genetic variants in CYP2D6 and CYP2C19. These genetic factors influence treatment with SSRIs, tricyclic antidepressants, and antipsychotics by altering medication metabolism, effectiveness, and adverse effects. The study examines key gene–drug interactions and emerging technologies such as polygenic risk scores, utilising data from PharmGKB, CPIC recommendations, and major medical databases. Discussion:: Despite its promise, widespread implementation faces challenges such as cost, accessibility, and the need for clinician education. Addressing these obstacles through improved insurance coverage and integration of electronic health records can advance precision medicine, thereby enhancing patient outcomes and reducing adverse effects. The gap can be narrowed by employing strategies such as increasing insurance coverage for testing and incorporating genetic decision-support tools into electronic health records. Conclusion:: Integrating pharmacogenetics into psychiatric care can improve treatment safety and precision. For broad adoption, challenges such as cost, test accessibility, and physician education must be addressed. This review supports a future in which pharmacogenetic insights guide psychiatric care to improve treatment outcomes and reduce adverse drug reactions.

DPYD testing can identify patients at risk for severe toxicity when a standard fluoropyrimidine antineoplastic dose is prescribed. Sequencing-based methods detect rare variants, which require classification. DPYD sequencing results over a 9-year period through to 2024 were analyzed. The dataset was filtered to calculate the positive test rate for different genotyping strategies, including targeted analysis of the Association for Molecular Pathology (AMP) Tier 1 and 2 recommended alleles, and as compared to sequencing. Variant classifications based on the laboratory's clinical protocol were compared to ClinVar classifications and designations by the Clinical Pharmacogenetics Implementation Consortium (CPIC) expert panel. A DPYD variant was reported in 12.79% (896/7003) of those tested, with 2.53% (170/7003) of all reports including a variant of uncertain significance. Had only AMP Tier 1 or both Tier 1 and 2 been tested, 9.30% and 9.44% of patients would have received a positive report, respectively. Among the 281 unique, non-Tier 1/Tier 2 variants encountered during sequencing, >80% were not classified by the CPIC expert panel, while >48% were not reported in ClinVar. Variant classifications by our laboratory and those in ClinVar were generally concordant with the CPIC expert panel, despite the lack of a standardized classification system. While AMP Tier 1 genotyping would have identified most patients at risk for fluoropyrimidine toxicity, sequencing is more comprehensive, identifying 26% more reportable variants compared to targeted genotyping. A standard framework for pharmacogenomic variant classification could facilitate consistent variant classification and a transition from targeted genotyping to sequencing.

Pharmacogenomic testing (PGx) is often completed after an adverse drug event (ADE) has occurred, but moving toward a preemptive rather than reactive testing approach could potentially decrease preventable drug-related hospitalizations and positively impact combat readiness. Although prior research has suggested that PGx testing may aid in individual patient medical management, there is limited research assessing the potential impact of preemptive PGx testing in the Military Health System (MHS). In this study, we utilized MHS prescription data along with available genotypic and phenotypic population frequency data to estimate the potential impact of PGx testing in the diverse MHS patient population. A retrospective cross-sectional study was conducted using fiscal year 2021 (FY21) prescription data from the Defense Health Agency (DHA) Pharmacy Operations Division. Medications that had Clinical Pharmacogenetics Implementation Consortium (CPIC) level A, A/B, and B designations prescribed to Active Duty, Reserve, Retired, and Dependent MHS beneficiaries ages 18 and up were included in the analyses. We evaluated the prescription count along with the age, biological sex, and MHS beneficiary status for medications prescribed within the MHS. We then estimated the number of MHS beneficiaries predicted to have non-normal metabolism of a given PGx-related medication. This data was presented as a range based on the CPIC allele and metabolizer frequency data which varies across PharmGKB-defined biogeographical groups. This study was approved and was determined exempt by the Uniformed Services University of Health Sciences (USUHS) and the Augustana University institutional review boards. There were over 8 million unique prescriptions for 83 PGx-related medications with CPIC level A, A/B, or B designation in FY21. Of these, over 1.2 million prescriptions (15%) were for Active Duty and Reserve members, with the top 5 prescribed PGx-related medications for Active Duty members being ibuprofen, ondansetron, hydrocodone, omeprazole, and meloxicam. This study further analyzed 64 medications with known metabolism frequency data. In FY21, there were up to 632,974 MHS beneficiaries taking omeprazole who were predicted to have non-normal CYP2C19 metabolism, which represents the medication with the highest number of prescriptions among individuals with estimated non-normal metabolism. Among medications with a risk for severe ADE, allopurinol was at the top with up to 301 prescriptions provided to Active Duty members estimated to have the *58:01 variant, which is associated with increased risk for toxic epidermal necrolysis. Currently, PGx testing is an underutilized resource in the MHS system, despite the many PGx-related medications that are widely prescribed among all MHS beneficiaries who have actionable CPIC guidelines. Based on published allele and metabolizer frequencies in the general population, a significant number of MHS beneficiaries taking these medications may be predicted to have non-normal metabolism and be at increased risk for adverse drug events and/or therapeutic failure. Given high prescription counts across all MHS beneficiaries, including Active Duty members, this data should be used to inform a preemptive PGx testing implementation approach in the MHS with the goal to reduce ADEs and therapeutic failure, while improving readiness among service members.

