Pharmacology of azoles

Azole antifungals have different pharmacokinetic characteristics: complete oral absorption for Voriconazole, and to a lesser extent for fluconazole. The absorption of posaconazole and itraconazole increases with food intake. All of them have high tissue distribution with low plasma concentrations, especially low in the case of posaconazole and itraconazole. Posaconazole and itraconazole have high plasmatic protein binding and consequently both have a very low free fraction. Elimination of azole antifungals is through a metabolic pathway with CYP450 isoenzymes, and has a non linear pharmacokinetics with a high risk of interation with other drugs since azoles have the ability of CYP450 isoenzymes inhibition. Possibly the parameter that defines more precisely their efficacy is AUIC with an optimum value near 20, although cut-off values must be defined since some azoles may have difficulty to reach this value.     

Pharmacokinetic interactions of flunixin meglumine and enrofloxacin in ICR mice.

We examined the pharmacokinetic interactions of enrofloxacin and flunixin in male ICR mice that were subcutaneously (SC) administered with both or either one of the drugs. The experiments were performed on the following three groups: flunixin alone (2 mg/kg, SC), combination of flunixin (2 mg/kg, SC) and enrofloxacin (10 mg/kg, SC), and enrofloxacin alone (10 mg/kg, SC). Blood samples were collected at 5, 15 and 30 min, and 1, 2, 3, 4, 5 and 6 h after the drug administration, and the pharmacokinetic parameters of flunixin and enrofloxacin were evaluated from the plasma drug concentrations. Significant changes were detected in the pharmacokinetics of flunixin following its coadministration with enrofloxacin. Coadministration of flunixin and enrofloxacin resulted in a 41% increase of the area under the curve (AUC) and a 53% extension of the terminal half-life of flunixin; moreover, flunixin attained the maximum plasma drug concentration 2.75 times faster than when administered alone. The terminal rate constant and the maximum plasma drug concentration showed significant decreases of 34% and 33%, respectively, following the coadministration of enrofloxacin and flunixin as compared to those following the administration of flunixin alone. In contrast, no significant difference in the pharmacokinetics of enrofloxacin was detected following its coadministration with flunixin, as compared to those following the administration of enrofloxacin alone. Following the administration of enrofloxacin alone or its coadministration with flunixin, the plasma level of ciprofloxacin, the metabolite of enrofloxacin, was very low or undetectable. In conclusion, the pharmacokinetics of flunixin in ICR mice are altered by the coadministration of flunixin and enrofloxacin.     

Stereoselective and isozyme-selective drug interactions

A surprisingly large number of marketed drugs are racemic mixtures. The pharmacokinetic literature on racemic drugs contains a vast amount of information on drug–drug interactions derived from the measurement of total drug concentrations in plasma and urine. The appreciation of the role of stereochemistry in drug interactions with racemic warfarin resulted in a long-overdue scientific rigor being applied to the study of drug interactions. It also compelled us to recognize that much of the literature was uninterpretable. A better understanding of oxidative metabolism, particularly the complexity of the cytochrome P-450 family of enzymes, has also strengthened the scientific basis of drug interactions. We now recognize that investigators and clinicians must consider both stereoselectivity and isozyme selectivity in the study of drug interactions to understand the nature of the interaction so as to more effectively use new and potent drugs. © 1993 Wiley-Liss, Inc.     

Kinetic simulation of anticancer drug interactions

A model is described that simulates the biochemical pathways of folate and nucleotide metabolism involved in DNA precursor biosynthesis. Examples are given of use of the model to study various aspects of the biochemical pharmacology of antitumour drugs. Modelling may be done in two ways: detailed simulation of all variables may be conducted for short time periods (<6 h of real time); alternatively, by assuming that concentrations of rapidly interconvertible metabolites remain close to steady-state proportions, time periods of several days may be modelled, facilitating simulation of cell growth in presence of drugs. Experiments designed to test predictions for these various types of study are described.     

