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This article explores the high attrition rate of oncology drugs, which leads to increased costs for drug developers. Only 1 in 20 new chemical entities in oncology receive approval from regulatory authorities. The primary reasons for drug attrition have shifted from inappropriate pharmacokinetics to a lack of efficacy and safety. Strategies to reduce attrition include careful selection of animal models and biomarkers, as well as the development of biologics. Safety and toxicology are the main sources of drug failure. The article also includes a survey of experts in the field to gather insights on attrition of oncology drugs. The article discusses the trends and factors contributing to the discontinuation of oncology drugs during drug development. The total number of failed drugs has increased over time, with a 2-fold increase in 8 years. Half of the discontinued drugs occurred in Phase 1 trials, indicating that early-stage attrition minimizes financial loss. The reasons for drug attrition varied, with efficacy and strategic considerations being the major factors. Small molecules had a higher attrition rate compared to antibodies and other drug classes. Lung cancer was the most targeted indication for discontinued drugs. The article also highlights the complexities of cancer treatment and the importance of physicochemical properties, target validation, biomarkers, and adaptive clinical trials in drug development. It emphasizes the need for improved drug development strategies, such as drug repurposing and combination treatments. The article concludes by suggesting that adaptive clinical trial designs and effective communication with regulatory agencies are [Extracted from the article]

AbstractThis review explores genetic contributors to drug interactions, known as drug-gene and drug-drug-gene interactions (DGI and DDGI, respectively). This article is part of a mini-review issue led by the International Society for the Study of Xenobiotics (ISSX) New Investigators Group. Pharmacogenetics (PGx) is the study of the impact of genetic variation on pharmacokinetics (PK), pharmacodynamics (PD), and adverse drug reactions. Genetic variation in pharmacogenes, including drug metabolizing enzymes and drug transporters, is common and can increase the risk of adverse drug events or contribute to reduced efficacy. In this review, we summarize clinically actionable genetic variants, and touch on methodologies such as genotyping patient DNA to identify genetic variation in targeted genes, and deep mutational scanning as a high-throughput in vitro approach to study the impact of genetic variation on protein function and/or expression in vitro. We highlight the utility of physiologically based pharmacokinetic (PBPK) models to integrate genetic and chemical inhibitor and inducer data for more accurate human PK simulations. Additionally, we analyze the limitations of historical ethnic descriptors in pharmacogenomics research. Altogether, the work herein underscores the importance of identifying and understanding complex DGI and DDGIs with the intention to provide better treatment outcomes for patients. We also highlight current barriers to wide-scale implementation of PGx-guided dosing as standard or care in clinical settings. [ABSTRACT FROM AUTHOR]

Purpose Pharmacogenetic testing can identify patients who may benefit from personalized drug treatment. However, clinical uptake of pharmacogenetic testing has been limited. Clinical practice guidelines recommend biomarker tests that the guideline authors deem to have demonstrated clinical utility, meaning that testing improves treatment outcomes. The objective of this narrative review is to describe the current status of pharmacogenetic testing recommendations within clinical practice guidelines in the US. Summary Guidelines were reviewed for pharmacogenetic testing recommendations for 21 gene-drug pairs that have well-established drug response associations and all of which are categorized as clinically actionable by the Clinical Pharmacogenetics Implementation Consortium. The degree of consistency within and between organizations in pharmacogenetic testing recommendations was assessed. Relatively few clinical practice guidelines that provide a pharmacogenetic testing recommendation were identified. Testing recommendations for HLA-B*57:01 before initiation of abacavir and G6PD before initiation of rasburicase, both of which are included in drug labeling, were mostly consistent across guidelines. Gene-drug pairs with at least one clinical practice guideline recommending testing or stating that testing could be considered included CYP2C19 -clopidogrel, CYP2D6 -codeine, CYP2D6 -tramadol, CYP2B6 -efavirenz, TPMT -thiopurines, and NUDT15 -thiopurines. Testing recommendations for the same gene-drug pair were often inconsistent between organizations and sometimes inconsistent between different guidelines from the same organization. Conclusion A standardized approach to evaluating the evidence of clinical utility for pharmacogenetic testing may increase the inclusion and consistency of pharmacogenetic testing recommendations in clinical practice guidelines, which could benefit patients and society by increasing clinical use of pharmacogenetic testing. [ABSTRACT FROM AUTHOR]

Purpose We describe the implementation and ongoing maintenance of CYP2C19 and CYP2D6 focused pharmacogenetic (PGx) testing to guide antidepressant and antianxiety medication prescriptions in a large rural, nonprofit health system. Summary Depression and anxiety are common psychiatric conditions. Sanford Health implemented PGx testing for metabolism of cytochrome P450 (CYP) isozymes 2C19 and 2D6 in 2014 to inform prescribing for multiple medications, including antidepressant and antianxiety therapies. As guidelines, genotype to phenotype translation, panel offerings, and other resources are updated, we adapt our approach. We make educational and informational materials available to providers and patients. Pharmacogenomic clinical pharmacists review PGx results with discrete values and provide guidance documentation in the electronic medical record. A robust clinical decision support system is in place to provide interruptive alerts, noninterruptive alerts, and genomic indicators. A referral-based interdisciplinary clinic is also available to provide in-depth education to patients regarding PGx results and implications. Additionally, partnering with our health plan has expanded access to PGx testing for patients with anxiety or depression. Conclusion The implementation and maintenance of Sanford Health's PGx program to guide antidepressant and antianxiety medication use continues to evolve and requires a multipronged approach relying on both human and informatics-based resources. [ABSTRACT FROM AUTHOR]

Tacrolimus, a calcineurin inhibitor, is a highly effective immunosuppressant used in solid organ transplantation (SOT). However, it is characterized by a narrow therapeutic range and high inter‐patient variability in pharmacokinetics. Standard weight‐based dosing followed by empiric dose titration is suboptimal in controlling drug concentrations, increasing risk of rejection or toxicity, particularly in the initial months post transplantation. This review explores the potential of combined pre‐transplant genotyping and pharmacokinetic (PK) modelling to improve tacrolimus dosing in paediatric SOT recipients. A systematic search of Medline, Embase and Cochrane databases identified studies published between March 2013 and March 2023 that investigated genotype‐ and PK model‐informed tacrolimus dosing in children post‐SOT. The Newcastle‐Ottawa Scale assessed study quality. Seven studies encompassing paediatric kidney, heart, liver and lung transplants reported using genotype and model‐informed dosing. A combination of clinical and genetic factors significantly impacts tacrolimus clearance and thus initial dose recommendation. Body size, transplant organ and co‐medications were consistently important, while either time post‐transplant or haematocrit emerged in some studies. Several models were identified, however, with limitations evident in some and with absence of evidence for their effectiveness in optimizing initial and subsequent dosing. This review highlights the development of PK models in paediatric SOT that integrate genotype and clinical covariates to personalize early tacrolimus dosing. While promising, prospective studies are needed to validate and confirm their effectiveness in improving time to therapeutic concentrations and reducing under‐ or overexposure. This approach has the potential to optimize tacrolimus therapy in paediatric SOT, thereby improving outcomes. [ABSTRACT FROM AUTHOR]

Pharmacotherapy is one of the primary treatment modalities for depression. However, there is considerable variability in the individual response to antidepressant medications. Personalized medicine guided by pharmacogenomic testing may hold promise in addressing this issue. In this study, 665 depressive patients were randomly enrolled into two groups: the pharmacogenomic testing group (n = 333) and the control group (n = 332). In the testing group, participants underwent pharmacogenomic testing, and clinicians customized the treatment plan with the result, while the control group relied solely on clinicians' experience. The primary outcomes were the proportion of remission and response, assessed with Hamilton Depression Rating Scale (HDRS). The secondary outcomes included changes in HDRS scores over time and frequency of adverse drug reactions by the participants. At week 8, the pharmacogenomic testing group showed significantly higher remission rates (24.0 % v.s. 15.1 %; RR = 1.117; P = 0.007) and response rates (39.3 % v.s. 25.7 %; RR = 1.225; P < 0.001) compared to the control group. By week 12, the pharmacogenomic testing group continued to demonstrate significant advantages in remission (31.0 % v.s. 20.0 %; RR = 1.159; P = 0.003) and response (48.7 % v.s. 37.3 %; RR = 1.224; P = 0.006). Additionally, adverse drug reactions were less frequent in the pharmacogenomic testing group. This study is not blind to clinicians and it's a single-center study. Conclusions: Pharmacogenomic testing-guided drug therapy can provide greater assistance in the treatment of depression. • Pharmacogenomic testing is available to guide the treatment of depression. • Pharmacogenomic guided medication enhances remission and response rates. • Pharmacogenomic guided medication reduces the occurrence of adverse effects. [ABSTRACT FROM AUTHOR]

Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors. [ABSTRACT FROM AUTHOR]

AbstractThe field of pharmacogenetics, the investigation of the influence of one or more sequence variants on drug response phenotypes, is a special case of pharmacogenomics, a discipline that takes a genome-wide approach. Massively parallel, next generation sequencing (NGS), has allowed pharmacogenetics to be subsumed by pharmacogenomics with respect to the identification of variants associated with responders and non-responders, optimal drug response, and adverse drug reactions. A plethora of rare and common naturally-occurring GPCR variants must be considered in the context of signals from across the genome. Many fundamentals of pharmacogenetics were established for G protein-coupled receptor (GPCR) genes because they are primary targets for a large number of therapeutic drugs. Functional studies, demonstrating likely-pathogenic and pathogenic GPCR variants, have been integral to establishing models used for in silico analysis. Variants in GPCR genes include both coding and non-coding single nucleotide variants and insertion or deletions (indels) that affect cell surface expression (trafficking, dimerization, and desensitization/downregulation), ligand binding and G protein coupling, and variants that result in alternate splicing encoding isoforms/variable expression. As the breadth of data on the GPCR genome increases, we may expect an increase in the use of drug labels that note variants that significantly impact the clinical use of GPCR-targeting agents. We discuss the implications of GPCR pharmacogenomic data derived from the genomes available from individuals who have been well-phenotyped for receptor structure and function and receptor-ligand interactions, and the potential benefits to patients of optimized drug selection. Examples discussed include the renin-angiotensin system in SARS-CoV-2 (COVID-19) infection, the probable role of chemokine receptors in the cytokine storm, and potential protease activating receptor (PAR) interventions. Resources dedicated to GPCRs, including publicly available computational tools, are also discussed. [ABSTRACT FROM AUTHOR]

Background: Pharmacogenomics (PGx) is a well-established concept of how genes impact medication response, with many studies demonstrating reductions in medication side effects, improved efficacy and cost effectiveness. Despite these benefits, implementation of PGx in daily practice remains limited. Studies on the implementation of PGx in clinical practice have previously found that inadequate knowledge is one of themain barriers. Details regarding specificallywhich educational needs exist among family medicine clinicians requires further study. Objective: The aim of this study was to identify both the perceived role that pharmacogenomics (PGx) could play in primary care practice, the knowledge gaps that family medicine clinicians experience, and the skills they require to use PGx in their daily practice. Methods: To achieve this aim, the attitudes, knowledge, barriers, skills needed, and preferred educational program were explored in a family medicine clinician focus group study via a semi-structured interview and knowledge quiz. Second, multidisciplinary focus groups provided information on the level of knowledge and necessary skills to use PGx in patient care. After gathering key recorded information from both focus groups, the perceived role pharmacogenomics could possibly play in primary care, the predominant knowledge gaps, and the most appropriate educational program was determined by qualitative analysis. Results: Four themes emerged regarding the PGx educational needs and the role of PGx in family medicine: 1) need for PGx competences, 2) insight into the roles and responsibilities of PGx services, 3) optimization of PGx workflow through artificial intelligence integrated in the electronic health record, and 4) the ethical dilemmas and psychological effects related to PGx. These themes reflect a shift in the role of PGx in family medicine with implications for education. Conclusion: The results obtained from this study will help improve the implementation of PGx in daily practice, and consequently, may result in increased utilization of PGx, thereby resulting in improved medication efficacy and reduced side effects. [ABSTRACT FROM AUTHOR]

Pharmacogenomics (PGx), examining the effect of genetic variation on interpatient variation in drug disposition and response, has been widely studied for several decades. However, as cost, as well as turnaround time associated with PGx testing, has significantly improved, the use of PGx in the clinical setting has been gaining momentum. Nevertheless, challenges have emerged in the broader clinical implementation of PGx. In this review, we will outline current models of PGx delivery and methodologies of evaluation, and discuss clinically relevant PGx tests and associated medications. Additionally, we will describe our approach for the broad implementation of pre‐emptive DPYD genotyping in patients taking fluoropyrimidines in Ontario, Canada, as an example of clinically actionable PGx testing with sufficient clinical evidence of patient benefit that can become a new standard of patient care. We will highlight challenges associated with PGx testing, including a lack of diversity in PGx studies as well as general limitations that impact the broad adoption of PGx testing. Lastly, we examine the future of PGx, discussing new clinical targets, methodologies and analysis approaches. [ABSTRACT FROM AUTHOR]

Tacrolimus metabolism is heavily influenced by the CYP3A5 genotype, which varies widely among African Americans (AA). We aimed to assess the performance of a published genotype‐informed tacrolimus dosing model in an independent set of adult AA kidney transplant (KTx) recipients. CYP3A5 genotypes were obtained for all AA KTx recipients (n = 232) from 2010 to 2019 who met inclusion criteria at a single transplant center in Philadelphia, Pennsylvania, USA. Medical record data were used to calculate predicted tacrolimus clearance using the published AA KTx dosing equation and two modified iterations. Observed and model‐predicted trough levels were compared at 3 days, 3 months, and 6 months post‐transplant. The mean prediction error at day 3 post‐transplant was 3.05 ng/mL, indicating that the model tended to overpredict the tacrolimus trough. This bias improved over time to 1.36 and 0.78 ng/mL at 3 and 6 months post‐transplant, respectively. Mean absolute prediction error—a marker of model precision—improved with time to 2.33 ng/mL at 6 months. Limiting genotype data in the model decreased bias and improved precision. The bias and precision of the published model improved over time and were comparable to studies in previous cohorts. The overprediction observed by the published model may represent overfitting to the initial cohort, possibly limiting generalizability. [ABSTRACT FROM AUTHOR]

This article presents a study on the distribution of cytochrome P450 (CYP450) alleles in the Danish population. CYP450 enzymes are important for drug metabolism, and genetic variations in the genes encoding these enzymes can impact drug response. The study compared genotype data from different genotyping platforms and found that the CYP2C19*17 and CYP2C9*2 alleles were more common than the CYP2C19*2 and CYP2C9*3 alleles. The results provide valuable insights into the genetic variability of these enzymes in the Danish population and suggest that the Illumina GSA platform could be useful for identifying drug-gene interactions. [Extracted from the article]

Aim: To explore the views of neonatal intensive care nursing staff on the deliverability of a novel genetic point‐of‐care test detecting a genetic variant associated with antibiotic‐induced ototoxicity. Design: An interpretive, descriptive, qualitative interview study. Methods: Data were collected using semi‐structured interviews undertaken between January and November 2020. Participants were neonatal intensive care nursing staff taking part in the Pharmacogenetics to Avoid Loss of Hearing trial. Results: Thematic analysis resulted in four themes: perceived clinical utility; the golden hour; point‐of‐care device; training and support. Recommendations were made to streamline the protocol and ongoing training and support were considered key to incorporating the test into routine care. Conclusion: Exploring the views of nurses involved in the delivery of the point‐of‐care test was essential in its implementation. By the study endpoint, all participants could see the value of routine clinical introduction of the point‐of care test. Implications for the Profession and/or Patient Care: Nurses are in a key position to support the delivery of point‐of‐care genetic testing into mainstream settings. This study has implications for the successful integration of other genetic point‐of‐care tests in acute healthcare settings. Impact: The study will help to tailor the training and support required for routine deployment of the genetic point‐of‐care test. The study has relevance for nurses involved in the development and delivery of genetic point‐of‐care tests in other acute hospital settings. Reporting Method: This qualitative study adheres to the Standards for Reporting Qualitative Research EQUATOR guidelines and utilizes COREQ and SRQR checklists. Patient or Public Contribution: All staff working on the participating neonatal intensive care units were trained to use the genetic point‐of‐care test. All inpatients on the participating units were eligible to have testing via the point‐of‐care test. The Pharmacogenetics to Avoid Loss of Hearing Patient and Public Involvement and Engagement group provided valuable feedback. Trial and Protocol Registration: Registered within the University of Manchester. Ethics approval reference numbers: IRAS: 253102 REC reference: 19/NW/0400. Also registered with the ISRCTN ref: ISRCTN13704894. [ABSTRACT FROM AUTHOR]

