Systematic review of pharmacoeconomic studies of pharmacogenomic tests

There is currently a lack of consensus on the components that should be included in the pharmacoeconomic evaluation of pharmacogenomic tests. We conducted a systematic review focusing on pharmacogenomic tests to identify and comment on key parameters. The articles selected as economic analyses were classified using a framework including components related to testing, model, health outcomes, costs and incremental cost-effectiveness ratio. We found 15 studies that met our inclusion and exclusion criteria. A high degree of heterogeneity between evaluations was observed even within studies evaluating the same pharmacogenomic test. Components specific to pharmacogenomic tests were identified as marker prevalence, population ethnicity, pharmacogenomic treatment effect and cost of genomic data collection and analysis. In order to fully assess all aspects of pharmacogenomic testing, future pharmacoeconomic assessments should include every specific component that has an impact on the incremental cost-effectiveness ratio.     

Pharmacogenomic Biomarker Information in FDA‐approved Paediatric Drug Labels

Gene maturation differs between paediatric and adult populations, and the extrapolation of adult pharmacogenomic information to paediatrics is not always appropriate. We sought to determine the extent of paediatric pharmacogenomic trial translation into US FDA‐approved labels and to evaluate needs for biomarker studies. Using FDA's Table of Genomic Biomarkers and Drugs@FDA website, 38 pharmacogenomic biomarkers in 56 drug labels were identified with possible application in paediatrics. Of these 56 drugs, biomarker comparison against ‘Very Important Pharmacogenes (VIPs)’ defined in PharmGKB's database revealed a total of eight VIPs labelled among 41 drugs. One hundred and thirty‐nine product reviews posted on the FDA website under the Best Pharmaceuticals for Children Act and Paediatric Research Equity Act between October 2007 and July 2014 were examined. Review screening identified 43 drugs with ‘pharmacogenomic’ content, of which only three were true genotyping study reviews for proton pump inhibitors, all evaluating CYP2C19 polymorphisms. Pantoprazole was the sole drug labelled with pharmacogenomic information obtained specifically from paediatric trials. Clinicaltrials.gov was searched to further evaluate the current availability of pharmacogenomic studies in the paediatric population. Of the 33,132 trials registered on Clinicaltrials.gov, 137 were labelled as paediatric pharmacogenetic and pharmacogenomic studies. Pharmacogenomic studies directly conducted in paediatric patients are lacking, and thus, pharmacogenomic biomarker information based on adult studies is commonly presented in FDA‐approved labels for use in paediatric patients. Considering differences in gene expression and physiological maturation between paediatric and adult populations, studies investigating pharmacogenomic effects specifically in paediatric patients should be conducted whenever significant biomarkers are available.     

Hydrophobic dendrimer-derived nanoparticles

Lipidic polylysine dendrimers, synthesized using Fmoc solid phase peptide techniques, have been formulated as nanoparticles by precipitation from solution in dichloromethane. The effect of concentration on the diameter and stability of nanoparticles formed from two short homologous series of dendrimers--one fifth generation and one sixth generation series and with surface C4, C10 or C12 groups--was investigated using photon correlation spectroscopy. The increase in generation from fifth to sixth resulted in increased diameter for each chain length. An increase in the surface lipidic chain length from C4 to C12 had no effect on the particle diameter of aggregates derived from fifth generation dendrimers, and a small and variable effect on the sixth generation derived nanoparticles. Using pyrene (excitation 340 nm) as a hydrophobic fluorescent probe, a decrease in intensity peak I1 (374 nm)/I3 (385 nm) in the emission spectra (340-600 nm) was observed in the two dendrimers studied, fifth generation dendrimers with C10 or C12 surface lipidic chains, as the dendrimer concentration increased, reaching a plateau at higher concentrations, indicating that a more compact form of the aggregates with a more hydrophobic interior was obtained. Apart from the hydrophobicity of the dendrimers and dendrimer concentration, the flexibility of the dendrimers might have a significant effect in determining nanoparticle size. The aggregates derived from the fifth generation dendrimers with C10 or C12 surface lipidic chains are stable in purified intestinal fluid but not in purified stomach fluid, in which further aggregation of the nanoparticulate dendrimer aggregates occurs as an effect of pH, salts, proteins and enzymes in these fluids. This study demonstrates, inter alia, the importance of testing nanoparticulate delivery systems in relevant physiologically based fluids prior to their use in vivo.     

The Innovative Canadian Pharmacogenomic Screening Initiative in Community Pharmacy (ICANPIC) study

Objectives

The safety and efficacy of medications can vary significantly between patients as a result of genetic variability. As genomic screening technologies become more widely available, pharmacists are ideally suited to use such tools to optimize medication therapy management. The objective of this study was to evaluate the feasibility of implementing personalized medication services into community pharmacy practice and to assess the number of drug therapy problems identified as a result of pharmacogenomic screening.

