Drug-drug interaction studies of cardiovascular drugs involving P-glycoprotein, an efflux transporter, on the pharmacokinetics of edoxaban, an oral factor Xa inhibitor.

BACKGROUND: Edoxaban, an oral direct factor Xa inhibitor, is in development for thromboprophylaxis, including prevention of stroke and systemic embolism in patients with atrial fibrillation (AF). P-glycoprotein (P-gp), an efflux transporter, modulates absorption and excretion of xenobiotics. Edoxaban is a P-gp substrate, and several cardiovascular (CV) drugs have the potential to inhibit P-gp and increase drug exposure. OBJECTIVE: To assess the potential pharmacokinetic interactions of edoxaban and 6 cardiovascular drugs used in the management of AF and known P-gp substrates/inhibitors. METHODS: Drug-drug interaction studies with edoxaban and CV drugs with known P-gp substrate/inhibitor potential were conducted in healthy subjects. In 4 crossover, 2-period, 2-treatment studies, subjects received edoxaban 60 mg alone and coadministered with quinidine 300 mg (n = 42), verapamil 240 mg (n = 34), atorvastatin 80 mg (n = 32), or dronedarone 400 mg (n = 34). Additionally, edoxaban 60 mg alone and coadministered with amiodarone 400 mg (n = 30) or digoxin 0.25 mg (n = 48) was evaluated in a single-sequence study and 2-cohort study, respectively. RESULTS: Edoxaban exposure measured as area under the curve increased for concomitant administration of edoxaban with quinidine (76.7 %), verapamil (52.7 %), amiodarone (39.8 %), and dronedarone (84.5 %), and exposure measured as 24-h concentrations for quinidine (11.8 %), verapamil (29.1 %), and dronedarone (157.6 %) also increased. Administration of edoxaban with amiodarone decreased the 24-h concentration for edoxaban by 25.7 %. Concomitant administration with digoxin or atorvastatin had minimal effects on edoxaban exposure. CONCLUSION: Coadministration of the P-gp inhibitors quinidine, verapamil, and dronedarone increased edoxaban exposure. Modest/minimal effects were observed for amiodarone, atorvastatin, and digoxin.

Differential scanning calorimetry in life science: thermodynamics, stability, molecular recognition and application in drug design

All biological phenomena depend on molecular recognition, which is either intermolecular like in ligand binding to a macromolecule or intramolecular like in protein folding. As a result, understanding the relationship between the structure of proteins and the energetics of their stability and binding with others (bio)molecules is a very interesting point in biochemistry and biotechnology. It is essential to the engineering of stable proteins and to the structure-based design of pharmaceutical ligands. The parameter generally used to characterize the stability of a system (the folded and unfolded state of the protein for example) is the equilibrium constant (K) or the free energy (deltaG(o)), which is the sum of enthalpic (deltaH(o)) and entropic (deltaS(o)) terms. These parameters are temperature dependent through the heat capacity change (deltaCp). The thermodynamic parameters deltaH(o) and deltaCp can be derived from spectroscopic experiments, using the van't Hoff method, or measured directly using calorimetry. Along with isothermal titration calorimetry (ITC), differential scanning calorimetry (DSC) is a powerful method, less described than ITC, for measuring directly the thermodynamic parameters which characterize biomolecules. In this article, we summarize the principal thermodynamics parameters, describe the DSC approach and review some systems to which it has been applied. DSC is much used for the study of the stability and the folding of biomolecules, but it can also be applied in order to understand biomolecular interactions and can thus be an interesting technique in the process of drug design.

Correlations between imatinib pharmacokinetics, pharmacodynamics, adherence, and clinical response in advanced metastatic gastrointestinal stromal tumor (GIST): An emerging role for drug blood level testing?

