Search

Pharmacogenomics (PGx) utilizes an individual’s germline genetic profile to identify those who are at higher risk for ADRs or lack of efficacy. This information can be used by healthcare professionals (HCPs) to guide dose and drug selection before drug initiation in an effort to optimize drug therapy through precision medicine. Despite both the promise of and the progress in the field of PGx to achieve precision medicine, it is still not routinely applied in patient care. As such, a number of barriers preventing implementation have been identified. These include the undetermined model for delivering PGx, the lack of evidence supporting a PGx panel approach and the lack of tools supporting implementation. Therefore, the work of this thesis aims to support the implementation of precision medicine using PGx panel testing. It reports on generating evidence for PGx panel testing (Part I) and the development of tools facilitating implementation (Part II), evaluates the implementation process utilizing these tools (Part III) and quantifies the impact of PGx implementation on patient outcomes and cost-effectiveness (Part IV).

To explore the pharmacogenomic markers that affect the platinum-based chemotherapy response in non-small-cell lung carcinoma (NSCLC), we performed a two-cohort of genome-wide association studies (GWAS), including 34 for WES-based and 433 for microarray-based analyses, as well as two independent validation cohorts. After integrating the results of two studies, the genetic variations related to the platinum-based chemotherapy response were further determined by fine-mapping in 838 samples, and their potential functional impact were investigated by eQTL analysis and in vitro cell experiments. We found that a total of 68 variations were significant at P

Despite an increase in the number of available therapeutics, many children with rheumatic disease continue to experience active inflammatory disease and treatment failure. One reason for treatment failure is the lack of dosing paradigms to account for the wide between-patient variability in drug pharmacokinetics because of developmental changes or genetic polymorphisms that effect drug absorption, distribution, metabolism, and elimination. This review highlights several strategies to optimize dosing for biologic and nonbiologic disease-modifying antirheumatic drugs, including therapeutic drug monitoring, pharmacogenomics, and the use of pharmacokinetic/pharmacodynamic modeling.

Purpose An increasing number of advanced non–small cell lung cancer (NSCLC) cases are being reported in the ageing population. However, studies on the use of afatinib in elderly patients are scarce. We conducted a prospective multicentre, single-arm, and open-label phase II trial for low-dose afatinib (30 mg/day) use in elderly patients with NSCLC with EGFR mutation to assess quality-of-life (QOL) and pharmacokinetic (PK)/pharmacogenomic (PGx) parameters. Patients and methods The primary end-point was the objective response rate (ORR), and the planned number of registered cases was 35, with a threshold ORR of 50%, an expected ORR of 75%, α of 0.05, and β of 0.1. Secondary end-points were progression-free survival (PFS), overall survival (OS), the incidence rate of adverse events (AEs), QOL survey (FACT-L), and trough plasma concentration of afatinib at steady state (Css) and at the occurrence of clinically significant AEs. Results The median age of the patients was 79 years. The ORR was 80.0% and the disease control rate was 91.4%. The median PFS and OS were 15.6 and 29.5 months, respectively. Four patients discontinued because of AEs. Treatment-related death was not observed. No significant change in QOL was observed at baseline and after 4, 8, and 12 weeks. Css was comparable with those in previous reports and was significantly higher in patients with grade 3 AEs. Direct correlations between afatinib treatment and PGx profiles were not observed. Conclusions An afatinib starting dose of 30 mg/day could be an effective and safe treatment option for elderly patients.

BACKGROUND Warfarin dose variability observed in patients is attributed to variation in genes involved in the warfarin metabolic pathway. Genetic variation in CYP2C9 and VKORC1 has been the traditional focus in evaluating warfarin dose variability, with little focus on other genes. OBJECTIVE We set out to evaluate 27 single nucleotide polymorphisms (SNPs) in the CYP2C cluster loci and 8 genes (VKORC1, ABCB1, CYP2C9, CYP2C19, CYP2C8, CYP1A2, CYP3A4, and CYP3A5) involved in pharmacokinetics of warfarin. PATIENTS/METHODS 503 participants were recruited among black Africans and Mixed Ancestry population groups, from South Africa and Zimbabwe, and a blood sample taken for DNA. Clinical parameters were obtained from patient medical records, and these were correlated with genetic variation. RESULTS Among black Africans, the SNPs CYP2C rs12777823G>A, CYP2C9 c.449G>A (*8), CYP2C9 c.1003C>T (*11) and CYP2C8 c.805A>T (*2) were significantly associated with warfarin maintenance dose. Conversely, CYP2C9 c.430C>T (*2), CYP2C8 c.792C>G (*4) and VKORC1 g.-1639G>A were significantly associated with maintenance dose among the Mixed Ancestry. The presence of CYP2C8*2 and CYP3A5*6 alleles was associated with increased mean warfarin maintenance dose, whereas CYP2C9*8 allele was associated with reduced warfarin maintenance dose. CONCLUSION African populations present with a diversity of variants that are important in predicting pharmacogenetics-based warfarin dosing in addition to those reported in CYP2C9 and VKORC1. It is therefore important, to include African populations in pharmacogenomics studies to be able to identify all possible biomarkers that are potential predictors for drug response.

