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.

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.

Drug interaction and location in liposomes: correlation with polar surface areas

An important step in liposome characterization is to determine the location of a drug within the liposome. This work thus investigated the interaction of dipalmitoylphosphatidylcholine liposomes with drugs of varied water solubility, polar surface area (PSA) and partition coefficient using high sensitivity differential scanning calorimetry. Lipophilic estradiol (ES) interacted strongest with the acyl chains of the lipid membrane, followed by the somewhat polar 5-fluorouracil (5-FU). Strongly hydrophilic mannitol (MAN) showed no evidence of interaction but water soluble polymers inulin (IN) and an antisense oligonucleotide (OLG), which have very high PSAs, interacted with the lipid head groups. Accordingly, the drugs could be classified as: hydrophilic ones situated in the aqueous core and which may interact with the head groups; those located at the water-bilayer interface with some degree of penetration into the lipid bilayer; those lipophilic drugs constrained within the bilayer. (c) 2004 Elsevier B.V. All rights reserved.

Solution calorimetry as a tool for investigating drug interaction with intestinal fluid

Solution calorimetry offers a reproducible technique for measuring the enthalpy of solution (ΔsolH) of a solute dissolving into a solvent. The ΔsolH of two solutes, propranolol HCl and mannitol were determined in simulated intestinal fluid (SIF) solutions designed to model the fed and fasted states within the gut, and in Hanks’ balanced salt solution (HBSS) of varying pH. The bile salt and lipid within the SIF solutions formed mixed micelles. Both solutes exhibited endothermic reactions in all solvents. The ΔsolH for propranolol HCl in the SIF solutions differed from those in the HBSS and was lower in the fed state than the fasted state SIF solution, revealing an interaction between propranolol and the micellar phase in both SIF solutions. In contrast, for mannitol the ΔsolH was constant in all solutions indicating minimal interaction between mannitol and the micellar phases of the SIF solutions. In this study, solution calorimetry proved to be a simple method for measuring the enthalpy associated with the dissolution of model drugs in complex biological media such as SIF solutions. In addition, the derived power–time curves allowed the time taken for the powdered solutes to form solutions to be estimated.

Incorporation of Ag nanoparticles into membrane mimetic systems composed by phospholipid layer-by-layer (LbL) films to achieve surface-enhanced Raman scattering as a tool in drug interaction studies

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

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.

Transfection of drug-specific T-cell receptors into hybridoma cells: tools to monitor drug interaction with T-cell receptors and evaluate cross-reactivity to related compounds

In the context of drug hypersensitivity, our group has recently proposed a new model based on the structural features of drugs (pharmacological interaction with immune receptors; p-i concept) to explain their recognition by T cells. According to this concept, even chemically inert drugs can stimulate T cells because certain drugs interact in a direct way with T-cell receptors (TCR) and possibly major histocompatibility complex molecules without the need for metabolism and covalent binding to a carrier. In this study, we investigated whether mouse T-cell hybridomas transfected with drug-specific human TCR can be used as an alternative to drug-specific T-cell clones (TCC). Indeed, they behaved like TCC and, in accordance with the p-i concept, the TCR recognize their specific drugs in a direct, processing-independent, and dose-dependent way. The presence of antigen-presenting cells was a prerequisite for interleukin-2 production by the TCR-transfected cells. The analysis of cross-reactivity confirmed the fine specificity of the TCR and also showed that TCR transfectants might provide a tool to evaluate the potential of new drugs to cause hypersensitivity due to cross-reactivity. Recombining the alpha- and beta-chains of sulfanilamide- and quinolone-specific TCR abrogated drug reactivity, suggesting that both original alpha- and beta-chains were involved in drug binding. The TCR-transfected hybridoma system showed that the recognition of two important classes of drugs (sulfanilamides and quinolones) by TCR occurred according to the p-i concept and provides an interesting tool to study drug-TCR interactions and their biological consequences and to evaluate the cross-reactivity potential of new drugs of the same class.

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 BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

An evaluation of a community-based program for homeless adults with mental disorders and comorbid alcohol drug and mental disorders