Interindividual variability in drug response poses a significant challenge in clinical practice, leading to treatment failure or adverse drug reactions (ADRs). A substantial portion of this variability is driven by genetic polymorphisms in key pharmacogenes. This review aims to synthesize the robust evidence and clinical guidelines for major gene-drug pairs and to discuss the critical evidence gaps hindering the equitable global implementation of pharmacogenomics. We conducted a comprehensive review of systematic reviews, meta-analyses, and clinical guidelines from consortia like the Clinical Pharmacogenetics Implementation Consortium (CPIC) for key gene-drug interactions, including CYP2C19-clopidogrel, CYP2C9/VKORC1-warfarin, SLCO1B1-statins, and SLC22A1-metformin. Furthermore, we examined the issue of population bias in genetic research and the need for real-world evidence. Strong evidence confirms that genetic variants significantly alter the efficacy and toxicity of numerous drugs. CPIC guidelines provide actionable recommendations for genotype-guided therapy, such as alternative antiplatelet agents for CYP2C19 poor metabolizers and dose adjustments for warfarin and statins.

ABSTRACTBackgroundTacrolimus is primarily metabolized by Cytochrome P450 (CYP)3A4/5. The Clinical Pharmacogenetics Implementation Consortium recommends increasing the initial dose 1.5‐ to 2‐fold in CYP3A5 expressers to enhance transplant outcomes. Our objective was to investigate the impact of CYP3A5 expresser status on tacrolimus dosing requirements and attainment of target trough concentrations in heart transplant recipients.MethodsWe performed a retrospective cohort analysis of tacrolimus dose, concentration, demographics, CYP3A4/5 genotype, concomitant medications, and biochemical data in heart transplant recipients from December 2020 to August 2023. The primary outcome was the time to first therapeutic trough concentration, compared by CYP3A5 expression status. Secondary outcomes included the tacrolimus dose at target trough and dose‐adjusted tacrolimus trough concentration (C0/D). Stepwise multiple regression was performed to account for potential covariates. Moreover, clinical outcomes were assessed at 1‐year post‐transplantation and compared based on CYP3A5 expression status.ResultsAmong 33 patients, CYP3A5 expressers (27.3%) required longer to achieve therapeutic trough concentrations (median [Q1, Q3]: expressers: 14 [9.5, 16] days vs. nonexpressers 7.5 [6.0, 11] days; p = 0.0073) and required nearly double the tacrolimus dose to reach target concentrations (10 [5.5, 13] mg/day for expressers vs. 5 [3.3, 5.9] mg/day for nonexpressers; p = 0.0019). Conversely, the C0/D was nearly 2‐fold higher in nonexpressers 2.0 [1.6, 3.4] ng/(mL*mg) than expressers (1.1 [0.83, 1.7] ng/(mL*mg); p = 0.0015). Stepwise regression identified route of administration (sublingual vs. oral) at therapeutic trough and initial dose as covariates for all outcomes. All clinical outcomes showed no significant differences based on CYP3A5 expression status, with the exception that poor metabolizers demonstrated higher serum creatinine elevation at 1‐week post‐transplantation (p = 0.047).ConclusionOur findings highlight the impact of CYP3A5 expresser status on the time needed and dosing requirements to attain tacrolimus therapeutic concentrations in heart transplant recipients, suggesting CYP3A5‐guided dosing strategies may improve rapid attainment of therapeutic tacrolimus concentrations.