Psychiatric genomics is providing insights into the nature of psychiatric conditions that in time should identify new drug targets and improve patient care. Less attention has been paid to psychiatric pharmacogenomics research, despite its potential to deliver more rapid change in clinical practice and patient outcomes. The pharmacogenomics of treatment response encapsulates both pharmacokinetic (“what the body does to a drug”) and pharmacodynamic (“what the drug does to the body”) effects. Despite early optimism and substantial research in both these areas, they have to date made little impact on clinical management in psychiatry. A number of bottlenecks have hampered progress, including a lack of large-scale replication studies, inconsistencies in defining valid treatment outcomes across experiments, a failure to routinely incorporate adverse drug reactions and serum metabolite monitoring in study designs, and inadequate investment in the longitudinal data collections required to demonstrate clinical utility. Nonetheless, advances in genomics and health informatics present distinct opportunities for psychiatric pharmacogenomics to enter a new and productive phase of research discovery and translation.

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

Background Nearly 300 medications contain pharmacogenomic information in their labeling approved by the U.S. Food and Drug Administration. As this number continues to grow, community pharmacists will be called on to use available pharmacogenomic data at the point of dispensing. Objective This qualitative study aimed to describe how pharmacists envision the integration of pharmacogenomic data into the current workflows of community pharmacy practice. Methods Community pharmacists from a regional supermarket chain pharmacy in the greater Pittsburgh area were interviewed using a semistructured interview guide. Participating pharmacists were presented with 3 clinical scenarios, followed by questions, to gain insight into how they envisioned the integration of pharmacogenomic data into community pharmacy workflow. The interview transcriptions were transcribed and coded. The content was analyzed to deduce the final themes. Supporting quotes were selected to illustrate each theme. Results Ten community pharmacists from 3 different pharmacy locations participated in the study. A thematic analysis produced 6 themes: (1) integrating pharmacogenomic data into the dispensing software, (2) receiving an alert for pharmacogenomic information within the dispensing software, (3) accessing pharmacogenomic clinical guidelines to guide drug–decision-making, (4) contacting the prescriber by adding a task to the call queue, (5) placing a mandatory counseling alert on medications that were adjusted using pharmacogenomic data, and (6) counseling the patient on the first refill of a medication that was adjusted using pharmacogenomic data. Conclusion This study describes how pharmacists envisioned the integration of pharmacogenomic data into community pharmacy workflow. The participants sought the integration of pharmacogenomic data into existing dispensing software, alerts for actionable prescribing changes using patient-specific pharmacogenomic data when available, and access to clinical decision support. In addition, the participants preferred to engage prescribers and receive alerts to counsel patients at prescription pick-up. These findings are key to integrating pharmacogenomic data into community pharmacy practice.

PURPOSE: Barriers to the implementation of pharmacogenomics in clinical practice have been thoroughly discussed over the past decade. METHODS: The objective of this scoping review was to characterize the peer-reviewed literature surrounding the experiences and actions of prescribers, pharmacists, or genetic counselors when using pharmacogenomic information in real-world or hypothetical research settings. RESULTS: A total of 33 studies were included in the scoping review. The majority of studies were conducted in the US (70%), used quantitative or mixed methods (79%) with physician or pharmacist respondents (100%). The qualitative content analysis revealed five major methodological approaches: hypothetical clinical case scenarios, real-world studies evaluating prescriber response to recommendations or alerts, cross-sectional quantitative surveys, cross-sectional qualitative surveys/interviews, and a quasi-experimental real-world study. CONCLUSION: The findings of this scoping review can guide further research on the factors needed to successfully integrate pharmacogenomics into clinical care.

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing, and to determine a minimal set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations on a minimal panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories in designing assays for PGx testing. When developing these recommendations, the Association for Molecular Pathology PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations with regard to PGx testing. The ultimate goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document is focused on clinical CYP2D6 PGx testing that may be applied to all cytochrome P450 2D6–metabolized medications. These recommendations are not meant to be interpreted as prescriptive but to provide a reference guide for clinical laboratories that may be either implementing PGx testing or reviewing and updating their existing platform.

CYP2C9 encodes a cytochrome P450 enzyme responsible for metabolizing up to 15% of small molecule drugs, and CYP2C9 variants can alter the safety and efficacy of these therapeutics. In particular, the anti-coagulant warfarin is prescribed to over 15 million people annually and polymorphisms in CYP2C9 can affect patient response leading to an increased risk of hemorrhage. We developed Click-seq, a pooled yeast-based activity assay to test thousands of variants. Using Click-seq, we measured the activity of 6,142 missense variants expressed in yeast. We also measured the steady-state cellular abundance of 6,370 missense variants expressed in a human cell line using Variant Abundance by Massively Parallel sequencing (VAMP-seq). These data revealed that almost two-thirds of CYP2C9 variants showed decreased activity, and that protein abundance accounted for half of the variation in CYP2C9 function. We also measured activity scores for 319 previously unannotated human variants, many of which may have clinical relevance.