Pharmacogenomics (PGx) results can potentially guide the prescribing of dozens of medications; however, use of such results is often limited by the prescriber's awareness of results and knowledge of drug–gene interactions. Integration of PGx results with corresponding clinical decision support (CDS) in the electronic health record (EHR) is critical to facilitate genotype‐guided medication prescribing among all clinicians in an integrated health system. We describe our experience with developing an infrastructure to house PGx results and ensure actionable findings can be used at the point of care in real time using CDS. Upon transitioning to a new EHR, PGx‐related CDS alerts for more than 50 medications were developed using a systematic and multidisciplinary process where clinical pharmacist input was key. Multiple strategies were required to enable the storage of PGx results as discrete data from any laboratory source to drive CDS. EHR features were leveraged to link results from external laboratories to CDS and a homegrown translational software platform was developed to integrate results from the in‐house genomics laboratory directly into the EHR. These processes enabled PGx result integration for 2342 patients. As an example, among 356 patients who were genotyped for CYP2C19 to guide voriconazole dosing as part of a standard protocol in bone marrow transplant, 114 (32%) had CDS alerts for medications other than voriconazole presented to a clinician. For 50 of these patients, alerts were presented to a clinician of a different specialty who likely was not aware the patient had PGx results. Clinical pharmacists at institutions performing PGx testing are encouraged to champion the integration of PGx results and CDS in the EHR to maximize clinician awareness and evidence‐based use of PGx results. [ABSTRACT FROM AUTHOR]

Model-informed drug development (MIDD) and the MIDD Paired Meeting Pilot Program have emerged as strategic approaches to using computational models and simulations to inform drug development and regulatory decision-making. MIDD began with the FDA Modernization Act in 1997, which allowed for greater flexibility in drug approval and the incorporation of computational models. The FDA has since issued guidance and launched initiatives to promote model-based drug development and facilitate interactions between regulatory scientists and pharmaceutical sponsors. MIDD has been recognized by the industry and the FDA, and efforts are being made to expand and enhance its use in drug development. The FDA is also committed to international collaboration through its participation in the International Council for Harmonization. Overall, MIDD aims to improve the efficiency and effectiveness of drug development and regulatory decision-making, benefiting both the industry and patients. [Extracted from the article]

The Department of Veterans Affairs (VA) utilizes a pharmacogenomic (PGx) program that analyzes specific "pharmacogenes." This study evaluates the effect that pharmacogenes may have on prevalence of polypharmacy. This retrospective cohort study included patients with VA prescriptions who underwent PGx testing. We quantified prescriptions active or recently expired at the time of PGx testing. We constructed two co‐primary polypharmacy (≥10 medications) end points: (i) based on all medications and (ii) requiring that at least one medication was affected by a pharmacogene of interest. Pharmacogenes and actionable phenotypes of interest included poor and ultrarapid metabolizers for CYP2D6, CYP2C9, and CYP2C19 and intermediate and normal metabolizers for CYP3A5. Patients were classified as having 0, 1, and 2+ total phenotypes across all genes. Of the 15,144 patients screened, 13,116 met eligibility criteria. Across phenotype cohorts, there was no significant association with polypharmacy using all medications, number of total medications, or number of medications affected by phenotypes. However, there was a significant difference in patients with polypharmacy prescribed ≥1 medication impacted by PGx across phenotype groups: 2,514/4,949 (51%), 1,349/2,595 (52%), 204/350 (58%) (P = 0.03, OR 1.31, 95% CI 1.02–1.67). The median number of medications affected by PGx phenotypes with ≥1 PGx‐impacted medication across phenotype groups was a median of 0 (IQR 0, 0), 0 (IQR 0, 0), and 1 (IQR 0, 1) (P < 0.001). In patients prescribed ≥1 medication impacted by PGx, those with more actionable pharmacogenomic phenotypes were more likely to meet polypharmacy criteria. [ABSTRACT FROM AUTHOR]

Aim: To determine the efficacy and safety of pharmacogenomics (PGx)-guided antidepressant prescribing in patients with depression through an umbrella review and updated meta-analysis. Methods: A comprehensive systematic search was conducted on PsycINFO, PubMed, Embase and the Cochrane databases. The pooled effect sizes of randomized controlled trials (RCTs) were expressed as mean differences for continuous data and risk ratios for noncontinuous data. Results: Patients who received PGx-guided medications were 41% to 78% more likely to achieve remission and 20% to 49% more likely to respond to antidepressants than patients receiving treatment-as-usual (TAU). Conclusion: PGx-guided antidepressant prescribing improves the treatment of depression. However, the significance and magnitude of the benefit varies widely between studies and different PGx testing panels. [ABSTRACT FROM AUTHOR]

Background: Oral squamous cell carcinoma (OSCC) causes significant mortality and morbidity worldwide. Surgical resection with adjuvant radiotherapy remains the standard treatment for locally advanced resectable OSCC. Results from landmark trials have established postoperative concurrent cisplatin-radiotherapy (Cis-RT) as the standard treatment for OSCC patients with high-risk pathologic features. However, cisplatin-related toxicity limits usage in clinical practice. Given the need for effective but less toxic alternatives, we previously conducted a single-arm trial showing favorable safety profiles and promising efficacy of concurrent docetaxel-radiotherapy (Doc-RT). Methods: In this randomized phase 2 trial, we aimed to compare Doc-RT with the standard Cis-RT in postoperative OSCC patients. Eligible patients had AJCC stage III–IV resectable OSCC with high-risk pathologic features. Two hundred twenty-four patients were enrolled and randomly assigned to receive concurrent Doc-RT or Cis-RT. The primary endpoint was 2-year disease-free survival (DFS). Secondary endpoints included overall survival (OS), locoregional-free survival (LRFS), distant metastasis-free survival (DMFS), and adverse events (AEs). Integrin β1 (ITGB1) expression was analyzed as a biomarker for efficacy. Results: After a median 28.8-month follow-up, 2-year DFS rates were 63.7% for Doc-RT arm and 56.1% for Cis-RT arm (p = 0.55). Meanwhile, Doc-RT demonstrated comparable efficacy to Cis-RT in OS, LRFS, and DMFS. Doc-RT resulted in fewer grade 3 or 4 hematological AEs. Low ITGB1 was associated with improved Doc-RT efficacy versus Cis-RT. Conclusions: This randomized trial directly compared Doc-RT with Cis-RT for high-risk postoperative OSCC patients, with comparable efficacy and less toxicity. ITGB1 merits further validation as a predictive biomarker to identify OSCC patients most likely to benefit from Doc-RT. Findings indicate docetaxel may be considered as a concurrent chemoradiation option in this setting. Trial registration: www.ClinicalTrials.gov. NCT02923258 (date of registration: October 4, 2016) [ABSTRACT FROM AUTHOR]

With the continuous development of genetics in healthcare, there has been a significant contribution to the development of precision medicine, which is ultimately aimed at improving the care of patients. Generally, drug treatments used in Oncology are characterized by a narrow therapeutic range and by their potential toxicity. Knowledge of pharmacogenomics and pharmacogenetics can be very useful in the area of Oncology, as they constitute additional tools that can help to individualize patients' treatment. This work includes a description of some genes that have been revealed to be useful in the field of Oncology, as they play a role in drug prescription and in the prediction of treatment response. [ABSTRACT FROM AUTHOR]

Cancer chemotherapy is advancing as we understand how cellular mechanisms and drugs interact, particularly involving the enzyme MGMT, which repairs DNA damage that can cause cancer. This review examines MGMT's role in DNA repair, its impact on chemotherapy, and its complex interaction with radiation therapy. MGMT activity can both protect against mutations and cause drug resistance. Modulating MGMT could improve treatment efficacy and tailoring therapy to MGMT status may enhance patient outcomes. Understanding MGMT is crucial for developing precise cancer treatments and advancing patient care. [ABSTRACT FROM AUTHOR]

