HLA-associated drug hypersensitivity and the prediction of adverse drug reactions

Adverse drug reactions are an important cause of morbidity and mortality and constitute the leading reason of drug withdrawal from the market. Besides classical reactions that are related to pharmacologic activity of the drug, some reactions are unpredictable, not dose dependent, and seem to occur in genetically predisposed individuals. The majority of this reaction is immunologically driven and they are referred to as hypersensitivity reactions. A growing number of studies provided evidences that specific HLA alleles increase the risk of developing hypersensitivity drug reactions. In this context, drug hypersensitivities that have more robust pharmacogenetic data include abacavir hypersensitivity syndrome and severe cutaneous adverse reactions induced by allopurinol and carbamazepine

Pharmacogenetics of hypersensitivity drug reactions

Adverse drug reactions are a significant cause of morbidity and mortality and represent a major burden on the healthcare system. Some of those reactions are immunologically mediated (hypersensitivity reactions) and can be clinically subdivided into two categories: immediate reactions (IgE-related) and delayed reactions (T-cell-mediated). Delayed hypersensitivity reactions include both systemic syndromes and organ-specific toxicities and can be triggered by a wide range of chemically diverse drugs. Recent studies have demonstrated a strong genetic association between human leukocyte antigen alleles and susceptibility to delayed drug hypersensitivity. Most notable examples include human leukocyte antigen (HLA)-B*57:01 allele and abacavir hypersensitivity syndrome or HLA-B*15:02 and HLA-B*58:01 alleles related to severe cutaneous reactions induced by carbamazepine and allopurinol, respectively. This review aims to explore our current understanding in the field of pharmacogenomics of HLA-associated drug hypersensitivities and its translation into clinical practice for predicting adverse drug reactions

Use of a mass consistent wind model to investigate areas of enhanced rainfall

International audienceGiven the considerable breadth of possibilities that crime and criminals evoke in cinema, there is no question of prioritizing a certain theme or approach. On this subject, it was possible to treat screen adaptations of important trials and crimes that shocked the public, to establish historical relationships and correlations between the criminality of one time period or one country and its current on-screen representation, or to concentrate on one or two films more in detail. Cinematographic representations of crime could interest any area of the human sciences (such as sociology, anthropology or psychology), but also film analysts and, of course, criminologists. From the beginning of cinema to the most recent releases, from statistical analysis to aesthetics, from the general to the particular, from one country to another, the variety of approaches and themes shows the potential of this subject

Modelling the influence of MDR1 polymorphism on digoxin pharmacokinetic parameters.

OBJECTIVES: Digoxin is a well-known probe for the activity of P-glycoprotein. The objective of this work was to apply different methods for covariate selection in non-linear mixed-effect models to study the relationship between the pharmacokinetic parameters of digoxin and the genotype for two major exons located on the multi-drug-resistance 1 (MDR1) gene coding for P-glycoprotein. METHODS: Thirty-two healthy volunteers were recruited in three pharmacokinetic drug interaction studies. The data after a single oral administration of digoxin alone were pooled. All subjects were genotyped for the MDR1 C3435T and G2677T/A genotypes. The concentration-time profile of digoxin was established using 12-16 blood samples taken between 15 min and 72 h after administration. We modelled the pharmacokinetics of digoxin using non-linear mixed-effect models. Parameter estimation was performed using the stochastic approximation EM method (SAEM). We used three methods to select the covariate model: selection from a full model using Wald tests, forward inclusion using the log-likelihood ratio test and model selection using the Bayesian Information Criterion. RESULTS: The three covariate inclusion methods led to the same final model. Carriers of two T alleles for the C3435T polymorphism in exon 26 of MDR1 had a lower apparent volume of distribution than carriers of a C allele. The only other covariate effect was a shorter absorption time-lag in women. CONCLUSION: The apparent volume of distribution of digoxin is lower in TT subjects, probably reflecting differences in bioavailability. Non-linear mixed-effect models can be useful for detecting the influence of covariates on pharmacokinetic parameters