Imatinib is the standard of care for patients with advanced metastatic gastrointestinal stromal tumors (GIST), and is also approved for adjuvant treatment in patients at substantial risk of relapse. Studies have shown that maximizing benefit from imatinib depends on long-term administration at recommended doses. Pharmacokinetic (PK) and pharmacodynamic factors, adherence, and drug-drug interactions can affect exposure to imatinib and impact clinical outcomes. This article reviews the relevance of these factors to imatinib's clinical activity and response in the context of what has been demonstrated in chronic myelogenous leukemia (CML), and in light of new data correlating imatinib exposure to response in patients with GIST. Because of the wide inter-patient variability in drug exposure with imatinib in both CML and GIST, blood level testing (BLT) may play a role in investigating instances of suboptimal response, unusually severe toxicities, drug-drug interactions, and suspected non-adherence. Published clinical data in CML and in GIST were considered, including data from a PK substudy of the B2222 trial correlating imatinib blood levels with clinical responses in patients with GIST. Imatinib trough plasma levels <1100ng/mL were associated with lower rates of objective response and faster development of progressive disease in patients with GIST. These findings have been supported by other analyses correlating free imatinib (unbound) levels with response. These results suggest a future application for imatinib BLT in predicting and optimizing therapeutic response. Nevertheless, early estimates of threshold imatinib blood levels must be confirmed prospectively in future studies and elaborated for different patient subgroups.

Prédiction des impacts pharmacocinétiques des interactions médicamenteuses impliquant des CYP3A et les glycoprotéines-P : développement de modèles physiologiques et analyse de sensibilité

Les propriétés pharmacocinétiques d’un nouveau médicament et les risques d’interactions médicamenteuses doivent être investigués très tôt dans le processus de recherche et développement. L’objectif principal de cette thèse était de concevoir des approches prédictives de modélisation du devenir du médicament dans l’organisme en présence et en absence de modulation d’activité métabolique et de transport. Le premier volet de recherche consistait à intégrer dans un modèle pharmacocinétique à base physiologique (PBPK), le transport d’efflux membranaire gouverné par les glycoprotéines-P (P-gp) dans le cœur et le cerveau. Cette approche, basée sur des extrapolations in vitro-in vivo, a permis de prédire la distribution tissulaire de la dompéridone chez des souris normales et des souris déficientes pour les gènes codant pour la P-gp. Le modèle a confirmé le rôle protecteur des P-gp au niveau cérébral, et a suggéré un rôle négligeable des P-gp dans la distribution tissulaire cardiaque pour la dompéridone. Le deuxième volet de cette recherche était de procéder à l’analyse de sensibilité globale (ASG) du modèle PBPK précédemment développé, afin d’identifier les paramètres importants impliqués dans la variabilité des prédictions, tout en tenant compte des corrélations entre les paramètres physiologiques. Les paramètres importants ont été identifiés et étaient principalement les paramètres limitants des mécanismes de transport à travers la membrane capillaire. Le dernier volet du projet doctoral consistait à développer un modèle PBPK apte à prédire les profils plasmatiques et paramètres pharmacocinétiques de substrats de CYP3A administrés par voie orale à des volontaires sains, et de quantifier l’impact d’interactions médicamenteuses métaboliques (IMM) sur la pharmacocinétique de ces substrats. Les prédictions des profils plasmatiques et des paramètres pharmacocinétiques des substrats des CYP3A ont été très comparables à ceux mesurés lors d’études cliniques. Quelques écarts ont été observés entre les prédictions et les profils plasmatiques cliniques mesurés lors d’IMM. Cependant, l’impact de ces inhibitions sur les paramètres pharmacocinétiques des substrats étudiés et l’effet inhibiteur des furanocoumarins contenus dans le jus de pamplemousse ont été prédits dans un intervalle d’erreur très acceptable. Ces travaux ont contribué à démontrer la capacité des modèles PBPK à prédire les impacts pharmacocinétiques des interactions médicamenteuses avec une précision acceptable et prometteuse.