Cytochrome P450 2D6 (CYP2D6) plays a crucial role in metabolizing approximately 20% of medications prescribed clinically. This enzyme is encoded by the CYP2D6 gene, known for its extensive polymorphism with over 170 catalogued haplotypes or star alleles, which can have a profound impact on drug efficacy and safety. Despite its importance, a gap exists in the global genomic databases, which are predominantly representative of European ancestries, thereby limiting comprehensive knowledge of CYP2D6 variation in ethnically diverse populations. In an effort to bridge this knowledge gap, we focused on elucidating the CYP2D6 variation landscape within a multi-ethnic Asian cohort, encompassing individuals of Chinese, Malay, and Indian descent. Our study comprised data analysis of 1850 whole genomes from the SG10K_Health dataset using an in-house consensus algorithm, which integrates the capabilities of Cyrius, Aldy, and StellarPGx. This analysis unveiled distinct population-specific star-allele distribution trends, highlighting the unique genetic makeup of the Singaporean population. Significantly, 46% of our cohort harbored actionable CYP2D6 variants—those with direct implications for drug dosing and treatment strategies. Furthermore, we identified 14 potential novel CYP2D6 star-alleles, of which 7 were observed in multiple individuals, suggesting their broader relevance. Overall, our study contributes novel data on CYP2D6 genetic variations specific to the Southeast Asian context. The findings are instrumental for the advancement of pharmacogenomics and personalized medicine, not only in Southeast Asia but also in other regions with comparable genetic diversity. [ABSTRACT FROM AUTHOR]

The application of network pharmacology (NP) has advanced our understanding of the complex molecular mechanisms underlying diseases, including neck, head, and oral cancers, as well as thyroid carcinoma. This review aimed to explore the therapeutic potential of natural network pharmacology using compounds and traditional Chinese medicines for combating these malignancies. NP serves as a pivotal tool that provides a comprehensive view of the interactions among compounds, genes, and diseases, thereby contributing to the advancement of disease treatment and management. In parallel, this review discusses the significance of publicly accessible databases in the identification of oral, head, and neck cancer-specific genes. These databases, including those for head and neck oral cancer, head and neck cancer, oral cancer, and genomic variants of oral cancer, offer valuable insights into the genes, miRNAs, drugs, and genetic variations associated with these cancers. They serve as indispensable resources for researchers, clinicians, and drug developers, contributing to the pursuit of precision medicine and improved treatment of these challenging malignancies. In summary, advancements in NP could improve the globalization and modernization of traditional medicines and prognostic targets as well as aid in the development of innovative drugs. Furthermore, this review will be an eye-opener for researchers working on drug development from traditional medicines by applying NP approaches. [ABSTRACT FROM AUTHOR]

Background: Pharmacogenomics (PGx) constitutes an important part of personalized medicine and has several clinical applications. PGx role in clinical practice is known, however, it has not been widely adopted yet. In this study, we aim to investigate the perspectives of Greek physicians regarding the implementation of PGx testing in clinical practice and the key issues associated with it. Methods: Fourteen interviews were conducted with physicians of various specialties for which PGx applications are available. A semi-structured interview guide was utilized based on the Consolidated Framework for Implementation Research (CFIR) context and the Diffusion of Innovation model. Transcripts were coded independently and compared by two members of the research team. Descriptive statistics were generated using Microsoft Excel. Results: Six main themes emerged: awareness and use of PGx testing; source of information; key stakeholders of the PGx supply chain, their interactions and change agents; clinical benefit and significance of PGx testing; barriers and lack of reimbursement; and recommendations to boost the PGx adoption rate. Most respondents were aware of PGx applications, but only three had already recommended PGx testing. Peer-reviewed journals along with clinical guidelines were regarded as the most used source of information while stakeholders of the PGx supply chain were discussed. PGx was considered that promote patient-centered care, enhance medication clinical effectiveness, decrease the risk of side effects, and reduce healthcare costs. Lack of reimbursement, scarcity of resources, and high PGx cost were the foremost barriers affecting PGx adoption. Conclusions: It was concluded that if case PGx testing is reimbursed and physicians' training is reinforced, PGx implementation will be boosted and improved shortly. [ABSTRACT FROM AUTHOR]

Depression continues to be a significant and growing public health concern. In clinical practice, it involves a clinical diagnosis. There is currently no defined or agreed upon biomarker/s for depression that can be readily tested. A biomarker is defined as a biological indicator of normal physiological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention that can be objectively measured and evaluated. Thus, as there is no such marker for depression, there is no objective measure of depression in clinical practice. The discovery of such a biomarker/s would greatly assist clinical practice and potentially lead to an earlier diagnosis of depression and therefore treatment. A biomarker for depression may also assist in determining response to medication. This is of particular importance as not all patients prescribed with medication will respond, which is referred to as medication resistance. The advent of pharmacogenomics in recent years holds promise to target treatment in depression, particularly in cases of medication resistance. The role of pharmacogenomics in routine depression management within clinical practice remains to be fully established. Equally so, the use of pharmaceutical grade nutrients known as nutraceuticals in the treatment of depression in the clinical practice setting is largely unknown, albeit frequently self-prescribed by patients. Whether nutraceuticals have a role in not only depression treatment but also in potentially modifying the biomarkers of depression has yet to be proven. The aim of this review is to highlight the potential biomarkers for the diagnosis, prediction, and medication response of depression. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host–microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives. [ABSTRACT FROM AUTHOR]

Pre-treatment genotyping of four well-characterized toxicity risk-variants in the dihydropyrimidine dehydrogenase gene (DPYD) has been widely implemented in Europe to prevent serious adverse effects in cancer patients treated with fluoropyrimidines. Current genotyping practices are largely limited to selected commonly studied variants and are unable to determine phasing when more than one variant allele is detected. Recent evidence indicates that common DPYD variants modulate the functional impact of deleterious variants in a phase-dependent manner, where a cis- or a trans-configuration translates into different toxicity risks and dosing recommendations. DPYD is a large gene with 23 exons spanning nearly a mega-base of DNA, making it a challenging candidate for full-gene sequencing in the diagnostic setting. Herein, we present a time- and cost-efficient long-read sequencing approach for capturing the complete coding region of DPYD. We demonstrate that this method can reliably produce phased genotypes, overcoming a major limitation with current methods. This method was validated using 21 subjects, including two cancer patients, each of whom carried multiple DPYD variants. Genotype assignments showed complete concordance with conventional approaches. Furthermore, we demonstrate that the method is robust to technical challenges inherent in long-range sequencing of PCR products, including reference alignment bias and PCR chimerism. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions Tacrolimus, metabolized by CYP3A4 and CYP3A5 enzymes, is susceptible to drug–drug interactions (DDI). Steroids induce CYP3A genes to increase tacrolimus clearance, but the effect is variable. We hypothesized that the extent of the steroid–tacrolimus DDI differs by CYP3A4/5 genotypes.Kidney transplant recipients (n = 2462) were classified by the number of loss of function alleles (LOF) (CYP3A5*3, *6 and *7 and CYP3A4*22) and steroid use at each tacrolimus trough in the first 6 months post‐transplant. A population pharmacokinetic analysis was performed by nonlinear mixed‐effect modelling (NONMEM) and stepwise covariate modelling to define significant covariates affecting tacrolimus clearance. A stochastic simulation was performed and translated into a Shiny application with the mrgsolve and Shiny packages in R.Steroids were associated with modestly higher (3%–11.8%) tacrolimus clearance. Patients with 0‐LOF alleles receiving steroids showed the greatest increase (11.8%) in clearance compared to no steroids, whereas those with 2‐LOFs had a negligible increase (2.6%) in the presence of steroids. Steroid use increased tacrolimus clearance by 5% and 10.3% in patients with 1‐LOF and 3/4‐LOFs, respectively.Steroids increase the clearance of tacrolimus but vary slightly by CYP3A genotype. This is important in individuals of African ancestry who are more likely to carry no LOF alleles, may more commonly receive steroid treatment, and will need higher tacrolimus doses. [ABSTRACT FROM AUTHOR]