Current status of researches in genomic medicine and the guidelines for pharmacogenomics (PGx)

Since the whole human genome sequence has become available, the methods to search for genes of diseases or drugs responses (traits) have changed dramatically. The former approach designated as "candidate gene approach" is now dominated by "genome-wide approach". In the former approach, researchers search for the genes based on the functions using biochemistry and molecular biology; however, in the latter approach, the genes are searched for by the genetic and statistical methods. Initially, monogenic diseases were the targets of the researches; however, polygenic diseases and drug responses have become the targets. Parametric linkage analysis was quite useful for identifying responsible genes for monogenic diseases. Genome-wide association study (GWAS) has been introduced for the identification of the genes for polygenic diseases and drug responses. GWAS was first introduced from 2002 to 2004 in Center for Genomic Medicine, RIKEN but has expanded rapidly to other countries including US, Europe and Asian countries from 2005. In Nature Genetics journal, about half of the articles published recently include the data from GWAS studies. Both qualitative and quantitative traits have been analyzed by GWAS. Qualitative traits include diseases and drug responses and quantitative traits include physical measures and clinical laboratory test values. Recent reports about the association between drug responses and genes have clarified many important pharmacogenomic associations. For these data to be analyzed efficiently and used appropriately; however, guidelines for researches and clinical tests concerning pharmacogenomics (PGx) are necessary. "Guideline for pharmacogenomic test" was issued in 2009 and, in addition, an extended guideline covering various fields is now being discussed.     

Temporal offset association between the number of irinotecan-related adverse reactions and pharmacogenomic studies: A cross-correlation analysis

ObjectivesStudies have proved that UGT1A1 (*6, *28 and *93) gene polymorphism was closely related to the side effects of irinotecan. This study intends to perform a correlation analysis on the relationship between pharmacogenomic studies and ADRs based on time series.MethodsThe ADRs related to irinotecan were derived through the FAERS; searched all pharmacogenomic studies in PubMed and Web of Science; then analyzed the sequence of correlation coefficients between total ADRs, fatal ADRs and pharmacogenomic studies under different time offset.ResultsThere is a positive correlation between the number of total ADRs and pharmacogenomic studies, of which the maximum correlation coefficient was 0.78 (95 % CI: 0.58–0.90), with a lag of 1 year. There is also a positive correlation between the number of fatal ADRs and pharmacogenomic studies, with the maximum correlation coefficient of 0.87 (95 % CI: 0.73–0.94) and a offset of ? 4 years.ConclusionIt was found that both the total ADRs and fatal ADRs were significantly positively correlated with change trend of published pharmacogenomic literatures, which confirmed the role of pharmacogenomic research in promoting the safe use of irinotecan, and have a faster response time in reducing fatal ADRs during clinical application.     

Lymphoblastoid cell lines in pharmacogenomic discovery and clinical translation

The ability to predict how an individual patient will respond to a particular treatment is the ambitious goal of personalized medicine. The genetic make up of an individual has been shown to play a role in drug response. For pharmacogenomic studies, human lymphoblastoid cell lines (LCLs) comprise a useful model system for identifying genetic variants associated with pharmacologic phenotypes. The availability of extensive genotype data for many panels of LCLs derived from individuals of diverse ancestry allows for the study of genetic variants contributing to interethnic and interindividual variation in susceptibility to drugs. Many genome-wide association studies for drug-induced phenotypes have been performed in LCLs, often incorporating gene-expression data. LCLs are also being used in follow-up studies to clinical findings to determine how an associated variant functions to affect phenotype. This review describes the most recent pharmacogenomic findings made in LCLs, including the translation of some findings to clinical cohorts.     

Antileukemic drug effects in childhood acute lymphoblastic leukemia

Cancer is the second most common cause of death in children between 1 and 15 years of age in industrialized countries. Although acute lymphoblastic leukemia (ALL) is still among the leading causes of death in childhood cancer, remarkable progress in treatment results has been made with this disease. With current antileukemic therapy, more than 80% of children with ALL can be cured. Antileukemic medications, however, are generally toxic and can cause significant adverse drug reactions. Moreover, some patients have leukemia cell clones that are resistant to conventional antileukemic treatment. Overall, a fifth of children with ALL will not be cured despite intensified therapy, including allogeneic stem cell transplantation. Pharmacogenomics aims to elucidate functionally relevant genomic determinants for drug disposition and response in order to establish valid pharmacogenomic models that can help to select medications and their dose based on a patient’s genetic make-up. This review focuses on investigations that provide important basic insights into ALL pharmacogenomics and/or hold great promise in providing clinically valuable pharmacogenomic models that can help to improve childhood ALL treatment by facilitating appropriate dose individualization, optimal treatment selection and drug discovery.     