Drug hypersensitivity reactions (DHR) are heterogeneous in their pathomechanisms, clinical presentation, severity, and outcomes. Novel DHR mechanisms, phenotypes, and endotypes have been described. The key to prevention from further exposure to the culprit drugs involves correct identification of the putative drug through a combination of in vitro and/or in vivo tests, accurate drug allergy labeling and reporting, and electronic decision support systems within electronic medical records to prevent future accidental prescribing. Prescreening and premedication, the focus of this review, may be a useful adjunct to preventive measures in certain situations. After an index immediate drug hypersensitivity reaction, prescreening may be useful in perioperative anaphylaxis, and iodinated (ICM) and gadolinium-based contrast media (GCM) where the culprit and potential alternative agents are skin tested. In certain nonimmediate DHR, pharmacogenomic prescreening may be used before prescribing high-risk drugs (eg, carbamazepine and allopurinol) where specific human-leukocyte antigen genotypes are associated with severe cutaneous adverse reactions. Premedication with antihistamine and systemic corticosteroids is another therapeutic strategy to prevent infusion reactions for certain biologicals and chemotherapeutic agents, in cases of perioperative anaphylaxis, ICM and GCM DHR, and clonal mast cell disorders. Rapid drug desensitization may also be used to induce temporary tolerance in situations where there are limited alternative drugs. ispartof: JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY-IN PRACTICE vol:9 issue:8 pages:2958-2966 ispartof: location:United States status: published

The response rate of most anti-cancer drugs is limited because of the high heterogeneity of cancer and the complex mechanism of drug action. Personalized treatment that stratifies patients into subgroups using molecular biomarkers is promising to improve clinical benefit. With the accumulation of preclinical models and advances in computational approaches of drug response prediction, pharmacogenomics has made great success over the last 20 years and is increasingly used in the clinical practice of personalized cancer medicine. In this article, we first summarize FDA-approved pharmacogenomic biomarkers and large-scale pharmacogenomic studies of preclinical cancer models such as patient-derived cell lines, organoids, and xenografts. Furthermore, we comprehensively review the recent developments of computational methods in drug response prediction, covering network, machine learning, and deep learning technologies and strategies to evaluate immunotherapy response. In the end, we discuss challenges and propose possible solutions for further improvement.

Functional studies of long noncoding RNAs (lncRNAs) are often performed in the context of only a single cancer type. However, the tissue-specific expression patterns of lncRNAs raise the question of whether lncRNA associations identified in one cancer type are relevant to other cancer types. Here, we examine the relationships between the expression levels of 50 cancer-related lncRNAs and survival data from 24 types of cancer in The Cancer Genome Atlas (TCGA) with the goal of identifying prognosis related lncRNAs. Our results suggest that high expression levels of certain lncRNAs are consistently associated with worse/better survival in a number of cancers, while other lncRNAs have different prognostic roles in different types of cancer. Our analysis also identifies 20 novel unadjusted associations that have not been reported before. In addition, in low-grade glioma (LGG), prognostic-related lncRNAs are identified after conditioning on known clinical biomarker and common therapy, revealing that 2 lncRNAs, FOXP4-AS1, and NEAT1, are associated with temozolomide response-a standard-of-care in LGG. Pathway analysis suggests NF-kB/STAT3 signaling pathway enrichment in LGG patients with high NEAT1 expression and DNA repair/myc gene set enrichment in LGG patients with high expression of FOXP4-AS1. Our work demonstrates the context dependency of lncRNAs across cancer types and highlights a number of lncRNAs as potential novel cancer prognosis markers.

RESUMEN El presente artículo es el resultado de una investigación, desde las perspectivas bioética y biojurídica, acerca de los lineamientos existentes en Colombia para el manejo de las pruebas farmacogenómicas y farmacogenéticas en los ensayos clínicos. La revisión de la legislación existente en nuestro medio se comparó con estándares internacionales y los propuestos por organismos supranacionales. Se encontró que en Colombia falta una regulación específica en esta área, lo que expone a una serie de riesgos bioéticos y jurídicos a los participantes e investigadores. No se deben subestimar estos riesgos, pues comprometen la viabilidad ética de la investigación clínica y básica en nuestro medio. Al final, desde la perspectiva de la ética de los principios, se proponen una serie de acciones para la creación y la promoción a escala nacional de lineamientos que sirvan para conformar una legislación aplicable a la protección de los datos genéticos y, por ende, los derechos de los sujetos que participan en esta clase de estudios de investigación en Colombia. ABSTRACT This paper is the result of research, from the bioethics and bio-legal perspectives, on the existing guidelines in Colombia for the handling of pharmacogenomic and pharmacogenetic tests in clinical trials. Colombian legislation on this kind of research was reviewed and then compared with international and supranational standards. It was found that Colombia lacks specific legislation in this area, a situation that puts both participants and researchers at risk, from bioethical and legal perspectives. These risks should not be underestimated, as they compromise the ethical viability of clinical and basic research in our setting. In the end, a proposal, based on principles of ethics is made, proposing a series of actions for the creation and promotion nationwide of guidelines which can be used to shape legislation to be applied to protect the genetic data and the rights of subjects participating in these types of research studies in Colombia.