Clopidogrel is widely used worldwide as an antiplatelet therapy in patients with acute coronary disease. Genetic factors influence interindividual variability in response. Some studies have explored the polygenic contributions in the drug response, generating pharmacogenomic risk scores (PgxPRS). Importantly, these factors are less explored in underrepresented populations, such as Latin-American countries. Identifying patients at risk of high-on-treatment platelet reactivity (HTPR) is highly valuable in translational medicine. In this study we used a custom next-generation sequencing (NGS) panel composed of 91 single nucleotide polymorphisms (SNPs) and 28 genes related to clopidogrel metabolism, to analyze 70 patients with platelet reactivity values, assessed through closure time (CT). Our results demonstrated the association of SNPs with HTPR and non-HTPR, revealing the strongest associations with rs2286823 (OR: 5,0; 95% CI: 1,02–24,48; p: 0,03), rs2032582 (OR: 4,41; 95% CI: 1,20–16,12; p: 0,019), and rs1045642 (OR: 3,38; 95% CI: 0,96–11,9; p: 0,05). Bivariate regression analysis demonstrated the significant association of several SNPs with the CT value, a "surrogate" biomarker of clopidogrel response. Exploratory results from the LASSO regression model showed a high discriminatory capacity between HTPR and non-HTPR patients (AUC: 0,955), and the generated PgxPRS demonstrated a significant negative association between the risk score, CT value, and the condition of HTPR and non-HTPR. To our knowledge, our study addresses for the first time the analysis of the polygenic contribution in platelet reactivity using NGS and establishes PgxPRS derived from the LASSO model. Our results demonstrate the polygenic implication of clopidogrel response and offer insights applicable to the translational medicine of antiplatelet therapy in an understudied population. [ABSTRACT FROM AUTHOR]

Pharmacogenetics investigates sequence of genes that affect drug response, enabling personalized medication. This approach reduces drug-induced adverse reactions and improves clinical effectiveness, making it a crucial consideration for personalized medical care. Numerous guidelines, drawn by global consortia and scientific organizations, codify genotype-driven administration for over 120 active substances. As the scientific community acknowledges the benefits of genotype-tailored therapy over traditionally agnostic drug administration, the push for its implementation into Italian healthcare system is gaining momentum. This evolution is influenced by several factors, including the improved access to patient genotypes, the sequencing costs decrease, the growing of large-scale genetic studies, the rising popularity of direct-to-consumer pharmacogenetic tests, and the continuous improvement of pharmacogenetic guidelines. Since EMA (European Medicines Agency) and AIFA (Italian Medicines Agency) provide genotype information on drug leaflet without clear and explicit clinical indications for gene testing, the regulation of pharmacogenetic testing is a pressing matter in Italy. In this manuscript, we have reviewed how to overcome the obstacles in implementing pharmacogenetic testing in the clinical practice of the Italian healthcare system. Our particular emphasis has been on germline testing, given the absence of well-defined national directives in contrast to somatic pharmacogenetics. [ABSTRACT FROM AUTHOR]

Background: A large number of challenging medically relevant genes (CMRGs) are situated in complex or highly repetitive regions of the human genome, hindering comprehensive characterization of genetic variants using next-generation sequencing technologies. In this study, we employed long-read sequencing technology, extensively utilized in studying complex genomic regions, to characterize genetic alterations, including short variants (single nucleotide variants and short insertions and deletions) and copy number variations, in 370 CMRGs across 41 individuals from 19 global populations. Results: Our analysis revealed high levels of genetic variants in CMRGs, with 68.73% exhibiting copy number variations and 65.20% containing short variants that may disrupt protein function across individuals. Such variants can influence pharmacogenomics, genetic disease susceptibility, and other clinical outcomes. We observed significant differences in CMRG variation across populations, with individuals of African ancestry harboring the highest number of copy number variants and short variants compared to samples from other continents. Notably, 15.79% to 33.96% of short variants were exclusively detectable through long-read sequencing. While the T2T-CHM13 reference genome significantly improved the assembly of CMRG regions, thereby facilitating variant detection in these regions, some regions still lacked resolution. Conclusion: Our results provide an important reference for future clinical and pharmacogenetic studies, highlighting the need for a comprehensive representation of global genetic diversity in the reference genome and improved variant calling techniques to fully resolve medically relevant genes. [ABSTRACT FROM AUTHOR]

Background Aims Results Discussion and Conclusion Despite common global usage, fluoropyrimidine (FP; 5‐flurouracil and capecitabine)‐related chemotherapy toxicity is poorly reported in the literature, with serious toxicity ranging from 10% to 40% and early toxicity (within 60 days of exposure) quoted at 14%. Data reflecting the incidence of Grades 3–5 FP‐related toxicity in Australian cancer patients is scant, despite the significant impact of toxicity on patients (hospitalisations, intensive care unit (ICU) admissions and even death).This retrospective audit evaluated Grades 3–5 toxicities in a contemporaneous cohort of 500 patients receiving FP chemotherapies within the Hunter‐New England Local Health District from June 2020 to June 2022. Data were extracted from public hospital records and oncology‐specific e‐records to determine rates of toxicity and associated hospitalisations, intensive care admissions and deaths that occurred within 60 days of first exposure to FP chemotherapy‐containing regimens.One hundred and fifty incidents of Grades 3–4 toxicity in the first 60 days led to 87 patients presenting to hospital (87/500, 17.4%). The most common serious toxicities were diarrhoea (39.3%), nausea and vomiting (22.7%) and febrile neutropaenia (10%). Four patients were admitted to the ICU, and four patients died of toxicity. Within the first 60 days, 22.2% of patients required treatment delays, 21.4% required dose reductions, and 7.8% of patients ceased treatment because of toxicities.Our experience reflects international reports and is likely generalisable to the Australian population. These data are a basis to understand the potential benefits of precision medicine strategies such as pharmacogenomic screening to improve patient tolerability and the cost‐effectiveness of FP chemotherapy prescribing. [ABSTRACT FROM AUTHOR]

Background: Endocrine therapy is the most important treatment modality of breast cancer patients whose tumors express the estrogen receptor α (ERα). The androgen receptor (AR) is also expressed in the vast majority (80–90%) of ERα-positive tumors. AR-targeting drugs are not used in clinical practice, but have been evaluated in multiple trials and preclinical studies. Methods: We performed a genome-wide study to identify hormone/drug-induced single nucleotide polymorphism (SNP) genotype - dependent gene-expression, known as PGx-eQTL, mediated by either an AR agonist (dihydrotestosterone) or a partial antagonist (enzalutamide), utilizing a previously well characterized lymphoblastic cell line panel. The association of the identified SNPs-gene pairs with breast cancer phenotypes were then examined using three genome-wide association (GWAS) studies that we have published and other studies from the GWAS catalog. Results: We identified 13 DHT-mediated PGx-eQTL loci and 23 Enz-mediated PGx-eQTL loci that were associated with breast cancer outcomes post ER antagonist or aromatase inhibitors (AI) treatment, or with pharmacodynamic (PD) effects of AIs. An additional 30 loci were found to be associated with cancer risk and sex-hormone binding globulin levels. The top loci involved the genes IDH2 and TMEM9, the expression of which were suppressed by DHT in a PGx-eQTL SNP genotype-dependent manner. Both of these genes were overexpressed in breast cancer and were associated with a poorer prognosis. Therefore, suppression of these genes by AR agonists may benefit patients with minor allele genotypes for these SNPs. Conclusions: We identified AR-related PGx-eQTL SNP-gene pairs that were associated with risks, outcomes and PD effects of endocrine therapy that may provide potential biomarkers for individualized treatment of breast cancer. [ABSTRACT FROM AUTHOR]

Background: Guided by Clinical Pharmacogenomic Implementation Consortium(CPIC) guidelines for >140medications, pharmacogenomic tests inform medication selection and dosing to optimize efficacy while minimizing toxicities. Purpose: This study assessed pharmacogenomic self-reported curricular content, knowledge, skills, attitudes, and usage in advanced practice registered nurses (APRNs) with prescriptive privileges. Methodology: An online survey was administered assessing pharmacogenomic curricular content, knowledge, skills, attitudes, and usage. Results: Data from 266 APRNs were analyzed. Most graduated with their highest nursing degree; 10 years ago and reported pharmacogenomic curricular content (n = 124, 48%). Pharmacogenomic curricular content was associated with pharmacogenomic familiarity (p = .045) but not with knowledge confidence (p = .615). Pharmacogenomic usage, defined as ordering a pharmacogenomic test within the past year, was low (n = 76, 29%) and most (n = 210, 84%) reported never using CPIC Guidelines. Advanced practice registered nurses (n = 162) who did not anticipate ordering a pharmacogenomic test in the next year (n = 77, 48%) indicated that they did not know what test to order. Conclusions: Deficits were identified in APRN pharmacogenomic knowledge and skills despite academic training. Most reported not ordering pharmacogenomic tests, did not know what test to order, and did not use CPIC guidelines. Implications: Pharmacogenomics is a quality and safety issue. Academic training did not result in practice integration and most reported capacity deficits. Recommendation for overcoming academic deficits include: (1) assessment of pharmacogenomics curricular content and faculty teaching capacity; (2) training addressing identified deficiencies; and (3) Commission of Collegiate Nursing Education policies that include pharmacogenomics in advanced pharmacology. Practicing APRN plans include on-the-job training and/or mandatory training at the time of relicensure. [ABSTRACT FROM AUTHOR]