Ethanol consumption and hepatic enzyme activity.

Enzyme activity and ethanol consumption were measured in an F2 generation derived from the C57BL and C3H inbred mouse strains. A significant correlation (0.25) was found between alcohol dehydrogenase activity and ethanol acceptance in the F2 generation. Mass selection from a genetically heterogenous mouse stock, HS/Ibg, has yielded high ethanol acceptance (HEA) and low ethanol acceptance (LEA) lines of mice. The mean ethanol acceptance scores for the fifth generation of these lines are 1.008 and 0.606, respectively. The total liver alcohol dehydrogenase activity was found to be 24% higher in the HEA line than in the LEA line after five generations of selective breeding. No association between cytosolic aldehyde dehydrogenase activity and ethanol acceptance was found in either the F2 generation or the fifth generation of the selectively bred lines.     

Implications of circadian gene expression in kidney, liver and the effects of fasting on pharmacogenomic studies.

Pharmacogenomics offers the potential to define metabolic pathways and to provide increased knowledge of drug actions. We studied relative levels of gene expression in the rat using a microarray with 8448 rat UniGenes (1928 known genes, 6520 unknown ESTs) in the liver and kidney as a function of time of day and then of feeding regime, which are common variables in preclinical pharmacogenomic studies. We identified 597 genes, including several key metabolic pathways, whose relative expression levels are significantly affected by time of day: expression of some was further modified by feeding state. These would have sparked interest in a pharmacogenomic study. Our study demonstrates that two common variables in pharmacogenomic studies can have dramatic effects on gene expression. This study provides investigators with baseline information for both kidney and liver with respect to 'normal' changes in gene expression influenced by time of day and feeding state. It also identifies 18 new genes that should be investigated for a role in circadian rhythms in peripheral tissues.     

Pharmacogenomics and drug development

It is generally anticipated that pharmacogenomic information will have a large impact on drug development and will facilitate individualized drug treatment. However, there has been relatively little quantitative modeling to assess how pharmacogenomic information could be best utilized in clinical practice. Using a quantitative model, this review demonstrates that efficacy is increased and toxicity is reduced when a genetically-guided dose adjustment strategy is utilized in a clinical trial. However, there is limited information available regarding the genetic variables affecting the disposition or mechanism of action of most commonly used medications. These genetic factors must be identified to enable pharmacogenomic testing to be routinely used in the clinic. A recently described murine haplotype-based computational genetic analysis method provides one strategy for identifying genetic factors regulating the pharmacokinetics and pharmacodynamics of commonly used medications.     

Pharmacogenomics of cardiovascular drugs and adverse effects in pediatrics

Individual response to medication is highly variable. For many drugs, a substantial proportion of patients show suboptimal response at standard doses, whereas others experience adverse drug reactions (ADRs). Pharmacogenomics aims to identify genetic factors underlying this variability in drug response, providing solutions to improve drug efficacy and safety. We review recent advances in pharmacogenomics of cardiovascular drugs and cardiovascular ADRs, including warfarin, clopidogrel, β-blockers, renin-angiotensin-aldosterone system inhibitors, drug-induced long QT syndrome, and anthracycline-induced cardiotoxicity. We particularly focus on the applicability of pharmacogenomic findings to pediatric patients in whom developmental changes in body size and organ function may affect drug pharmacokinetics and pharmacodynamics. Solid evidence supports the importance of gene variants in CYP2C9 and VKORC1 for warfarin dosing and in CYP2C19 for clopidogrel response in adult patients. For the other cardiovascular drugs or cardiovascular ADRs, further studies are needed to replicate or clarify genetic associations before considering uptake of pharmacogenetic testing in clinical practice. With the exception of warfarin and anthracycline-induced cardiotoxicity, there is lack of pharmacogenomic studies on cardiovascular drug response or ADRs aimed specifically at children or adolescents. The first pediatric warfarin pharmacogenomic study indeed indicates differences from adults, pointing out the importance and need for pediatric-focused pharmacogenomic studies.     

Grey-box Modelling of Pharmacokinetic /Pharmacodynamic Systems

Grey-box pharmacokinetic/pharmacodynamic (PK/PD) modelling is presented as a promising way of modelling PK/PD systems. The concept behind grey-box modelling is based on combining physiological knowledge along with information from data in the estimation of model parameters. Grey-box modelling consists of using stochastic differential equations (SDEs) where the stochastic term in the differential equations represents unknown or incorrectly modelled dynamics of the system. The methodology behind the grey-box PK/PD modelling framework for systematic model improvement is illustrated using simulated data and furthermore applied to Bergmans minimal model of glucose kinetics using clinical data from an intravenous glucose tolerance test (IVGTT). The grey-box estimates of the stochastic system noise parameters indicate that the glucose minimal model is too simple and should preferably be revised in order to describe the complicated in vivo system of insulin and glucose following an IVGTT.     