To characterize the allelic and diplotype variability of TPMT and NUDT15 in pediatric patients with B-cell acute lymphoblastic leukemia from the central-southern region of Mexico. Samples from 275 pediatric B-cell acute lymphoblastic leukemia patients were analyzed. Next-generation sequencing was used for TPMT and NUDT15 genotyping. Alleles and diplotypes were assessed according to the Clinical Pharmacogenetics Implementation Consortium guidelines. Their geographic distribution was compared across Mexican states and global populations. In-silico analyses were conducted to assess the structural and functional impact of TPMT variants not associated with star alleles. The wild-type *1 allele, associated with normal enzymatic activity, was predominant in both genes: TPMT (94.15%) and NUDT15 (90.45%). TPMT showed greater allelic diversity compared with previous studies in Mexican populations. Alleles conferring absent or indeterminate enzymatic activity in TPMT were distributed across six diplotypes (11.62%), with *3A allele (4.73%) and *1/*3A diplotype (9.45%) being the most frequent. Additionally, two unclassified TPMT variants, p.G126A and p.D137Y, were identified. For NUDT15, three non-wild-type diplotypes were observed (19.09%), with the *2 allele (6.74%) and *1*/2 diplotype (13.48%) being the most prevalent. Approximately 28% of patients carried TPMT and/or NUDT15 variants associated with non-wild-type enzymatic activity, increasing the risk of mercaptopurine-induced myelotoxicity. Preemptive genotyping is essential to reduce toxicity, optimize treatment, and advance precision medicine in this population. Additionally, the two TPMT variants p.G126A and p.D137Y, currently not classified within Clinical Pharmacogenetics Implementation Consortium-defined star alleles, highlight the need for functional validation and potential clinical classification to improve pharmacogenetic interpretation in diverse populations.

Drug-gene interactions (DGIs) modify drug response and safety, yet their influence on diabetic microvascular complications remains unclear. This study aimed to elucidate the role of DGIs in these complications. Using UK Biobank (UKB) data, we identified medications frequently prescribed to individuals with diabetes and defined DGIs based on the Food and Drug Administration (FDA) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Associations between DGIs and diabetic microvascular complications were evaluated using Cox proportional hazards models, which are suited for longitudinal time-to-event data. Two complementary analyses were performed: (1) a therapeutic class-level analysis among medication users, and (2) a genotype-level analysis among individuals with non-normal metabolizer phenotypes who used the corresponding medications. We identified 368 medications preferentially used among participants with diabetes, primarily cardiovascular agents and detected 55 clinically relevant DGIs implicating 30 medications and 7 genes. Among users of antithrombotic agents, the presence of DGIs was associated with diabetic kidney disease (DKD) (hazard ratio [HR]: 1.44, 95% confidence interval [CI]: 1.12-1.86) and diabetic neuropathy (DN) (HR: 2.13, 95% CI: 1.39-3.28). Likewise, among individuals with non-normal metabolizer status for CYP2C19 or CYP2D6, DGIs conferred elevated risks for DKD and DN (HR range: 1.26-2.11). However, no significant association was found between DGI and DR. This study provides the first comprehensive assessment of DGIs and diabetic microvascular complications. DGIs involving antithrombotic agents and non-normal CYP2C19 or CYP2D6 metabolizers were significantly linked to higher risks of DKD and DN. These findings underscore the potential of pharmacogenomic-guided prescribing to enhance drug safety.