Antiemetic prophylaxis for postoperative nausea and vomiting (PONV) - a frequent complication in the postoperative period - is routinely given to high-risk patients. However, standard PONV risk models do not account for genetic factors, which have been shown to have a significant influence on PONV incidence and drug response. In this review, we describe the polymorphisms of various genes (serotonin, dopamine, cholinergic, etc.) and how pharmacogenomics is involved in the pathophysiology of PONV. This review also addresses how genetics is involved in today's clinical practice related to PONV and how it will change in the upcoming years as personalized medicine advances.

To cater to medication needs in the future healthcare system, we need to shift from the conventional system of drug delivery to modern molecular signature-based drug delivery systems. The current drug therapies are either less effective, ineffective, or produce numerous adverse reactions. One scientific principle or discipline cannot adequately address all the problems, so we need an innovative application of the current scientific principles. Here we are proposing a novel concept of nanoformulation based on pharmacogenomics and theranostics for personalized error-free and targeted therapeutic agent delivery. The addition of more knowledge about the human genome opens the new way to study disease-gene, gene-drug, and drug-effect interactions, which is the basis of future medicines. Pharmacogenomics provides information about the disease etiology, role in genes in disease pathophysiology, disease biomarkers, drug targets, drug effects, and the fate of drugs inside the body. Theranostics approach utilizes the above information in diagnosis, treatment, and monitoring of the disease on a real-time basis. Personalized dosage forms can be formulated into a nanoformulation that provides a better therapeutic effect and minimizes adverse drug reactions. The therapeutic system needs to be shifted from the principle of one drug fits all to one drug unique population. In the present manuscript, we tried to conceptualize a modern therapeutic system by combining the three approaches viz. pharmacogenomics, theranostics, and nanotechnology applied in the area of formulation development to produce a multifunctional single tiny entity.

Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B∗55:01 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10-31) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10-47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B∗55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.

Drug development, from preclinical to clinical studies, is a lengthy and complex process. There is an increased interest in the Kingdom of Saudi Arabia (KSA) to promote innovation, research and local content including clinical trials (Phase I-IV). Currently, there are over 650 registered clinical trials in Saudi Arabia, and this number is expected to increase. An important part of drug development and clinical trials is to assure the safe and effective use of drugs. Clinical pharmacology plays a vital role in informed decision making during the drug development stage as it focuses on the effects of drugs in humans. Disciplines such as pharmacokinetics, pharmacodynamics and pharmacogenomics are components of clinical pharmacology. It is a growing discipline with a range of applications in all phases of drug development, including selecting optimal doses for Phase I, II and III studies, evaluating bioequivalence and biosimilar studies and designing clinical studies. Incorporating clinical pharmacology in research as well as in the requirements of regulatory agencies will improve the drug development process and accelerate the pipeline. Clinical pharmacology is also applied in direct patient care with the goal of personalizing treatment. Tools such as therapeutic drug monitoring, pharmacogenomics and model informed precision dosing are used to optimize dosing for patients at an individual level. In KSA, the science of clinical pharmacology is underutilized and we believe it is important to raise awareness and educate the scientific community and healthcare professionals in terms of its applications and potential. In this review paper, we provide an overview on the use and applications of clinical pharmacology in both drug development and clinical care.

In this review, we summarize recent published work interrogating the relationship between genetic variation or gene expression regulation across the genome and asthma or asthma treatment outcomes. This includes 11 genome-wide association studies of asthma phenotypes that collectively identified 64 novel loci; transcriptome-wide asthma association studies which identified genes involved in virus recognition, bacterial infection, lung tissue remodeling, eosinophilic and neutrophilic inflammation and genes in the chromosome 17q12 asthma susceptibility locus; and three epigenome-wide studies of asthma that had robust sample sizes and replicated findings. We also highlight pharmacogenomic studies of corticosteroids, bronchodilator response to albuterol and zileuton, although finding from these studies may still be preliminary due to their relatively small sample sizes and limited availability of replication cohorts.

Pharmacogenomics is the study of how genetic differences between individuals affect pharmacokinetics and pharmacodynamics. These differences are apparent to clinicians when taking into account the wide range of responses to medications given in clinical practice. A review of literature involving pharmacogenomics and pain management was performed. The implementation of preoperative pharmacogenomics will allow us to better care for our patients by delivering personalized, safer medicine. This review describes the current state of pharmacogenomics as it relates to many aspects of clinical practice and how clinicians can use these tools to improve patient outcomes.

The goal of the Association for Molecular Pathology (AMP) Clinical Practice Committee's AMP Pharmacogenomics (PGx) Working Group is to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The AMP PGx Working Group considered functional impact of the variants, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations for PGx testing when developing these recommendations. The ultimate goal is to promote standardization of PGx gene/allele testing across clinical laboratories. These recommendations are not to be interpreted as prescriptive but to provide a reference guide. Of note, a separate article with recommendations for CYP2C9 allele selection was previously developed by the PGx Working Group that can be applied broadly to CYP2C9-related medications. The warfarin allele recommendations in this report incorporate the previous CYP2C9 allele recommendations and additional genes and alleles that are specific to warfarin testing.

