Pharmacogenomics Applications in Clinical Practice: Revolutionizing Patient Care

Putting pharmacogenomics into practice

The Pharmacogenomics Horizon

In the biology of complex disorders, such as breast cancer, interactions among genetic factors may play an important role and theoretical considerations suggest that gene-gene interactions are quite common in such diseases. In this case-control study with 500 breast cancer patients and 500 population-based healthy sex- and age-matched control subjects, we applied a multigenic approach to examine the associations with breast cancer risk of a comprehensive panel of 16 selected polymorphisms in a variety of pathways using classification tree analysis (CART). Overall, 79.6% of all breast cancer patients and 80.6% of all control subjects were correctly classified on the basis of their individual genetic profile by the classification procedure. CART analysis of the data identified the heterozygous vascular endothelial growth factor (VEGF) and matrix metalloproteinase 3 (MMP3) genotype and homozygous cyclooxygenase-2 (PTGS2) mutant as the initial splits, indicating that these genotypes exert the greatest impact on the classification process. Breast cancer patients were primarily indicated by 30 distinct genetic profiles. The odds ratio of these genetic risk profiles for breast cancer was 16.12 (95% confidence interval 11.09-23.49). Five genetic profiles formed homogenous breast cancer subgroups and represented highest risk genetic profiles. This is the first comprehensive study to use a multigenic analysis for breast cancer and the data suggest that individuals with distinct genetic profiles are at an increased risk for breast cancer, confirming the importance of taking a multigenic approach for risk assessment.

Cybersecurity vulnerabilities of cardiac implantable electronic devices: Communication strategies for clinicians—Proceedings of the Heart Rhythm Society's Leadership Summit

Ethical issues in pediatric pharmacogenomics.

In order to explore valproate's spectrum of efficacy in rapid-cycling bipolar disorder, 55 patients underwent a prospective, open, 7.8-month trial designed to assess the drug's acute and prophylactic properties. Twenty patients received monotherapy, and 35 received combination therapy. Moderate to marked acute antidepressant responses were seen in 47% of the patients, prophylactic antidepressant responses in 76%, acute antimanic responses in 91%, prophylactic antimanic responses in 94%, acute responses in mixed states in 85%, and prophylactic responses in mixed states in 93%. Consistent with other anticonvulsant literature, these data suggest that valproate has marked antimanic and mixed state efficacy, but minimal to moderate antidepressant properties.

Building the patient–clinician relationship through conversation based on narrative approaches

Pharmacogenomics is the examination of how genetic variation influences drug metabolism and response, in terms of both efficacy and safety. In cardiovascular disease, patient-specific diplotypes determine phenotypes, thereby influencing the efficacy and safety of drug treatments, including statins, antiarrhythmics, anticoagulants and antiplatelets. Notably, polymorphisms in key genes, such as CYP2C9, CYP2C19, VKORC1 and SLCO1B1, significantly impact the outcomes of treatment with clopidogrel, warfarin and simvastatin. Furthermore, the CYP2C19 polymorphism influences the pharmacokinetics and safety of the novel hypertrophic cardiomyopathy inhibitor, mavacamten. In this review, we critically assess the clinical application of pharmacogenomics in cardiovascular disease and delineate present and future utilization of pharmacogenomics. This includes insights into identifying missing heritability, the integration of whole genome sequencing and the application of polygenic risk scores to enhance the precision of personalized drug therapy. Our discussion encompasses health economic analyses that underscore the cost benefits associated with pre-emptive genotyping for warfarin and clopidogrel treatments, albeit acknowledging the need for further research in this area. In summary, we contend that cardiovascular pharmacogenomic analyses are underpinned by a wealth of evidence, and implementation is already occurring for some of these gene-drug pairs, but as with any area of medicine, we need to continually gather more information to optimize the use of pharmacogenomics in clinical practice.

The authors investigated the pharmacological treatment of delusional depression by assigning patients on a random double-blind basis to amitriptyline alone, perphenazine alone, or a combination of the two. Fourteen (78%) of the 18 patients assigned to amitriptyline plus perphenazine were responders, compared with seven (41%) of 17 patients treated with amitriptyline alone and three (19%) of the 16 patients treated with perphenazine alone. The combination of amitriptyline and perphenazine was clearly superior (p less than .01).

Pharmacogenomics, the study of how genetic variations influence drug response, has become integral to cancer treatment as personalized medicine evolves. This review aims to explore key pharmacogenomic biomarkers relevant to cancer therapy and their clinical implications, providing an updated and comprehensive perspective on how genetic variations impact drug metabolism, efficacy, and toxicity in oncology. Genetic heterogeneity among oncology patients significantly impacts drug efficacy and toxicity, emphasizing the importance of incorporating pharmacogenomic testing into clinical practice. Genes such as CYP2D6, DPYD, UGT1A1, TPMT, EGFR, KRAS, and BRCA1/2 play pivotal roles in influencing the metabolism, efficacy, and adverse effects of various chemotherapeutic agents, targeted therapies, and immunotherapies. For example, CYP2D6 polymorphisms affect tamoxifen metabolism in breast cancer, while DPYD variants can result in severe toxicities in patients receiving fluoropyrimidines. Mutations in EGFR and KRAS have significant implications for the use of targeted therapies in lung and colorectal cancers, respectively. Additionally, BRCA1/2 mutations predict the efficacy of PARP inhibitors in breast and ovarian cancer. Ongoing research in polygenic risk scores, liquid biopsies, gene-drug interaction networks, and immunogenomics promises to further refine pharmacogenomic applications, improving patient outcomes and reducing treatment-related adverse events. This review also discusses the challenges and future directions in pharmacogenomics, including the integration of computational models and CRISPR-based gene editing to better understand gene-drug interactions and resistance mechanisms. The clinical implementation of pharmacogenomics has the potential to optimize cancer treatment by tailoring therapies to an individual's genetic profile, ultimately enhancing therapeutic efficacy and minimizing toxicity.