Interactions médicamenteuses et réactions adverses aux soins intensifs: le rôle des sédatifs et des analgésiants

Les patients admis aux soins intensifs (SI) souffrent de comorbidités qui affectent leur pronostic. Deux problèmes sont potentiellement associés aux sédatifs et compliquent le séjour de 35 à 50% des malades : le délirium, un état confusionnel aigu; et le coma ‘iatrogénique’, une altération de la conscience induite pharmacologiquement. L’importance de l’association entre clinique et médicaments a un intérêt pour prévenir ces syndromes cliniques morbides. Nous voulions étudier le délirium et le coma iatrogénique, les doses administrées de midazolam et de fentanyl, leurs niveaux plasmatiques, les variantes génétiques de métabolisme et de transport et les facteurs inflammatoires et ce, chez 100 patients admis aux soins intensifs. Nos données soulignent l’importance des interactions médicamenteuses dans l’incidence du coma iatrogénique, et réfutent l’association entre les benzodiazépines et le délirium. Ces résultats clarifient la pathophysiologie du délirium, corroborent le manque d’association délirium-benzodiazépines avec un marqueur biologique, c.-à-d. les niveaux sériques, et ouvrent le débat quant aux agents les plus utiles pour traiter l’anxiété et le délirium. Finalement, plusieurs caractéristiques pharmacocinétiques des benzodiazépines administrées aux soins intensifs publiées récemment complètent les données de notre étude quant à la sédation en soins critiques. Un chapitre sur l’importance de la pharmacogénomique en soins intensifs et un débat publié quant au pro et con de l'utilisation des benzodiazépines aux SI, sont soumis en complément de l’étude clinique décrite ci-haut effectuée dans le cadre de cette maîtrise.

Sequentially testing for a gene-drug interaction in a genomewide analysis

Assaying a large number of genetic markers from patients in clinical trials is now possible in order to tailor drugs with respect to efficacy. The statistical methodology for analysing such massive data sets is challenging. The most popular type of statistical analysis is to use a univariate test for each genetic marker, once all the data from a clinical study have been collected. This paper presents a sequential method for conducting an omnibus test for detecting gene-drug interactions across the genome, thus allowing informed decisions at the earliest opportunity and overcoming the multiple testing problems from conducting many univariate tests. We first propose an omnibus test for a fixed sample size. This test is based on combining F-statistics that test for an interaction between treatment and the individual single nucleotide polymorphism (SNP). As SNPs tend to be correlated, we use permutations to calculate a global p-value. We extend our omnibus test to the sequential case. In order to control the type I error rate, we propose a sequential method that uses permutations to obtain the stopping boundaries. The results of a simulation study show that the sequential permutation method is more powerful than alternative sequential methods that control the type I error rate, such as the inverse-normal method. The proposed method is flexible as we do not need to assume a mode of inheritance and can also adjust for confounding factors. An application to real clinical data illustrates that the method is computationally feasible for a large number of SNPs. Copyright (c) 2007 John Wiley & Sons, Ltd.

Interactions between herbal and conventional medicines

Herb-drug interactions are subject to much interest at present, but for various reasons reports may be unreliable or unsubstantiated. Herbal medicines are variable in composition and quality, which may affect their interaction profile as well as the reliability of reports concerning them. In this review, clinical and experimental reports have been collated, evaluated and summarised, and the theoretical and clinical evidence presented. There is an explanation of the particular issues involved with herbal medicines as compared with conventional drugs, and reasons why comparisons may or may not be valid, which is intended for those without specialist experience in herbal products. It has become apparent that only a few herbal drugs have so far been cited in interaction reports, for example St John's Wort, Ginkgo biloba, Dan Shen, liquorice, Ma huang and garlic, and that the main drugs involved are those which are already susceptible to interactions with many other conventional drugs, such as warfarin, protease inhibitors and anti-cancer drugs. An attempt has been made to put the matter into perspective and recommendations have been given for health professionals to advise or develop strategies to safeguard patients, without resorting to speculation or scaremongering.