Purpose To examine the evidence on the cost-effectiveness of implementing pharmacogenomics (PGx) in cardiovascular disease (CVD) care. Methods We conducted a systematic review using multiple databases from inception to 2018. The titles and abstracts of cost-effectiveness studies on PGx-guided treatment in CVD care were screened, and full texts were extracted. Results We screened 909 studies and included 46 to synthesize. Acute coronary syndrome and atrial fibrillation were the predominantly studied conditions (59%). Most studies (78%) examined warfarin–CYP2C9/VKORC1 or clopidogrel–CYP2C19. A payer’s perspective was commonly used (39%) for cost calculations, and most studies (46%) were US-based. The majority (67%) of the studies found PGx testing to be cost-effective in CVD care, but cost-effectiveness varied across drugs and conditions. Two studies examined PGx panel testing, of which one examined pre-emptive testing strategies. Conclusion We found mixed evidence on the cost-effectiveness of PGx in CVD care. Supportive evidence exists for clopidogrel–CYP2C19 and warfarin–CYP2C9/VKORC1, but evidence is limited in other drug–gene combinations. Gaps persist, including unclear explanation of perspective and cost inputs, underreporting of study design elements critical to economic evaluations, and limited examination of PGx panel and pre-emptive testing for their cost-effectiveness. This review identifies the need for further research on economic evaluations of PGx implementation.

The purpose of the present study was to investigate the impact of genetic polymorphism on fluvastatin pharmacokinetics. In addition, we compared the fluvastatin pharmacokinetics differences between extended-release (ER) 80 mg tablet and immediate-release (IR) 40 mg capsule in terms of drug metabolism enzyme and transporter genetic polymorphisms. In this open-label, randomized, two-period, two-treatment, crossover study (n = 24), effects of ABCG2, SLCO1B1, ABCB1, CYP2C9 and CYP3A5 polymorphisms on the pharmacokinetics of fluvastatin were analyzed. The administration dosage for IR 40 mg and ER 80 mg were twice and once daily, respectively, for total 7 d. Blood samples for pharmacokinetic evaluation were taken on the 1st and 7th d. The lower exposure following ER was observed. For ER tablets, SLCO1B1 T521C genotype correlated with AUC0-24 of repeat doses (P = 0.010). SLCO1B1 T521C genotype had no statistically significant effect on AUC0-24 of IR capsule of fluvastatin after single or repeated doses. In vitro study demonstrated that when the concentration of fluvastatin was low (< 1 µmol/l), the uptake of fluvastatin in the HEK293-OATP1B1 with SLCO1B1 521TT (Km=0.18 µmol/l) was faster than that with SLCO1B1 521CC (Km=0.49 µmol/l), On the other hand, when concentration reached to higher level (> 1 µmol/l), transport velocity of fluvastatin by HEK293-OATP1B1 with SLCO1B1 521TT (Km = 11.4 µmol/l) and with SLCO1B1 521TCC (Km=15.1 µmol/l) tend to be the same. It suggests that the increased effect of SLCO1B1 T521C genotype on ER formulation of fluvastatin was mainly caused by lower blood concentrations. We recommend that formulation should be incorporated into future pharmacogenomics studies., Graphical abstract Image, graphical abstract

Drug reactions and interactions are common with opioids. Opioids are often dosed based on clinical indication, patient presentation, and subjective pain scores, resulting in a trial-and-error approach to dosage. Based on the patient’s phenotype, the response to the opioid therapy could range from toxicity and overdose to inadequate control of pain. In patients with genetic opioid metabolism defects, prescribing medications that bypass the cytochrome P450 system can be helpful. Considering pharmacogenetic principles is recommended when prescribing opioids to practice more safely and effectively leading to improved pain, reduced health care costs, and higher patient satisfaction.

Pharmacogenomics (PGx) is the study of how individuals' personal genotypes may affect their responses to various pharmacologic agents. The application of PGx principles in perioperative medicine is fairly novel. Challenges in executing PGx programs into health care systems include physician buy-in and integration into usual clinical workflow, including the electronic health record. This article discusses the current evidence highlighting the potential of PGx with various drug categories (including opioids, nonopioid analgesics, sedatives, β-blockers, antiemetics, and anticoagulants) used in the perioperative process and the challenges of integrating PGx into a health care system and relevant workflows.

Cancer treatments become more effective now. One cause of these therapeutic promotions is based on drug selective paradigms in the clinic. A small range of drug selective paradigms (pharmacogenomics, precision-oncology, biomarkers and drug sensitivity testing) have been widely used worldwide. To accelerate the performance of these drug selective strategies, improved understanding of different mechanisms may be useful. Among these four classes of selective systems, drug sensitivity testing (DST) plays a unique role in clinical trials. Biomedical advances of knowledge and technology in current drug selective systems are increasingly importance. In the past two decades, knowledge gap between pathology and therapeutics is gradually filling, especially among different predictive mechanisms. The different drug selective systems are competitive, progress and advantageous in different clinical situations. To face with this diversity of drug selective strategies, guiding principle and technical feasibility need to emphasize. As a powerful platform, DST have some unique characters—high-quality quantification and comparison of responses among anticancer drug of interests. The smooth progress of DST platform depends on increasingly understanding of cancer biology, pathology and pharmacology—including medical knowledge (cancer heterogeneity, plasticity, stem cells and metastasis) and technical versatility (micro-fluidity and apoptotic evaluation). The medical and technical insights into various and uniqueness of DST are especially highlighted in this article.