IntroductionPharmacogenomic (PGx) variants can influence drug efficacy and safety, yet their prevalence in Latin American populations with cancer is underexplored. Our aim is to characterize the frequency and phenotypic distribution of actionable pharmacogenes in Brazilian patients with metastatic prostate cancer (MPC) and Human Epidermal Growth Factor Receptor 2 (HER2)-positive breast cancer (BC).MethodsThis analysis included 452 patients (259 BC, 193 MPC) from a multicenter study across 19 Brazilian sites. Exome sequencing was performed, and PGx variants were analyzed using the Pharmacogenomics Clinical Annotation Tool (PharmCAT) following the Clinical Pharmacogenetics Implementation Consortium (CPIC®) guidelines. Genotypes, star alleles, and predicted phenotypes were reported for 15 clinically relevant pharmacogenes.ResultsActionable PGx phenotypes were detected in 99.33% of participants. The decreased-function ABCG2 rs2231142 T allele occurred at 8.96%, and the VKORC1 rs9923231 T allele at 32.63%. In SLCO1B1, normal function predominated (63.11%), with 21.11% exhibiting decreased function. Normal metabolizer phenotypes were most frequent in CYP2C19 (45.35%), CYP2C9 (70.51%), and CYP3A4 (94.62%), whereas CYP2B6 was dominated by intermediate metabolizers (43.02%) and CYP3A5 by poor/intermediate metabolizers (93.79%). Normal diplotypes predominated in thiopurine-related genes (NUDT15: 92.92%; TPMT: 88.72%), although nonfunctional alleles were observed. In UGT1A1, decreased-function alleles accounted for approximately 37% of participants. Clinically relevant DPYD and RYR1 variants were rare (<2.0%).ConclusionNearly all Brazilian patients with cancer carried at least one actionable PGx variant, highlighting the potential impact of PGx-guided therapy in oncology. These results underscore the value of integrating pharmacogenomic strategies into clinical practice in Brazil.

This study aimed to assess the prevalence of the use of medications with pharmacogenomic guidelines upon hospital admission in patients aged 65 and over and evaluate its association with adverse outcomes, including length of stay, unplanned admissions, and repeat hospital admissions. A retrospective cross-sectional study was conducted using hospital admissions data from 2018–2019 in one NHS hospital trust in England, focusing on patients aged 65 and over. The usage of medications with pharmacogenomic guidelines was examined, and comparisons were made between their prevalence in unplanned and planned admissions. Multivariable models assessed whether the use of medications with pharmacogenomic guidelines were associated with adverse outcomes, considering frailty status. Analysis of 59,973 admissions revealed 67 pharmacogenomics medicines as per the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, with 11 classified as high-risk among 1438 unique medicines identified from 560,179 recorded medications. Notably, unplanned admissions exhibited a higher prevalence of medications with pharmacogenomic guidelines (84% versus 64%, p < 0.001) compared to planned admissions. The models demonstrated the usage of these medications was associated with adverse outcomes (length of stay in hospital, unplanned admission and repeat hospital admission) with substantial evidence (Delta_AICc < 2) particularly in patients with high frailty status. This study highlights the association between medications with pharmacogenomic guidelines and adverse outcomes, particularly among patients with high frailty. The findings emphasise the importance of integrating pharmacogenomic-guided care into the management of older individuals with frailty to mitigate adverse outcomes and enhance medication safety.