Nanotechnology-based drug delivery systems for treatment of hyperproliferative skin diseases - a review

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bright solitons in quasi-one-dimensional dipolar condensates with spatially modulated interactions

We introduce a model for the condensate of dipolar atoms or molecules, in which the dipole-dipole interaction (DDI) is periodically modulated in space due to a periodic change of the local orientation of the permanent dipoles, imposed by the corresponding structure of an external field (the necessary field can be created, in particular, by means of magnetic lattices, which are available to the experiment). The system represents a realization of a nonlocal nonlinear lattice, which has a potential to support various spatial modes. By means of numerical methods and variational approximation (VA), we construct bright one-dimensional solitons in this system and study their stability. In most cases, the VA provides good accuracy and correctly predicts the stability by means of the Vakhitov-Kolokolov criterion. It is found that the periodic modulation may destroy some solitons, which exist in the usual setting with unmodulated DDI and can create stable solitons in other cases, not verified in the absence of modulations. Unstable solitons typically transform into persistent localized breathers. The solitons are often mobile, with inelastic collisions between them leading to oscillating localized modes. © 2013 American Physical Society.

Role of the clinical pharmacist in detection of drug therapy problemas in critically impatients: experience report

This is an experience report on clinical pharmacy in New York, United States of America, in a teaching hospital, describing the results of drug therapy monitoring in critically ill patients, as well as interventions to solve or prevent identified drug therapy problems. The cross-sectional study was conducted by the clinical staff at the Surgical Intensive Care Unit during August 20th to 24th, 2012. Blood counts, serum levels of certain antibiotics, microbiological cultures and their antibiotic susceptibility, possible drug interactions, dosage of each drug prescribed and the compatibility between the route of administration and pharmaceutical form were assessed daily through review of electronic medical records. Twenty seven patients were followed up and 16 drug therapy problems were identified: Unnecessary drug therapy (seven), adverse drug reaction (four), needs additional drug therapy (two), noncompliance (two) and dosage too low (one). After evaluation, the drug therapy problems and their pharmaceutical interventions were reported to clinical pharmaceutical responsible for the Surgical ICU, as well as the multidisciplinary team. Further, the clinical outcomes were monitored and interventions were classified as to its acceptance. Data demonstrate that clinical pharmacists can contribute to the security and proper use of medications, as the trigger tools for intensive monitoring helps in early detection of drug therapy problems and patient safety.

Immune pathomechanism of drug hypersensitivity reactions

Drug hypersensitivity research has progressed enormously in recent years, and a greater understanding of mechanisms has contributed to improved drug safety. Progress has been made in genetics, enabling personalized medicine for certain drugs, and in understanding drug interactions with the immune system. In a recent meeting in Rome, the clinical, chemical, pharmacologic, immunologic, and genetic aspects of drug hypersensitivity were discussed, and certain aspects are briefly summarized here. Small chemicals, including drugs, can induce immune reactions by binding as a hapten to a carrier protein. Park (Liverpool, England) demonstrated (1) that drug haptens bind to protein in patients in a highly restricted manner and (2) that irreversibly modified carrier proteins are able to stimulate CD4(+) and CD8(+) T cells from hypersensitive patients. Drug haptens might also stimulate cells of the innate immune system, in particular dendritic cells, and thus give rise to a complex and complete immune reaction. Many drugs do not have hapten-like characteristics but might gain them on metabolism (so-called prohaptens). The group of Naisbitt found that the stimulation of dendritic cells and T cells can occur as a consequence of the transformation of a prohapten to a hapten in antigen-presenting cells and as such explain the immune-stimulatory capacity of prohaptens. The striking association between HLA-B alleles and the development of certain drug reactions was discussed in detail. Mallal (Perth, Australia) elegantly described a highly restricted HLA-B∗5701-specific T-cell response in abacavir-hypersensitive patients and healthy volunteers expressing HLA-B∗5701 but not closely related alleles. Expression of HLA-B∗1502 is a marker known to be necessary but not sufficient to predict carbamazepine-induced Stevens-Johnson syndrome/toxic epidermal necrolysis in Han Chinese. The group of Chen and Hong (Taiwan) described the possible "missing link" because they showed that the presence of certain T-cell receptor (TCR) clonotypes was necessary to elicit T-cell responses to carbamazepine. The role of TCRs in drug binding was also emphasized by Pichler (Bern, Switzerland). Following up on their "pharmacological interactions of drugs with immune receptors" concept (p-i concept), namely that drugs can bind directly to TCRs, MHC molecules, or both and thereby stimulate T cells, they looked for drug-binding sites for the drug sulfamethoxazole in drug-specific TCRs: modeling revealed up to 7 binding sites on the CDR3 and CDR2 regions of TCR Vα and Vβ. Among many other presentations, the important role of regulatory T cells in drug hypersensitivity was addressed.