Graphical abstract, In recent decades the identification of pharmacogenomic gene-drug associations has evolved tremendously. Despite this progress, a major fraction of the heritable inter-individual variability remains elusive. Higher-dimensional phenomena, such as gene-gene-drug interactions, in which variability in multiple genes synergizes to precipitate an observable phenotype have been suggested to account at least for part of this missing heritability. However, the identification of such intricate relationships remains difficult partly because of analytical challenges associated with the complexity explosion of the problem. To facilitate the identification of such combinatorial pharmacogenetic associations, we here propose a network analysis strategy. Specifically, we analyzed the landscape of drug metabolizing enzymes and transporters for 100 top selling drugs as well as all compounds with pharmacogenetic germline labels or dosing guidelines. Based on this data, we calculated the posterior probabilities that gene i is involved in metabolism, transport or toxicity of a given drug under the condition that another gene j is involved for all pharmacogene pairs (i, j). Interestingly, these analyses revealed significant patterns between individual genes and across pharmacogene families that provide insights into metabolic interactions. To visualize the gene-drug interaction landscape, we use multidimensional scaling to collapse this similarity matrix into a two-dimensional network. We suggest that Euclidian distance between nodes can inform about the likelihood of epistatic interactions and thus might provide a useful tool to reduce the search space and facilitate the identification of combinatorial pharmacogenomic associations.

Opioid use disorder (OUD) constitutes a significant public health burden as opioid overdose deaths have continued to rise in the United States. Although treatment modalities are available to manage OUD, some patients experience challenges achieving their OUD management goals. Some of these challenges may be attributable to inherited genetic variations, or polymorphisms, on the genes that code for proteins impacting the pharmacokinetics or pharmacodynamics of medications used in OUD management. Clinical pharmacogenomics testing can elucidate these polymorphisms; however, a lack of real-world evidence for the use of pharmacogenomics in OUD management complicates the implementation process. We conducted a retrospective cohort study of 113 patients undergoing buprenorphine-based OUD management in Northeast Washington D.C. to determine if clinical pharmacogenomics testing for CYP3A4 and CYP3A5 would impact treatment outcomes. Data were collected from the electronic medical record (EMR) from December 30, 2015 to December 31, 2016. Study outcomes were based on presence of withdrawal symptoms, instances of unauthorized substances in urine drug tests (UDTs), and sublingual buprenorphine/naloxone (SBN) dose with standard-of-care (SOC) dosing versus pharmacogenomics (PGx)-based dosing. Pearson correlation tests, Wilcoxon signed rank tests, Wilcoxon rank sum tests, and one-way ANOVA tests were used. Linear and logistic regression analyses were used to assess predictors of withdrawal symptomatology. Kaplan-Meier survival analyses were used to assess time to first withdrawal. Our research suggests that patients with at least one copy of the CYP3A4*1B allele exhibit an accelerated rate of metabolism compared to the wild-type allele CYP3A4*1.

Pharmacogenomics (PGx) is a powerful tool that can predict increased risks of adverse effects and sub-therapeutic response to medications. This article establishes the core principles necessary for a primary care provider to meaningfully and prudently use PGx testing. Key topics include in which patients PGx testing should be considered, how PGx tests are ordered, how the results are translated into clinical recommendations, and what further advancements are likely in the near future. This will provide clinicians with a foundational knowledge of PGx that can allow incorporation of this tool into their practice or support further personal investigation.

Cystic fibrosis (CF) is a life-shortening genetic disease caused by mutations of CFTR, the gene encoding cystic fibrosis transmembrane conductance regulator. Despite considerable progress in CF therapies, targeting specific CFTR genotypes based on small molecules has been hindered because of the substantial genetic heterogeneity of CFTR mutations in patients with CF, which is difficult to assess by animal models in vivo. There are broadly four classes (e.g., II, III, and IV) of CF genotypes that differentially respond to current CF drugs (e.g., VX-770 and VX-809). In this review, we shed light on the pharmacogenomics of diverse CFTR mutations and the emerging role of stem cell-based organoids in predicting the CF drug response. We discuss mechanisms that underlie differential CF drug responses both in organoid-based assays and in CF clinical trials, thereby facilitating the precision design of safer and more effective therapies for individual patients with CF.

Objective To explore the implications of direct-to-consumer pharmacogenomic testing for community pharmacy practice. Summary In October 2018, the U.S. Food and Drug Administration provided approval for direct-to-consumer genetic testing company, 23andMe (Mountain View, CA), to return select pharmacogenomic test results to their customers. Given the community pharmacist’s high accessibility to the public and in-depth knowledge of pharmacology, and the availability of direct-to-consumer genetic testing kits at pharmacies, it is likely that patients will present their pharmacogenomic test results to their pharmacists and expect them to incorporate those results into their care. It is important, therefore, that community pharmacists are aware of the clinical implications of these results, know where to turn for evidence-based clinical pharmacogenomics information, and be mindful of the need for confirmatory testing before changing therapy. Conclusion Community pharmacists are at the frontlines of health care, and as such will be at the frontlines of direct-to-consumer pharmacogenomic testing. In the near future, it is likely that community pharmacists will need to counsel patients on the interpretation and appropriate use of direct-to-consumer pharmacogenomic test results.