Modeling sequence-sequence interactions for drug response

MOTIVATION: Genetic interactions or epistasis may play an important role in the genetic etiology of drug response. With the availability of large-scale, high-density single nucleotide polymorphism markers, a great challenge is how to associate haplotype structures and complex drug response through its underlying pharmacodynamic mechanisms. RESULTS: We have derived a general statistical model for detecting an interactive network of DNA sequence variants that encode pharmacodynamic processes based on the haplotype map constructed by single nucleotide polymorphisms. The model was validated by a pharmacogenetic study for two predominant beta-adrenergic receptor (betaAR) subtypes expressed in the heart, beta1AR and beta2AR. Haplotypes from these two receptors trigger significant interaction effects on the response of heart rate to different dose levels of dobutamine. This model will have implications for pharmacogenetic and pharmacogenomic research and drug discovery. AVAILABILITY: A computer program written in Matlab can be downloaded from the webpage of statistical genetics group at the University of Florida. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Design and synthesis of novel tetrahydronaphthyl azoles and related cyclohexyl azoles as antileishmanial agents

A novel series of trans-2-aryloxy-1,2,3,4,-tetrahydronaphthyl azoles and related cyclohexyl azoles were synthesized and evaluated in vitro against Leishmania donovani. Compound 9 identified as most active analog with IC₅₀ value of 0.64 μg/mL and SI value of 34.78 against amastigotes, and is several folds more potent than the reference drugs sodium stilbogluconate and paromomycin. It also exhibited significant in vivo inhibition of 83.33%, and provided a new structural scaffold for antileishmanials.     

Pharmacometabolomics in drug safety and drug-exposome interactions

Background

Pharmacometabolomics is a relatively new field that measures an individual’s metabolome in biofluids to detect prognostic and diagnostic biomarkers of drug response and to provide an effective means to predict variation in a subject’s response to drug treatment. Pharmacometabolomics has the potential to help clinicians determine the effectiveness and safety of a drug on an individual basis.

Aim of Review

To provide information from the current literature in pharmocometabolomics relevant to drug safety including factors besides genetics that can play a role in how a subject responds to a drug treatment. Pharmacometabolomics studies on drug-induced liver toxicity, the use of pharmacometabolomics to detect and predict drug interactions, and future applications of pharmacometabolomics in drug safety are discussed.

Key scientific concepts of the review

Pharmacometabolomics can play a role in identifying and/or characterizing toxicity at all stages of drug development. These stages include: pharmacokinetics and ADME; initial toxicity; protective mechanisms; adverse events; late injury; and, injury progression or recovery. Pharmacometabolomics also has the ability to detect endogenous metabolites and markers of other exposure factors including alcohol consumption, impact of the gut microbiome, nutrition, other medications (polypharmacy), dietary supplements, and current individual health-to-disease status, all of which could play a role in patient response to a drug. Pharmacometabolomics alone or in combination with pharmacogenomics can be used to develop customized treatment plans for patients (i.e., personalized medicine) that could significantly reduce adverse events that are sometimes associated with the use of pharmaceuticals.

     

A D-octapeptide drug efflux pump inhibitor acts synergistically with azoles in a murine oral candidiasis infection model

Clinical management of patients undergoing treatment of oropharyngeal candidiasis with azole antifungals can be impaired by azole resistance. High-level azole resistance is often caused by the overexpression of Candida albicans efflux pump Cdr1p. Inhibition of this pump therefore represents a target for combination therapies that reverse azole resistance. We assessed the therapeutic potential of the D-octapeptide derivative RC21v3, a Cdr1p inhibitor, in the treatment of murine oral candidiasis caused by either the azole-resistant C. albicans clinical isolate MML611 or its azole-susceptible parental strain MML610. RC21v3, fluconazole (FLC), or a combination of both drugs were administered orally to immunosuppressed ICR mice at 3, 24, and 27 h after oral inoculation with C. albicans. FLC protected the mice inoculated with MML610 from oral candidiasis, but was only partially effective in MML611-infected mice. The co-application of RC21v3 (0.02 μmol per dose) potentiated the therapeutic performance of FLC for mice infected with either strain. It caused a statistically significant decrease in C. albicans cfu isolated from the oral cavity of the infected mice and reduced oral lesions. RC21v3 also enhanced the therapeutic activity of itraconazole against MML611 infection. These results indicate that RC21v3 in combination with azoles has potential as a therapy against azole-resistant oral candidiasis.     