Resistant hypertension (RHTN) prevalence ranges from 4 to 19% in Africa. There is a paucity of data on the role of genetic variation on RHTN among Africans. We set out to investigate the role of polymorphisms in ABCB1, ADRB1, CYP3A4, CYP3A5, NEDD4L, and NR3C2, on RHTN susceptibility among South Africans. Using a retrospective matched case–control study, 190 RHTN patients (cases: blood pressure (BP) ≥ 140/90 mmHg on ≥3 anti-hypertensives or BP < 140/90 mmHg on >3 anti-hypertensives) and 189 non-RHTN patients (controls: <3 anti-hypertensives, BP < 140/90 or ≥140/90 mmHg), 12 single nucleotide polymorphisms were genotyped using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP), quantitative PCR and Sanger sequencing. Genetic association analyses were conducted using the additive model and multivariable logistic regression. Homozygosity for CYP3A5 rs776746C/C genotype (p = 0.02; OR: 0.44; CI: 0.22–0.89) was associated with reduced risk for RHTN. Homozygous ADRB1 rs1801252G/G (p = 0.02; OR: 3.30; CI: 1.17–10.03) and NEDD4L rs4149601A/A genotypes (p = 0.001; OR: 3.82; CI: 1.67–9.07) were associated with increased risk for RHTN. Carriers of the of ADRB1 rs1801252—rs1801253 G–C haplotype had 2.83-fold odds of presenting with RHTN (p = 0.04; OR: 2.83; CI: 1.05–8.20). These variants that are associated with RHTN may have clinical utility in the selection of antihypertensive drugs in our population. [ABSTRACT FROM AUTHOR]

Aim: Remethylation disorders such as 5,10-methylenetetrahydrofolate reductase (MTHFR) deficiency reduce the remethylation of homocysteine to methionine. The resulting hyperhomocysteinemia can lead to serious neurological consequences and multisystem toxicity. The role of MTHFR genotypes has not been investigated in patients with Rett Syndrome (RTT). In this study, we sought to assess the impact of co-occurring MTHFR genotypes on symptom profiles in RTT. Method: Using pharmacogenomic (PGx) testing, the MTHFR genetic polymorphisms rs1801133 (c.665C>T mutation) and rs1801131 (c.1286A>C mutation) were determined in 65 patients (18.7 years ± 12.1 [mean ± standard deviation]) with RTT as part of routine clinical care within the Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, a National and Specialist Child and Adolescent Mental Health Service (CAMHS) in the UK. The clinical severity of patients was assessed using the RTT-anchored Clinical Global Impression Scale (RTT-CGI). Results: The clinical severity symptom distribution varied between the homozygous and heterozygous MTHFR rs1801133 and rs1801131 genotypes. Those with the homozygous genotype had a narrower spread of severity scores across several domains (language and communication, ambulation, hand-use and eye contact clinical domains). Patients with the homozygous genotype had statistically significantly greater CGI-Severity scores than individuals with a non-homozygous MTHFR genotype (Z = −2.44, p = 0.015). When comparing the ratings of moderately impaired (4), markedly impaired (5), severely impaired (6) and extremely impaired (7), individuals with the homozygous MTHFR genotype were more impaired than those with the non-homozygous MTHFR genotype (Z = −2.06, p = 0.039). There was no statistically significant difference in the number of prescribed anti-epileptic drugs between the genotypes. Conclusions: Our findings show that in those with a pathogenic RTT genetic variant, co-occurring homozygotic MTHFR rs1801133 and rs1801131 polymorphisms may act as associative genetic modifiers of clinical severity in a subset of patients. Profiling of rs1801133 and rs1801131 in RTT may therefore be useful, especially for high-risk patients who may be at the most risk from symptom deterioration. [ABSTRACT FROM AUTHOR]

The majority of the well-known pharmacogenomics research used in the medical sciences contributes to our understanding of medication interactions. It has a significant impact on treatment and drug development. The broad use of pharmacogenomics is required for the progress of therapy. The main focus is on how genes and an intricate gene system affect the body's reaction to medications. Novel biomarkers that help identify a patient group that is more or less likely to respond to a certain medication have been discovered as a result of recent developments in the field of clinical therapeutics. It aims to improve customized therapy by giving the appropriate drug at the right dose at the right time and making sure that the right prescriptions are issued. A combination of genetic, environmental, and patient variables that impact the pharmacokinetics and/or pharmacodynamics of medications results in interindividual variance in drug response. Drug development, illness susceptibility, and treatment efficacy are all impacted by pharmacogenomics. The purpose of this work is to give a review that might serve as a foundation for the creation of new pharmacogenomics applications, techniques, or strategies. [ABSTRACT FROM AUTHOR]

Pharmacogenomics (PGx) is the hope for the full optimization of drug therapy while minimizing the accompanying adverse drug events that cost billions of dollars annually. Since years before the century, it has been known that inter-individual variations contribute to differences in specific drug responses. It is the bridge to what is well-known today as "personalized medicine". Addressing the drug's pharmacokinetics and pharmacodynamics is one of the features of this science, owing to patient characteristics that vary on so many occasions. Mainly in the liver parenchymal cells, intricate interactions between the drug molecules and enzymes family of so-called "Cytochrome P450" occur which hugely affects how the body will react to the drug in terms of metabolism, efficacy, and safety. Single nucleotide polymorphisms, once validated for a transparent and credible clinical utility, can be used to guide and ensure the succession of the pharmacotherapy plan. Novel tools of pharmacoeconomics science are utilized extensively to assess cost-effective pharmacogenes preceding the translation to the bedside. Drug development and discovery incorporate a drug-gene perspective and save more resources. Regulations and laws shaping the clinical PGx practice can be misconceived; however, these pre-/post approval processes ensure the product's safety and efficacy. National and international regulatory agencies seek guidance on maintaining conduct in PGx practice. In this patient-centric era, social and legal considerations manifest in a way that makes them unavoidable, involving patients and other stakeholders in a deliberate journey toward utmost patient well-being. In this comprehensive review, we contemporarily addressed the scientific leaps in PGx, along with various challenges that face the proper implementation of personalized medicine in Egypt. These informative insights were drawn to serve what the Egyptian population, in particular, would benefit from in terms of knowledge and know-how while maintaining the latest global trends. Moreover, this review is the first to discuss various modalities and challenges faced in Egypt regarding PGx, which we believe could be used as a pilot piece of literature for future studies locally, regionally, and internationally. [ABSTRACT FROM AUTHOR]

There is growing evidence that pharmacogenetic analysis can improve drug therapy for individual patients. In Switzerland, pharmacists are legally authorized to initiate pharmacogenetic tests. However, pharmacogenetic tests are rarely conducted in Swiss pharmacies. Therefore, we aimed to identify implementation strategies that facilitate the integration of a pharmacist-led pharmacogenetic service into clinical practice. To achieve this, we conducted semi-structured interviews with pharmacists and physicians regarding the implementation process of a pharmacist-led pharmacogenetic service. We utilized the Consolidated Framework for Implementation Research (CFIR) to identify potential facilitators and barriers in the implementation process. Additionally, we employed Expert Recommendations for Implementing Change (ERIC) to identify strategies mentioned in the interviews and used the CFIR-ERIC matching tool to identify additional strategies. We obtained interview responses from nine pharmacists and nine physicians. From these responses, we identified 7 CFIR constructs as facilitators and 12 as barriers. Some of the most commonly mentioned barriers included unclear procedures, lack of cost coverage by health care insurance, insufficient pharmacogenetics knowledge, lack of interprofessional collaboration, communication with the patient, and inadequate e-health technologies. Additionally, we identified 23 implementation strategies mentioned by interviewees using ERIC and 45 potential strategies using the CFIR-ERIC matching tool. In summary, we found that significant barriers hinder the implementation process of this new service. We hope that by highlighting potential implementation strategies, we can advance the integration of a pharmacist-led pharmacogenetic service in Switzerland. [ABSTRACT FROM AUTHOR]