Cancer cells generally harbor hundreds of alterations in the cancer genomes and act as crucial factors in the development and progression of cancer. Gene alterations in the cancer genome form genetic interactions, which affect the response of patients to drugs. We developed an algorithm that mines copy number alteration and whole-exome mutation profiles from The Cancer Genome Atlas (TCGA), as well as functional screen data generated to identify potential genetic interactions for specific cancer types. As a result, 4,529 synthetic viability (SV) interactions and 10,637 synthetic lethality (SL) interactions were detected. The pharmacogenomic datasets revealed that SV interactions induced drug resistance in cancer cells and that SL interactions mediated drug sensitivity in cancer cells. Deletions of HDAC1 and DVL1, both of which participate in the Notch signaling pathway, had an SV effect in cancer cells, and deletion of DVL1 induced resistance to HDAC1 inhibitors in cancer cells. In addition, patients with low expression of both HDAC1 and DVL1 had poor prognosis. Finally, by integrating current reported genetic interactions from other studies, the Cancer Genetic Interaction database (CGIdb) (http://www.medsysbio.org/CGIdb) was constructed, providing a convenient retrieval for genetic interactions in cancer. Keywords: synthetic viability, synthetic lethality, drug resistance, drug sensitivity, biomarker

The goals of the Association for Molecular Pathology Pharmacogenomics (PGx) Working Group of the Association for Molecular Pathology Clinical Practice Committee are to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document provides recommendations for a minimum panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories when designing assays for CYP2C9 testing. The Working Group considered the functional impact of the variants, allele frequencies in different populations and ethnicities, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. Our goal is to promote standardization of testing PGx genes and alleles across clinical laboratories. These recommendations are not to be interpreted as restrictive but to provide a reference guide. The current document will focus on CYP2C9 testing that can be applied to all CYP2C9-related medications. A separate recommendation on warfarin PGx testing is being developed to include recommendations on CYP2C9 alleles and additional warfarin sensitivity–associated genes and alleles.

PurposeTo compare patient/tumor characteristics and outcomes of Asians to Caucasian patients with epithelial ovarian cancer.MethodsAncillary data were pooled and analyzed from ten prospective randomized front-line Gynecologic Oncology Group clinical trials from 1996 to 2011. Demographic, clinicopathologic features, disease-specific and all-cause survival were analyzed.ResultsOf 7914 patients, 7641 were Caucasian and 273 Asian. When compared to Caucasians, Asians were younger at trial enrollment, had a better performance status, earlier-stage cancers (17.2% vs. 8.1% with stage I; p

Precision medicine seeks to improve health care by individualizing treatment based on a person’s genetic predispositions, lifestyle, and environment. While this approach holds great promise for improving health care, its potential relevance to population health disparities is not clear. Pediatric acute lymphoblastic leukemia provides an example to illustrate the complexity of the issue. African American (AA) children have a lower incidence of acute lymphoblastic leukemia (ALL), due in part to a lower prevalence of gene variants associated with risk, but experience higher relapse rates than European American (EA) children after treatment. AA children are also more likely to present with poor prognostic indicators at the time of diagnosis. Numerous environmental exposures have been associated with ALL risk, but effect sizes are small and studies are lacking to assess whether differential exposure could account for the observed racial disparities. Gene variants associated with treatment response can partially account for higher relapse rates in AA children. This finding could reflect the optimization of current chemotherapy regimens in predominantly EA populations. Importantly, the higher relapse rate seen for AA children in national data was not observed in a care setting that included elimination of out of pocket costs, risk-directed therapy based on stringent risk stratification, and rigorous case management. The ALL example illustrates the importance of social factors in addressing health disparities, including access to effective treatment and inclusion of diverse populations in research, but also points to important ways in which precision health research can help to illuminate disease processes and contribute to improving effective treatment for all patients.

Three important factors, including genetics, environment factors and autoimmunity play a role in the pathogenesis of rheumatoid arthritis (RA). The heritability of RA has been accounted to be 50-60%, while the HLA involvement in heritability of the disease has been accounted to be 10-40%. It has been documented that shared epitope (SE) alleles, such as HLA-DRB1*01 and DRB1*04, some HLA alleles like HLA-DRB1*13 and DRB1*15 are connected to RA susceptibility. An advanced classification of SE categorizes SE alleles into four main groups namely, S1, S2, S3D, and S3P. The S2 and S3P groups have been linked to susceptibility of seropositive RA. Various genome-wide association studies (GWAS) have discovered many susceptibility loci implicated in pathogenesis of RA. Some of the important single nucleotide polymorphisms (SNPs) linked to RA are TRAF1, STAT4, CTLA4, IRF5, CCR6, PTPN22, IL23R, and PADI4. HLA and non-HLA genes may discriminate anti-cyclic citrullinated peptide (anti-CCP) antibody-positive and anti-CCP-negative RA groups. Furthermore, risk of the disease has also been linked to environmental agents, mainly cigarette smoking. Pharmacogenomics has also confirmed SNPs or genetic patterns that might be linked to drugs responses. Different aspects of genetic involvement in the pathogenesis, etiology, and RA complications are reviewed in this article.