Clustering and Alignment of Polymorphic Sequences for HLA-DRB1 Genotyping

Located on Chromosome 6p21, classical human leukocyte antigen genes are highly polymorphic. HLA alleles associate with a variety of phenotypes, such as narcolepsy, autoimmunity, as well as immunologic response to infectious disease. Moreover, high resolution genotyping of these loci is critical to achieving long-term survival of allogeneic transplants. Development of methods to obtain high resolution analysis of HLA genotypes will lead to improved understanding of how select alleles contribute to human health and disease risk. Genomic DNAs were obtained from a cohort of n = 383 subjects recruited as part of an Ulcerative Colitis study and analyzed for HLA-DRB1. HLA genotypes were determined using sequence specific oligonucleotide probes and by next-generation sequencing using the Roche/454 GSFLX instrument. The Clustering and Alignment of Polymorphic Sequences (CAPSeq) software application was developed to analyze next-generation sequencing data. The application generates HLA sequence specific 6-digit genotype information from next-generation sequencing data using MUMmer to align sequences and the R package diffusionMap to classify sequences into their respective allelic groups. The incorporation of Bootstrap Aggregating, Bagging to aid in sorting of sequences into allele classes resulted in improved genotyping accuracy. Using Bagging iterations equal to 60, the genotyping results obtained using CAPSeq when compared with sequence specific oligonucleotide probe characterized 4-digit genotypes exhibited high rates of concordance, matching at 759 out of 766 (99.1%) alleles. © 2013 Ringquist et al

AAPS Workshop Report: Strategies to Address Therapeutic Protein–Drug Interactions during Clinical Development

Therapeutic proteins (TPs) are increasingly combined with small molecules and/or with other TPs. However preclinical tools and in vitro test systems for assessing drug interaction potential of TPs such as monoclonal antibodies, cytokines and cytokine modulators are limited. Published data suggests that clinically relevant TP-drug interactions (TP-DI) are likely from overlap in mechanisms of action, alteration in target and/or drug-disease interaction. Clinical drug interaction studies are not routinely conducted for TPs because of the logistical constraints in study design to address pharmacokinetic (PK)- and pharmacodynamic (PD)-based interactions. Different pharmaceutical companies have developed their respective question- and/or risk-based approaches for TP-DI based on the TP mechanism of action as well as patient population. During the workshop both company strategies and regulatory perspectives were discussed in depth using case studies; knowledge gaps and best practices were subsequently identified and discussed. Understanding the functional role of target, target expression and their downstream consequences were identified as important for assessing the potential for a TP-DI. Therefore, a question-and/or risk-based approach based upon the mechanism of action and patient population was proposed as a reasonable TP-DI strategy. This field continues to evolve as companies generate additional preclinical and clinical data to improve their understanding of possible mechanisms for drug interactions. Regulatory agencies are in the process of updating their recommendations to sponsors regarding the conduct of in vitro and in vivo interaction studies for new drug applications (NDAs) and biologics license applications (BLAs)

Special RepoRt Practical recommendations for pharmacogenomics- based prescription: 2010 ESF-UB Conference on Pharmacogenetics and Pharmacogenomics

medical practice Oncology drugs A full day was dedicated to oncology covering germline as well as tumor pharmacogenomics. Three major examples were discussed. Response to tyrosine kinase inhibitors owing to activating EGFR mutations in non-small-cell lung cancer Miguel A Molina from Instituto Universitario USP Dexeus, Barcelona, presented the results of a national survey indicating the usefulness of tumor EGFR pharmacogenomics in order to define tumors that will respond (owing to activating mutations) to EGF receptor (EGFR) antagonists (tyrosine kinase inhibitors) [1]. Additional recent publications have confirmed the usefulness of EGFR pharmacogenomics in non-small-cell lung cancer (NSCLC) [2,3]. Tumor samples can be obtained from tumor biopsies, possibly followed by laser microdissection -or circulating blood tumor cells. Activating mutations are observed in 15% of The present article summarizes the discussions of the 3rd European Science Foundation-University of Barcelona (ESF-UB) Conference in Biomedicine on Pharmacogenetics and Pharmacogenomics, which was held in June 2010 in Spain. It was focused on practical applications in routine medical practice. We provide practical recommendations for ten different clinical situations, that have either been approved or not approved by regulatory agencies. We propose some comments that might accompany the results of these tests, indicating the best drug and doses to be prescribed. The discussed examples include KRAS, cetuximab, panitumumab, EGFR-gefitinib, CYP2D6 -tamoxifen, TPMT-azathioprine -6-mercaptopurine, VKORC1/CYP2C9-warfarin, CYP2C19-clopidogrel, HLA-B*5701-abacavir, HLA-B*5701-flucloxacillin, SLCO1B1-statins and CYP3A5-tacrolimus. We hope that these practical recommendations will help physicians, biologists, scientists and other healthcare professionals to prescribe, perform and interpret these genetic tests. KEYWORDS: adverse drug reaction azathioprine cetuximab clopidogrel gefitinib genetic testing pharmacogenetics statins tacrolimus tamoxifen warfari