KEY IDEAS: Anti‐D cannot agglutinate red cells of any Del phenotype in routine serology.Many individuals with East Asian ancestry who type D‐negative in serology harbor a Del phenotype.Almost all such individuals carry one distinct DEL variant, dubbed Asian‐type DEL, known as RHD*01EL.01, RHD*DEL1, RHD:c.1227G>A, formerly known as RHD(K409K).Clinical evidence strongly suggests that Asian‐type DEL individuals can safely be transfused with RhD‐positive blood and do not need anti‐D prophylaxis in pregnancy. [ABSTRACT FROM AUTHOR]

Background Aminoglycosides (AGs) are important antibiotics in the treatment of Gram-negative sepsis. However, they are associated with the risk of irreversible sensorineural hearing loss (SNHL). Several genetic variants have been implicated in the development of ototoxicity. Objectives To evaluate the pharmacogenetic determinants of AG-related ototoxicity. Methods This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses and was registered on Prospero (CRD42022337769). In Dec 2022, PubMed, Cochrane Library, Embase and MEDLINE were searched. Included studies were those reporting original data on the effect of the AG-exposed patient's genome on the development of ototoxicity. Results Of 10 202 studies, 31 met the inclusion criteria. Twenty-nine studies focused on the mitochondrial genome, while two studied the nuclear genome. One study of neonates found that 30% of those with the m.1555A > G variant failed hearing screening after AG exposure (level 2 evidence). Seventeen additional studies found the m.1555A > G variant was associated with high penetrance (up to 100%) of SNHL after AG exposure (level 3–4 evidence). Nine studies of m.1494C > T found the penetrance of AG-related SNHL to be up to 40%; however, this variant was also identified in those with SNHL without AG exposure (level 3–4 evidence). The variants m.1005T > C and m.1095T > C may be associated with AG-related SNHL; however, further studies are needed. Conclusions This review found that the m.1555A > G and m.1494C > T variants in the MT-RNR1 gene have the strongest evidence in the development of AG-related SNHL, although study quality was limited (level 2–4). These variants were associated with high penetrance of a SNHL phenotype following AG exposure. [ABSTRACT FROM AUTHOR]

This article, published in the American Journal of Psychiatry, explores the topics of affective disorders, pharmacogenomics, and psychiatric illness-related cardiometabolic problems. It discusses the use of pharmacogenomic tools in treating depression and examines the genetics of affective disorders and bipolar disorder. The article also investigates the connection between antidepressant use and the induction of hypomania/mania in bipolar depression, as well as the relationship between alterations in stress responsivity and the pathophysiology of depression. Additionally, it assesses the risk of developing cardiometabolic problems in various psychiatric illnesses. The findings provide valuable insights into the genetics, pathophysiology, and treatment of affective disorders, as well as the associations between different psychiatric disorders and the development of cardiometabolic problems. The article discusses the results of a study on patients with major depression, which revealed abnormal brain activity in mood regulation networks and blunted stress-related cortisol levels. The study also found decreased GABA levels in a specific brain region and a negative correlation between cortisol reactivity and brain activity in depressed patients. The authors suggest that these findings indicate faulty regulation and abnormal associations between brain activity and stress response in depressed individuals. Another study examined the relationship between psychiatric disorders and cardiometabolic problems, finding that individuals with psychiatric diagnoses had an increased risk of developing cardiovascular disorders and metabolic syndrome. The authors concluded that a general psychopathology factor contributes to this increased risk. [Extracted from the article]

Introduction: CYP2C19 plays a major role in the metabolism of various drugs. The most common genetic variants were the CYP2C19*2 and *3 alleles (rs4244285 and rs4986893, non-functional variants). In previous studies, we found that genetic polymorphisms in CYP2C19 variants influenced the active metabolites of clopidogrel and caused major adverse cardiovascular and cerebrovascular effects. However, the distribution of CYP2C19 varies among ethnic groups and according to adverse drug reactions. This study aimed to investigate the frequency of CYP2C19 genetic polymorphisms in the Thai population and analyze the differences in the frequency of CYP2C19 genetic polymorphisms between Thai and other populations. Methods: This study enrolled 211 unrelated healthy Thai individuals in total. We performed a real-time polymerase chain reaction to genotype CYP2C19*2 (681G > A) and CYP2C19*3 (636G > A). Results: In the Thai population, the CYP2C19*1 allele was the most prevalent at 70.14%, while the CYP2C19*2 and *3 alleles were found at frequencies of 25.36% and 4.50%, respectively. Conversely, the CYP2C19*3 allele was not detected in Caucasian, Hispanic, African, Italian, Macedonian, Tanzanian, or North Indian populations. The phenotypic profile of this gene revealed that the frequency of intermediate metabolizers (IMs) is nearly equal to that of extensive metabolizers (EMs), at 42.65% and 48.82% respectively, with genotypes *1/*2 (36.02%) and *1/*3 (6.63%). Likewise, poor metabolizers (PMs) with genotypes *2/*2 (6.16%), *2/*3 (2.37%), and *3/*3 (< 1%) are more prevalent in our population as well. Conclusion: The distribution of CYP2C19 genotype and phenotype influenced by non-functional alleles has potential as a pharmacogenomics biomarker for precision medicine and is dependent on an ethnic-specific genetic variation database. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) has traditionally been considered the archetype of progressive fibrotic interstitial lung diseases (f-ILDs), but several other f-ILDs can also manifest a progressive phenotype. Integrating genomic signatures into clinical practice for f-ILD patients may help to identify patients predisposed to a progressive phenotype. In addition to the risk of progressive pulmonary fibrosis, there is a growing body of literature examining how pharmacogenomics influences treatment response, particularly regarding the efficacy and safety profiles of antifibrotic and immunomodulatory agents. In this narrative review, we discuss current studies in IPF and other forms of pulmonary fibrosis, including systemic autoimmune disorders associated ILDs, sarcoidosis and hypersensitivity pneumonitis. We also provide insights into the future direction of research in this complex field. [ABSTRACT FROM AUTHOR]

This study focuses on the role of topoisomerases (TOPs) in sarcomas (SARCs), highlighting TOPs' influence on sarcoma prognosis through mRNA expression, genetic mutations, immune infiltration, and DNA methylation analysis using transcriptase sequencing and other techniques. The findings indicate that TOP gene mutations correlate with increased inflammation, immune cell infiltration, DNA repair abnormalities, and mitochondrial fusion genes alterations, all of which negatively affect sarcoma prognosis. Abnormal TOP expression may independently affect sarcoma patients' survival. Cutting‐edge genomic tools such as Oncomine, gene expression profiling interactive analysis (GEPIA), and cBio Cancer Genomics Portal (cBioPortal) are utilized to explore the TOP gene family (TOP1/1MT/2A/2B/3A/3B) in soft‐tissue sarcomas (STSs). This in‐depth analysis reveals a notable upregulation of TOP mRNA in STS patients arcoss various SARC subtypes, French Federation Nationale des Centres de Lutte Contre le Cancer classification (FNCLCC) grades, and specific molecular profiles correlating with poorer clinical outcomes. Furthermore, this investigation identifies distinct patterns of immune cell infiltration, genetic mutations, and somatic copy number variations linked to TOP genes that inversely affect patient survival rates. These findings underscore the diagnostic and therapeutic relevance of the TOP gene suite in STSs. [ABSTRACT FROM AUTHOR]

Multi-omics sequencing is poised to revolutionize clinical care in the coming decade. However, there is a lack of effective and interpretable genome-wide modeling methods for the rational selection of patients for personalized interventions. To address this, we present iGenSig-Rx, an integral genomic signature-based approach, as a transparent tool for modeling therapeutic response using clinical trial datasets. This method adeptly addresses challenges related to cross-dataset modeling by capitalizing on high-dimensional redundant genomic features, analogous to reinforcing building pillars with redundant steel rods. Moreover, it integrates adaptive penalization of feature redundancy on a per-sample basis to prevent score flattening and mitigate overfitting. We then developed a purpose-built R package to implement this method for modeling clinical trial datasets. When applied to genomic datasets for HER2 targeted therapies, iGenSig-Rx model demonstrates consistent and reliable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We anticipate that iGenSig-Rx, as an interpretable class of multi-omics modeling methods, will find broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx. [ABSTRACT FROM AUTHOR]