The aim of this study was to determine the frequency of UGT1A1 and DPYD polymorphisms among Brazilian patients with gastrointestinal cancer. UGT1A1 and DPYD polymorphisms were selected due to their importance in the metabolism of fluoropyrimidines and irinotecan, and the existence of available clinical guidelines for dosing recommendations based on genetic testing. Polymorphism rs3918290, rs67376798, rs56038477, rs55886062, rs115232898, and rs887829 were investigated in 100 patients. Allelic discrimination was performed using the TaqMan Assay. Minor allele frequencies were calculated, and metabolic phenotypes were inferred based on the Clinical Pharmacogenetics Implementation Consortium and the Dutch Pharmacogenetics Working Group guidelines. For DPYD, rs56038477 (n=100) showed a minor allele frequency of 1.50% (CI 0.51-4.32), rs115232898 (n=49) had a minor allele frequency of 1.02% (CI 0.18-5.56), and rs3918290 (n=100) had a minor allele frequency of 0.50% (CI 0.09-2.78). No variants were observed in rs67376798 (n=100) or rs55886062 (n=44). A total of 4% of patients received a Clinical Pharmacogenetics Implementation Consortium DPYD activity score (AS) of less than 2.0, with 3% of 1.5 AS and 1% of 0.5 AS. For UGT1A1, rs887829 (n=100) revealed a minor allele frequency of 37.5% (CI 31.09-44.39) and 16% of patients with Dutch Pharmacogenetics Working Group poor metabolizer phenotype. The presence of DPYD and UGT1A1 variants is considerable among Brazilian gastrointestinal cancer patients, reinforcing the promising use of pre-therapeutic genetic tests for irinotecan and fluoropyrimidines to avoid severe toxicities related to treatment. Genetic panels for these variants must be continuously updated and adapted for population-specific characteristics.

ABSTRACTThe aim of this study was to describe self‐reported use of medications with established pharmacogenetic guidance in the Our Future Health (OFH) cohort. We examined four key pharmacogenes—CYP2C19, CYP2C9, CYP2D6, and SLCO1B1—and medications supported by strong evidence for clinical actionability according to the Clinical Pharmacogenetics Implementation Consortium (CPIC). Self‐reported medication use was summarized, concurrent use assessed, and findings stratified by age, sex, and ethnicity. We studied these data in 1.78 million OFH participants included in the June 2025 release. The cohort was 57.3% female, aged 18–95 years (mean 53.1 years), with 90.2% self‐identifying as “White.” Eighteen medication groups were explicitly listed in the baseline questionnaire, enabling identification of exposure at group level rather than for individual drugs. Medication groups with pharmacogenetic relevance included antidepressants (selective serotonin reuptake inhibitors and tricyclics), statins, proton pump inhibitors, ibuprofen, opioids, clopidogrel, and warfarin. Overall, 25.2% of participants (N = 449,641) reported use of at least one such group. These users tended to be older, more frequently female, and reported more comorbidities than non‐users. Concurrent exposure to two or more pharmacogenetically actionable medications metabolized by different genes was common, occurring in 37% of users. A substantial proportion of the OFH cohort therefore reported exposure to medications with pharmacogenetic guidance. Use was observed across all ages, with prevalence increasing with age. With continued expansion of the cohort and future linkage to prescribing records, OFH will provide a critical resource for population‐scale pharmacogenetic research.