Limited research has been conducted evaluating programs that are designed to improve the outcomes of homeless adults with mental disorders and comorbid alcohol, drug and mental disorders. This study conducted such an evaluation in a community-based day treatment setting with clients of the Harris County Mental Health and Mental Retardation Authority's Bristow Clinic. The study population included all clients who received treatment at the clinic for a minimum of six months between January 1, 1995 and August 31, 1996. An electronic database was used to identify clients and to track their program involvement. A profile was developed of the study participants and their level of program involvement included an examination of the amount of time spent in clinical, social and other interventions, the type of interventions encountered and the number of interventions encountered. Results were analyzed to determine whether social, demographic and mental history affected levels of program involvement and the effects of the levels of program involvement on housing status and psychiatric functioning status.^ A total of 101 clients met the inclusion criteria. Of the 101 clients, 96 had a mental disorder, and five had comorbidity. Due to the limited numbers of participants with comorbidity, only those with mental disorders were included in the analysis. The study found the Bristow Clinic population to be primarily single, Black, male, between the ages of 31 and 40 years, and with a gross family income of less than $4,000. There were more persons residing on the streets at entry and at six months following treatment than in any other residential setting. The most prevalent psychiatric diagnoses were depressive disorders and schizophrenia. The Global Assessment of Functioning (GAF) scale which was used to determine the degree of psychiatric functioning revealed a modal GAF score of 31--40 at entry and following six months in treatment. The study found that the majority of clients spent less than 17 hours in treatment, had less than 51 encounters and had clinical, social, and other encounters. In regard to social and demographic factors and levels of program involvement, there were statistically significant associations between gender and ethnicity and the types of interventions encountered as well as the number of interventions encountered. There was also a statistically significant difference between the amount of time spent in clinical interventions and gender. Relative to outcomes measured, the study found female gender to be the only background variable that was significantly associated with improved housing status and the female gender and previous MHMRA involvement to be statistically associated with improvement in GAF score. The total time in other (not clinical or social) interventions and the total number of encounters with other interventions were also significantly associated with improvement in housing outcome. The analysis of previous services and levels of program involvement revealed significant associations between time spent in social and clinical interventions and previous hospitalizations and previous MHMRA involvement.^ Major limitations of this study include the small sample size which may have resulted in very little power to detect differences and the lack of generalizability of findings due to site locations used in the study. Despite these limitations, the study makes an important contribution to the literature by documenting the levels of program involvement and the social and demographic factors necessary to produce outcomes of improved housing status and psychiatric functioning status. ^

RELATIONSHIP OF ANTISOCIAL PERSONALITY SYNDROME IN BOYS TO PARENTAL ALCOHOL/DRUG DEPENDENCY

The study focused on the relationship between antisocial personality syndrome in boys ages 8-15 and parental alcohol/drug dependency. The population studied was case records of 101 boys coming to a private psychiatrist from 1966 through 1979. The boys were predominantly white and from middle to upper income families.^ A boy was determined to have antisocial personality syndrome if he exhibited antisocial behaviors in four or five major categories, did not exhibit a brain syndrome, and did not exhibit a thought disorder. The five major behavior categories were: (1) self-control (i.e., temper tantrums or hyperactivity), (2) behavior at home (i.e., disobedience or lying), (3) behavior at school (i.e., truancy or cheating), (4) behavior toward peers (i.e., bullying, fighting, or tattling), and (5) behavior against property (i.e., destructiveness or stealing). A boy was determined to be a control if he exhibited antisocial behaviors in two or less behavior categories.^ A parent was determined to have alcohol/drug dependency if s/he exhibited a score above the established threshold (1) for the MacAndrew Alcoholism Scale (28 or above), and (2) for the Holmes Alcoholism Scale (35 or above) which are used with the MMPI. A parent was classified not alcohol/drug dependent if s/he had scores below set thresholds (22 on the MacAndrew Alcoholism Scale and 28 on the Holmes Alcoholism Scale).^ For the final sample (N = 10), there was no reason to believe a relationship exists between antisocial personality syndrome in boys ages 8-15 and parental alcohol/drug dependency (Fisher's Exact Test {FET} P = 1.0). The small sample size primarily occurred as a result of 88.12% of the parents being classified in a questionable category in terms of alcohol/drug dependency.^ The sample was suggestive of a relationship between the fathers' Psychopathic Deviate (Pd) Scale scores as a measure of antisocial tendencies and the boy having antisocial personality syndrome (N = 75; P = .12). There was no evidence of such a relationship for mothers (N = 75; P = .97). ^

Evidence for two nonidentical drug-interaction sites in the human P-glycoprotein

Human P-glycoprotein (Pgp) confers multidrug resistance to cancer cells by ATP-dependent extrusion of a great many structurally dissimilar hydrophobic compounds. The manner in which Pgp recognizes these different substrates is unknown. The protein shows internal homology between its N- and C-terminal halves, each comprised of six putative transmembrane helices and a consensus ATP binding/utilization site. Photoactive derivatives of certain Pgp substrates specifically label two regions, one on each half of the protein. In this study, using [125I]iodoarylazidoprazosin ([125I]IAAP), a photoactive analog of prazosin, we have demonstrated the presence of two nonidentical drug-interaction sites within Pgp. Taking advantage of a highly susceptible trypsin cleavage site in the linker region of Pgp, we characterized the [125I]IAAP binding to the N- and C-terminal halves. cis(Z)-Flupentixol, a modulator of Pgp function, preferentially increased the affinity of [125I]IAAP for the C-terminal half of the protein (C-site) by reducing the Kd from 20 to 6 nM without changing the labeling or affinity (Kd = 42–46 nM) of the N-terminal half (N-site). Also, the concentration of vinblastine (Pgp substrate) and cyclosporin A (Pgp modulator) required for 50% inhibition of [125I]IAAP binding to the C-site was increased 5- to 6-fold by cis(Z)-flupentixol without any effect on the N-site. In addition, [125I]IAAP binding to the N-site was less susceptible than to C-site to inhibition by vanadate which blocks ATP hydrolysis and drug transport. These data demonstrate the presence of at least two nonidentical substrate interaction sites in Pgp.