Purpose To describe our experiences implementing and iterating CYP2C19 genotype–guided clopidogrel pharmacogenetic clinical decision support (CDS) tools over time in the setting of a large health system–wide, preemptive pharmacogenomics program. Summary Clopidogrel-treated patients who are genetically predicted cytochrome P450 isozyme 2C19 (CYP2C19) intermediate or poor metabolizers have an increased risk of atherothrombotic events, some of which can be life-threatening. The Clinical Pharmacogenetics Implementation Consortium provides guidance for the use of clopidogrel based on CYP2C19 genotype in patients with cardiovascular and cerebrovascular diseases. Our multidisciplinary team implemented an automated, interruptive alert that fires when clopidogrel is ordered or refilled for biobank participants with structured CYP2C19 intermediate or poor metabolizer genomic indicators in the electronic health record. The implementation began with a narrow cardiovascular indication and setting and was then scaled in 4 primary dimensions: (1) clinical indication; (2) availability across health-system locations; (3) care venue (e.g. inpatient vs outpatient); and (4) provider groups (eg, cardiology and neurology). We iterated our approach over time based on evolving clinical evidence and proactive strategies to optimize CDS maintenance and sustainability. A key facilitator of expansion was socialization of the broader pharmacogenomics initiative among our academic medical center community, accompanied by clinician acceptance of pharmacogenetic alerts in practice. Conclusion A multidisciplinary collaboration is recommended to facilitate the use of CYP2C19 genotype–guided antiplatelet therapy in patients with cardiovascular and cerebrovascular diseases. Evolving clopidogrel pharmacogenetic evidence necessitates thoughtful iteration of implementation efforts and strategies to optimize long-term maintenance and sustainability. [ABSTRACT FROM AUTHOR]

Rationale: Standardized dosing of antitubercular drugs leads to variable plasma drug levels, which are associated with adverse drug reactions, delayed treatment response, and relapse. Mutations in genes affecting drug metabolism explain considerable interindividual pharmacokinetic variability; however, pharmacogenomic assays that predict metabolism of antitubercular drugs have been lacking. Objectives: We sought to develop a Nanopore sequencing panel and validate its performance in patients with active tuberculosis (TB) to personalize treatment dosing. Methods: We developed a Nanopore sequencing panel targeting 15 SNPs in five genes affecting the metabolism of antitubercular drugs. For validation, we sequenced DNA samples (n = 48) from the 1,000 Genomes Project and compared the variant calling accuracy with that of Illumina genome sequencing. We then sequenced DNA samples from patients with active TB (n = 100) from South Africa on a MinION Mk1C and evaluated the relationship between genotypes and pharmacokinetic parameters for isoniazid (INH) and rifampin (RIF). Measurements and Main Results: The pharmacogenomic panel achieved 100% concordance with Illumina sequencing in variant identification for the samples from the 1,000 Genomes Project. In the clinical cohort, coverage was more than 100× for 1,498 of 1,500 (99.8%) amplicons across the 100 samples. Thirty-three percent, 47%, and 20% of participants were identified as slow, intermediate, and rapid INH acetylators, respectively. INH clearance was 2.2 times higher among intermediate acetylators and 3.8 times higher among rapid acetylators, compared with slow acetylators (P < 0.0001). RIF clearance was 17.3% (2.50–29.9) lower in individuals with homozygous AADAC rs1803155 G→A substitutions (P = 0.0015). Conclusions: Targeted sequencing can enable the detection of polymorphisms that influence TB drug metabolism on a low-cost, portable instrument to personalize dosing for TB treatment or prevention. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions Pharmacogenetics (PGx) is increasingly recognized as a strategy for medicines optimisation and prevention of adverse drug reactions. According to guidelines produced by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetic Working Group (DPWG), most medicines with drug‐gene interactions (DGIs) are prescribed in primary care. This study aimed to estimate the prevalence of potential and actionable DGIs involving all medicines dispensed in Irish primary care.Dispensings of 46 drugs to General Medical Services (GMS) patients in the Health Service Executive Primary Care Reimbursement Service Irish pharmacy claims database from 01 January 2021 to 31 December 2021 were analysed to estimate the national prevalence of total dispensings and incidence of first‐time dispensings of drugs with potential DGIs according to the CPIC and/or DPWG guidelines. Phenotype frequency data from the UK Biobank and the CPIC were used to estimate the incidence of actionable DGIs.One in five dispensings (12 443 637 of 62 754 498, 19.8%) were medicines with potential DGIs, 1 878 255 of these dispensed for the first time. On application of phenotype frequencies and linked guideline based therapeutic recommendations, 2 349 055 potential DGIs (18.9%) required action, such as monitoring and guarding against maximum dose, drug or dose change. One in five (369 700, 19.7%) first‐time dispensings required action, with 139 169 (7.4%) requiring a change in prescribing. Antidepressants, weak opioids and statins were most commonly identified as having actionable DGIs.This study estimated a high prevalence of DGIs in primary care in Ireland, identifying the need and opportunity to optimize drug therapy through PGx testing. [ABSTRACT FROM AUTHOR]

Salmonella enteritidis is a main pathogen responsible for sporadic outbreaks of gastroenteritis, and therefore is an important public health problem. This study investigated the drug resistance and genomic characteristics of S. enteritidis isolated from clinical and food sources in Huzhou, Zhejiang Province, China, from February 1, 2021, to December 30, 2023. In total, 43 S. enteritidis strains isolated during the study period were subjected to virulence gene, drug resistance gene, genetic correlation, antibiotic resistance, and multilocus sequence typing analyses. All 43 isolates were identified as ST11, and contained 108 virulence-related genes. Drug sensitivity analysis of the 43 isolates showed resistance rates of 100% to nalidixic acid and 90.70% to ampicillin and ampicillin/sulbactam. Multidrug resistance is a serious issue, with 81.40% of strains resistant to three or more antibacterial drugs. Genome sequencing indicated that S. enteritidis possessed 23 drug resistance genes, of which 14 were common to all 43 isolates. Phylogenetic analysis based on core genome single-nucleotide polymorphisms divided the 43 S. enteritidis strains into three clusters, with the 10 samples from an outbreak forming an independent branch located in cluster 3. [ABSTRACT FROM AUTHOR]

Background: Pharmacogenetic profiling and therapeutic drug monitoring (TDM) have both been proposed to manage inter-individual variability (IIV) in drug exposure. However, determining the most effective approach for estimating exposure for a particular drug remains a challenge. This study aimed to quantitatively assess the circumstances in which pharmacogenetic profiling may outperform TDM in estimating drug exposure, under three sources of variability (IIV, inter-occasion variability [IOV], and residual unexplained variability [RUV]). Methods: Pharmacokinetic models were selected from the literature corresponding to drugs for which pharmacogenetic profiling and TDM are both clinically considered approaches for dose individualization. The models were used to simulate relevant drug exposures (trough concentration or area under the curve [AUC]) under varying degrees of IIV, IOV, and RUV. Results: Six drug cases were selected from the literature. Model-based simulations demonstrated that the percentage of patients for whom pharmacogenetic exposure prediction is superior to TDM differs for each drug case: tacrolimus (11.0%), tamoxifen (12.7%), efavirenz (49.2%), vincristine (49.6%), risperidone (48.1%), and 5-fluorouracil (5-FU) (100%). Generally, in the presence of higher unexplained IIV in combination with lower RUV and IOV, exposure was best estimated by TDM, whereas, under lower unexplained IIV in combination with higher IOV or RUV, pharmacogenetic profiling was preferred. Conclusions: For the drugs with relatively low RUV and IOV (e.g., tamoxifen and tacrolimus), TDM estimated true exposure the best. Conversely, for drugs with similar or lower unexplained IIV (e.g., efavirenz or 5-FU, respectively) combined with relatively high RUV, pharmacogenetic profiling provided the most accurate estimate for most patients. However, genotype prevalence and the relative influence of genotypes on the PK, as well as the ability of TDM to accurately estimate AUC with a limited number of samples, had an impact. The results could be used to support clinical decision making when considering other factors, such as the probability for severe side effects. [ABSTRACT FROM AUTHOR]