The development and evaluation of eHealth interventions in clinical care should be accompanied by a thorough assessment of their implementation. The NASSS (Non-adoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies) framework was designed to facilitate the implementation and scale-up of health technology programs, providing an option for analyzing the progression of these initiatives as they are implemented in real-time. Considering health care provider perspectives within the framework for implementation offers valuable insights into the early identification of barriers and facilitators in the implementation of potentially effective eHealth innovations. Nevertheless, there is a dearth of studies on eHealth interventions that encompass longer time frames and delve into the complexities of scaling up and sustaining such interventions within real-world health care environments. This study aims to investigate the perspectives and insights of health care professionals (HCPs) regarding the implementation of an eHealth intervention in pediatric health care while applying the NASSS framework to theorize and evaluate the conditions influencing the implementation of eHealth solutions. Semistructured interviews were performed with health care providers, including both staff and management personnel, within a university pediatric hospital (N=10). The data collection process occurred concurrently with a clinical trial focused on developing and assessing an eHealth app for self-management in pediatric care following hospital discharge. Using an abductive approach, the interviews were initially analyzed qualitatively and subsequently mapped onto the 7 domains of the NASSS framework to identify factors influencing implementation, encompassing facilitators, barriers, and varying levels of complexity. In the realm of pediatric care, the family was identified as the primary unit of care, and patient heterogeneity was a prominent feature. The implementation of eHealth tools, while deemed usable and flexible, was also seen as a delicate balance between safety and adaptability, highlighting challenges related to health care integration. Child participation and secrecy, especially for adolescents, contributed to the complexity of using eHealth. HCPs had high eHealth literacy, and thus challenges concerning adoption were related to work adaptations and the risk of "app overload." The readiness for implementation was experienced as induced through the research study and the pandemic situation. However, to move from research to implementation in clinical practice, organizational challenges identified a need to update the concept of care and ensure activity measurements. In a wider context, HCPs raised concerns related to regulatory requirements for documentation, public procurement, and data safety. Implementation became more complex due to a lack of overview in a large organization. Important perspectives for implementation were considerations of regulatory requirements, as well as the need for a shared vision of eHealth and the establishment of eHealth-related work as part of regular health care. Key contextual factors that support reach and impact are communication channels between different levels at the hospital and a need for paths and procedures compatible with legal, technological, and security concerns. Further research should focus on how eHealth interventions are perceived by children, adolescents, their parents, and other stakeholders. ClinicalTrials.gov NCT04150120; https://clinicaltrials.gov/ct2/show/NCT04150120.

Personalized medicine offers the promise of better diagnoses, targeted therapies and individualized treatment plans. Pharmacogenomics is an integral component of personalized medicine; it aids in the prediction of an individual's response to medications. Despite growing public acceptance and emerging clinical evidence, this rapidly expanding field of medicine is slow to be adopted and utilized by healthcare providers, although many believe that they should be knowledgeable and able to apply pharmacogenomics in clinical practice. Institutional infrastructure must be built to support pharmacogenomic implementation. Multidisciplinary education for healthcare providers is a critical component for pharmacogenomics to achieve its full potential to optimize patient care. We describe our recent experience at the Mayo Clinic implementing pharmacogenomics education in a large, academic healthcare system facilitated by the Mayo Clinic Center for Individualized Medicine.

A Physiologic Approach to the Pharmacogenomics of Hypertension

The use of companion diagnostic-medicine combinations to targetpharmacological treatments can potentially be beneficial to patientsand health care providers alike, with improved clinical effectiveness,fewer episodes of adverse events, and reduced costs to healthcare systems predicted. However, decision makers charged withallocating finite health care budgets require robust and timelyevidence to support the clinical effectiveness and cost-effectivenessof pharmacogenetic and pharmacogenomic technologies before theycan be recommended for funding and use in clinical practice.This chapter describes the underlying concepts that inform theframework of economic evaluation. Economic evaluation is amethod that is used to quantify the incremental costs and benefitsof new interventions compared with current practice. The chapterintroduces the types of methods of economic evaluation andprovides an overview of the design of an economic evaluation. Thechapter then summarizes the current level of evidence supportingthe use of pharmacogenetic and pharmacogenomic technologies.The chapter concludes by describing the current key issues andsuggests some future challenges for the design, conduct, and use ofstudies to evaluate the cost-effectiveness of pharmacogenomics inclinical practice.

Cost-effectiveness analysis is a widely used tool to assess the value of healthcare interventions. Our objective was to conduct a systematic review of the literature on the cost effectiveness of pharmacogenomic interventions. We found 11 studies that met our inclusion criteria. The most commonly examined disease was deep vein thrombosis (n=4), followed by cancer (n=3) and viral infections (n=3); the most frequently examined mutation was factor V Leiden (n=5); and the majority of the mutations examined were inherited mutations (n=7), although several studies looked at acquired (tumor or viral) mutations (n=4). The majority of the studies reported a favorable cost-effectiveness ratio for the pharmacogenomic-based strategy (n=7), while two studies reported that the pharmacogenomic-based strategy was not cost effective and two were equivocal. We conclude that there have been few evaluations of the economic costs and benefits of pharmacogenomic interventions and they have covered a limited number of conditions. Further analyses that can be used to guide the use of pharmacogenomics in clinical practice and in developing health policies are urgently needed.