Introduction This study was designed to assess the depth, breadth, and perception of pharmacogenomics education in pharmacy curricula in the United States (US). Methods A modified, online questionnaire from previous studies was sent to all accredited US schools and colleges of pharmacy. The survey covered three distinct areas related to the schools' educational environments, the depth and the extent of pharmacogenomics core competencies and topics taught, and the institutions' perceptions of the importance of pharmacogenomics in the curriculum and future plans for expanded pharmacogenomics education. Multiple approaches were used to increase the response rate, and results were analyzed using descriptive statistics. Results Of the 133 eligible programs, 32 participated in the survey. Six invalid surveys were excluded from our study, resulting in a 19.6% response rate. Results revealed that all responding schools included pharmacogenomics in the curriculum. Interestingly, 76.9% of the respondents believed pharmacists do not have the appropriate knowledge of pharmacogenomics. However, only 30.7% indicated that their programs planned to expand pharmacogenomics in their curriculum. Conclusions The responding schools all included some pharmacogenomics in their curriculum. However, the depth and the extent of pharmacogenomics topics covered varied. Respondents perceived that pharmacists today do not possess the appropriate level of pharmacogenomics knowledge. Despite this, there is limited emphasis on expanding pharmacogenomics instruction in the responding schools' curriculums.

Preemptive pharmacogenetic testing aims to optimize medication use by having genetic information at the point of prescribing. Payers’ decisions influence implementation of this technology. We investigated US payers’ knowledge, awareness, and perspectives on preemptive pharmacogenetic testing. A qualitative study was conducted using semistructured interviews. Participants were screened for eligibility through an online survey. A blended inductive and deductive approach was used to analyze the transcripts. Two authors conducted an iterative reading process to code and categorize the data. Medical or pharmacy directors from 14 payer organizations covering 122 million US lives were interviewed. Three concept domains and ten dimensions were developed. Key findings include clinical utility concerns and limited exposure to preemptive germ-line testing, continued preference for outcomes from randomized controlled trials, interest in guideline development, importance of demonstrating an impact on clinical decision making, concerns of downstream costs and benefit predictability, and the impact of public stakeholders such as the Food and Drug Administration and Centers for Medicare and Medicaid Services. Both barriers and potential facilitators exist to developing cohesive reimbursement policy for pharmacogenetics, and there are unique challenges for the preemptive testing model. Prospective outcome studies, more precisely defining target populations, and predictive economic models are important considerations for future research.

Individuals differ substantially in their response to pharmacological treatment. Personalized medicine aspires to embrace these inter-individual differences and customize therapy by taking a wealth of patient-specific data into account. Pharmacogenomic constitutes a cornerstone of personalized medicine that provides therapeutic guidance based on the genomic profile of a given patient. Pharmacogenomics already has applications in the clinics, particularly in oncology, whereas future development in this area is needed in order to establish pharmacogenomic biomarkers as useful clinical tools. In this review we present an updated overview of current and emerging pharmacogenomic biomarkers in different therapeutic areas and critically discuss their potential to transform clinical care. Furthermore, we discuss opportunities of technological, methodological and institutional advances to improve biomarker discovery. We also summarize recent progress in our understanding of epigenetic effects on drug disposition and response, including a discussion of the only few pharmacogenomic biomarkers implemented into routine care. We anticipate, in part due to exciting rapid developments in Next Generation Sequencing technologies, machine learning methods and national biobanks, that the field will make great advances in the upcoming years towards unlocking the full potential of genomic data.

G protein-coupled receptors (GPCRs) are key membrane-embedded receptor proteins, with critical roles in cellular signal transduction. In the era of precision medicine, understanding the role of natural variants on GPCR function is critical, especially from a pharmacogenomics viewpoint. Studies involved in mapping variants to GPCR structures are briefly reviewed here. The endocannabinoid system involving the central nervous system (CNS), the human cannabinoid receptor 1 (CB1), is an important drug target and its variability has implications for disease susceptibility and altered drug and pain response. We have carried out a computational study to map deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) to CB1. CB1 mutations were computationally evaluated from neutral to deleterious, and the top twelve deleterious mutations, with structural information, were found to be either close to the ligand binding region or the G-protein binding site. We have mapped these to the active and inactive CB1 X-ray crystallographic structures to correlate variants with available phenotypic information. We have also carried out molecular dynamics simulations to functionally characterize four selected mutants.

The inter-individual response to medications and the presence of genetic polymorphisms which impact the safe conduct of anaesthesia and analgesia are of paramount importance to the anaesthetist, intensivist and pain physician. The frequency of these phenomena is not reflected in the attention afforded them in undergraduate or postgraduate curricula. In order to appreciate how these issues may affect our clinical practice, it is crucial to have a working understanding of the concepts that underpin the relevant fields within the collection of disciplines we term the ‘omics’.