Pharmacogenomics (PGx) offers a powerful strategy to improve medication safety and efficacy, yet its integration into community pharmacy practice remains limited. While an "attitude-knowledge gap" is known to exist globally, limited national data exist concerning PGx readiness among community pharmacists in Jordan. This study aimed to (i) quantify Clinical Pharmacogenetics Implementation Consortium (CPIC)-aligned PGx knowledge and characterize attitudes; (ii) assess implementation readiness across organizational, leadership, and structural dimensions; (iii) map perceived barriers; and (iv) identify independent predictors of knowledge, attitudes, and readiness. A national, cross-sectional survey was conducted using a proportionate stratified random sampling method. A content-validated and reliability-tested electronic questionnaire was distributed to community pharmacists across Jordan's three administrative regions. The instrument assessed demographics, CPIC-aligned knowledge, attitudes and perceived barriers on five-point Likert scales, and theory-informed implementation readiness. Data were analyzed using descriptive statistics, bivariate tests, and multiple linear regression. A total of 347 community pharmacists completed the survey. A vast majority (83.0%) reported no prior formal PGx training. Knowledge of practical PGx was low, with a mean score of 5.54 ± 2.12 out of 10. Attitudes were neutral (mean = 3.49 ± 0.26), while perceived barriers were rated as significant (mean severity = 3.45 ± 0.30), with privacy concerns being the highest-rated challenge (mean = 3.65 ± 0.78). Total implementation readiness was moderate (mean = 3.34 ± 0.25), with organizational readiness (mean = 3.39) rated higher than structural readiness (mean = 3.21) or leadership support (mean = 3.27). Bivariate analyses revealed few significant associations, and crucially, multiple linear regression models showed that no demographic or practice characteristics within the variables tested were significant independent predictors of knowledge or readiness. Jordanian community pharmacists demonstrated a significant gap between their positive attitudes towards PGx and the practical knowledge and systemic support required for clinical implementation. The findings revealed that the identified deficits in knowledge and readiness were widespread across all surveyed subgroups, not concentrated in specific demographic or professional subgroups. Translating the existing positive sentiment into routine clinical practice urgently requires a nationwide, standardized educational strategy coupled with the development of systemic enablers, including reimbursement pathways, integrated clinical workflows, and explicit leadership support.

Pharmacogenetics, the discipline concerned with how inherited genetic variation shapes individual responses to medications, holds particular promise for anesthesiology, where the margin between therapeutic efficacy and dangerous toxicity is often narrow and the consequences of getting the dose wrong can unfold within minutes rather than days. This research evaluated the clinical impact of preoperative pharmacogenetic testing on anesthetic drug dosing accuracy, adverse event rates, and recovery outcomes compared with standard empirical dosing at two Spanish university hospitals over a 29-month enrollment period. A prospective comparative cohort investigation enrolled 687 adult patients scheduled for elective major surgery under general anesthesia at Hospital Clínic de Barcelona and Hospital Universitario La Paz in Madrid between February 2021 and July 2023. Patients were assigned to either a pharmacogenetic-guided protocol (n=341) involving preoperative genotyping for CYP2D6, CYP2C19, UGT1A9, and OPRM1 polymorphisms with subsequent dose adjustment algorithms, or a standard empirical dosing protocol (n=346) reflecting routine institutional practice without genetic information. The pharmacogenetic panel was performed using the Agena Bioscience MassARRAY platform interrogating 24 genetic variants, with results available within 72 hours of blood draw. Four metabolizer phenotypes were classified for each enzyme system: poor, intermediate, normal, and ultra-rapid, following internationally standardized Clinical Pharmacogenetics Implementation Consortium guidelines. Dose modification algorithms adjusted opioid selection and dosing for CYP2D6 phenotype, propofol induction doses for UGT1A9 genotype, benzodiazepine dosing for CYP2C19 status, and baseline opioid requirements for OPRM1 A118G variant carriers. The primary endpoint was a composite adverse event score encompassing six perioperative complications: inadequate analgesia requiring rescue medication, excessive sedation defined as modified Observer&#39;s Assessment of Alertness scale below two for more than 30 minutes, postoperative nausea and vomiting within 24 hours, respiratory depression requiring pharmacological intervention, prolonged post-anesthesia care unit stay exceeding two hours beyond protocol discharge criteria, and the need for unplanned drug switching during the surgical case. Results demonstrated significant reductions in every component of the composite endpoint in the genotype-guided group. Inadequate analgesia dropped from 23.4% in standard care to 11.7% with pharmacogenetic guidance (p

The routine application of pharmacogenomic insights in clinical settings marks a transformative shift toward individualized patient care and precision medicine. Genotype-guided dosing has demonstrated clinical benefits in optimizing the safety and efficacy of several medications, including warfarin, clopidogrel, and thiopurines 1,2. Despite the availability of well-established guidelines and robust scientific backing from entities such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG), the integration of pharmacogenomics into routine clinical practice remains limited. One major barrier is the lack of awareness and training among healthcare professionals. Studies show that many clinicians lack confidence in interpreting and applying pharmacogenomic data 3, which limits its utility at the point of care.