Mixed Effects Modeling Using Stochastic Differential Equations: Illustrated by Pharmacokinetic Data of Nicotinic Acid in Obese Zucker Rats

Inclusion of stochastic differential equations in mixed effects models provides means to quantify and distinguish three sources of variability in data. In addition to the two commonly encountered sources, measurement error and interindividual variability, we also consider uncertainty in the dynamical model itself. To this end, we extend the ordinary differential equation setting used in nonlinear mixed effects models to include stochastic differential equations. The approximate population likelihood is derived using the first-order conditional estimation with interaction method and extended Kalman filtering. To illustrate the application of the stochastic differential mixed effects model, two pharmacokinetic models are considered. First, we use a stochastic one-compartmental model with first-order input and nonlinear elimination to generate synthetic data in a simulated study. We show that by using the proposed method, the three sources of variability can be successfully separated. If the stochastic part is neglected, the parameter estimates become biased, and the measurement error variance is significantly overestimated. Second, we consider an extension to a stochastic pharmacokinetic model in a preclinical study of nicotinic acid kinetics in obese Zucker rats. The parameter estimates are compared between a deterministic and a stochastic NiAc disposition model, respectively. Discrepancies between model predictions and observations, previously described as measurement noise only, are now separated into a comparatively lower level of measurement noise and a significant uncertainty in model dynamics. These examples demonstrate that stochastic differential mixed effects models are useful tools for identifying incomplete or inaccurate model dynamics and for reducing potential bias in parameter estimates due to such model deficiencies.KEY WORDS: extended Kalman filter, model uncertainty, nonlinear kinetics, parameter estimation, state prediction     

Clinical applications of pharmacogenomics guided warfarin dosing

Aim of the Review To assess the state of the literature concerning pharmacogenomic testing in patients requiring vitamin K antagonists, specifically warfarin. Method We conducted a literature search of MEDLINE and International Pharmaceutical Abstracts using the following words: warfarin, pharmacogenetic, and pharmacogenomic. The search results were reviewed by the authors and papers concerning pharmacogenomic testing in warfarin dosing were procured and reviewed. Additionally bibliographies of papers procured were also examined for other studies. The authors focused on clinical trials concerning the use of pharmacogenomic testing in warfarin dosing. Results Although numerous studies have demonstrated that a significant portion of warfarin dosing variability can be explained by genetic polymorphisms, few prospective studies have been conducted that examine the integration of this information in practical dosing situations. Those that have, have shown that using pharmacogenomic information improves initial dosing estimates and decreases the need for frequent clinic visits and laboratory testing. Data showing a reduction in serious bleeding events is sparse. Cost-effectiveness analyses have generally shown a small but positive effect with pharmacogenomic testing in patients receiving warfarin. Conclusion Several studies have shown that pharmacogenomic testing for warfarin dosing is more accurate that other dosing schemes. Pharmacogenomic testing improves time to a therapeutic international normalized ratio while requiring fewer dosing adjustments. Patients who require higher or lower than usual doses seem to benefit the most. The cost-effectiveness of pharmacogenomic testing as well as preventing of outcomes such as bleeding or thrombosis are not yet elucidated. Pharmacists, especially those in a community setting can play a role in this new technology by educating prescribers and patients concerning pharmacogenomic testing, and by developing and using dosing protocols that incorporate its use.     

Clinical pharmacogenomics of warfarin and clopidogrel

Genetic polymorphisms significantly influence responses to warfarin and clopidogrel. Polymorphisms in the cytochrome P450 (CYP) 2C9 and vitamin K epoxide reductase genes change warfarin pharmacokinetics and pharmacodynamics, respectively. Because these polymorphisms influence warfarin dose requirements, they may primarily help determine therapeutic warfarin doses in patients who newly start on the drug. To assist in estimating therapeutic warfarin doses, the warfarin label provides a pharmacogenomic dosing table and various warfarin pharmacogenomic dosing algorithms are available. On the other hand, polymorphisms in the CYP2C19 gene affect clopidogrel pharmacokinetics. These polymorphisms may be useful to identify clopidogrel nonresponders who may benefit from taking an alternative antiplatelet agent such as prasugrel and ticagrelor. Although both drugs have pharmacogenomic tests available for clinical use, their clinical utilities have not been established and are currently being actively studied. In this review, clinical application of warfarin and clopidogrel pharmacogenomics will be focused. With the current level of evidence, potential patients who may get benefit from warfarin and clopidogrel pharmacogenomic testing will be discussed. In addition, the interpretation of the warfarin and clopidogrel test results and the current barriers to widespread use of warfarin and clopidogrel pharmacogenomic testing will be discussed.