Drug interaction potential of resveratrol

Resveratrol is a naturally occurring polyphenol that is often used as a food supplement. Many positive health effects, including cardio protection, tumor suppression, and immune modulation, are associated with the intake of resveratrol. Resveratrol is well tolerated in healthy subjects without any comedication. However, supplemental doses of resveratrol in the range of 1 g/day or above by far exceed the natural intake through food. Whether resveratrol-drug interactions can be harmful in patients taking additional medications remains unknown. Recent in vivo studies and clinical trials indicate a possible drug-drug interaction potential using high-dosage formulations. In this review, the known in vitro and in vivo effects of resveratrol on various cytochrome P450 (CYP) isoenzymes are summarized. They are discussed in relation to clinically relevant plasma concentrations in humans. We conclude that resveratrol may lead to interactions with various CYPs, especially when taken in high doses. Aside from systemic CYP inhibition, intestinal interactions must also be considered. They can potentially lead to reduced first-pass metabolism, resulting in higher systemic exposure to certain coadministrated CYP substrates. Therefore, patients who ingest high doses of this food supplement combined with additional medications may be at risk of experiencing clinically relevant drug-drug interactions.

The well-being model: a new drug interaction model for positive and negative effects

BACKGROUND: Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. METHODS: By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by superposition of positive and negative effects. Well-being response surfaces are computed and analyzed for varying drugs pharmacodynamics and interaction types. In particular, the existence of multiple maxima and of optimal drug combinations is investigated for the combination of two drugs. RESULTS: Both drug pharmacodynamics and interaction type affect the well-being surface and the deriving optimal combinations. The effect of the interaction parameters can be explained in terms of synergy and antagonism and remains unchanged for varying pharmacodynamics. For all simulations performed for the combination of two drugs, the presence of more than one maximum was never observed. CONCLUSIONS: The model is consistent with clinical knowledge and supports previously published experimental results on optimal drug combinations. This new framework improves understanding of the characteristics of drug combinations used in clinical practice and can be used in clinical research to identify optimal drug dosing.

A unifying approach for haplotype analysis of quantitative traits in family-based association studies: Testing and estimating gene-environment interactions with complex exposure variables

We propose robust and e±cient tests and estimators for gene-environment/gene-drug interactions in family-based association studies. The methodology is designed for studies in which haplotypes, quantitative pheno- types and complex exposure/treatment variables are analyzed. Using causal inference methodology, we derive family-based association tests and estimators for the genetic main effects and the interactions. The tests and estimators are robust against population admixture and strati¯cation without requiring adjustment for confounding variables. We illustrate the practical relevance of our approach by an application to a COPD study. The data analysis suggests a gene-environment interaction between a SNP in the Serpine gene and smok- ing status/pack years of smoking that reduces the FEV1 volume by about 0.02 liter per pack year of smoking. Simulation studies show that the pro- posed methodology is su±ciently powered for realistic sample sizes and that it provides valid tests and effect size estimators in the presence of admixture and stratification.