Exploratory studies of some drug charge transfer interactions

Conductivity and capacitance titrations yield minima for the chlorpromazine hydrochloride-heparin interaction, confirming clinical suspicions of its occurrence. The effective dosage of heparin thus is reduced if administered in conjunction with chlorpromazine. The interaction is interpreted as charge transfer complex formation, occurring as an (electrode) surface reaction. It is suggested that the charge transfer complexing capability of heparin preparations, as evidenced by conductance and/or capacitance changes, evaluated against a well defined donor such as chlorpromazine hydrochloride, may be adapted as a more precise method of measuring heparin activity than coagulation time determinations. Phenytoin and chlorpromazine likewise yield conductance and capacitance minima; voltammetry indicates new peaks at +250mV and −300mV vers.SCE supporting the suggestions that an uncharged 1∶1 complex is being formed, again in a type of surface reaction. Phenytoin and lignocain form a precipitate at 0.002 equimolar; in conductance and capacitance titrations phenytoin behaves as a weak electron donor against iodine though as a weak acceptor against lignocain. Lignocain and chlorpromazine conductance and capacitance titrations using gold electrodes fail to show any evidence for their previously reported interaction on Pt/Pt electrodes. Voltammetry on Pt/Pt electrodes indicates 2 new peaks at zero and at −750mV vers.SCE. It is thought that these two compounds interact only on catalytically highly active surfaces, where they form a weak surface charge transfer complex. Adrenalin, in conductance and capacitance titrations, behaves amphoteric, i.e. as an electron acceptor against the strong donor chlorpromazine and as a donor against the strong acceptor tetramethyl-p-phenylenediamine. Voltammograms of the above listed interactions are interpreted as of the ECE type exhibiting mainly irreversible behaviour.     

Pharmacokinetic aspects of tert-butylaminoethyl disulfide, an experimental drug against schistosomiasis in mice

A preliminary study of the pharmacokinetic parameters of t-Butylaminoethyl disulfide was performed after administration of two different single doses (35 and 300 mg/kg) of either the cold or labelled drug. Plasma or blood samples were treated with dithiothreitol, perchloric acid, and, after filtration, submitted to further purification with anionic resin. In the final step, the drug was retained on a cationic resin column, eluted with NaCl 1M and detected according to the method of Ellman (1958). Alternatively, radioactive drug was detected by liquid scintillation counting. The results corresponding to the smaller dose of total drug suggested a pharmacokinetic behavior related to a one open compartment model with the following parameters: area under the intravenous curve (AUCi.v.): 671 +/- 14; AUCoral: 150 +/- 40 micrograms.min.ml-1; elimination rate constant: 0.071 min-1; biological half life: 9.8 min; distribution volume: 0.74 ml/g. For the higher dose, the results seemed to obey a more complex undetermined model. Combining the results, the occurrence of a dose-dependent pharmacokinetic behavior is suggested, the drug being rapidly absorbed and rapidly eliminated; the elimination process being related mainly to metabolization. The drug seems to be more toxic when administered I.V. because by this route it escapes first pass metabolism, while being quickly distributed to tissues. The maximum tolerated blood level seems to be around 16 micrograms/ml.     

Pharmacokinetic and pharmacodynamic interactions between simvastatin and diltiazem in patients with hypercholesterolemia and hypertension

Pharmacokinetic and pharmacodynamic interactions between simvastatin, a 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor, and diltiazem, a calcium antagonist, were investigated in 7 male and 4 female patients with hypercholesterolemia and hypertension. The patients were given, for one in a three consecutive 4-week periods, oral simvastatin (5 mg/day), oral simvastatin (5 mg/day) combined with diltiazem (90 mg/day), and then oral diltiazem (90 mg/day), respectively. The area under the plasma concentration versus time curve up to 6 hours post-dose (AUC0-6h) and maximum plasma concentrations (Cmax) of the drugs, serum lipid profiles, blood pressures and liver functions were assessed on the last day of each of the three 4-week periods. After the combined treatment period, Cmax of HMG-CoA reductase inhibitor was elevated from 7.8 +/- 2.6 ng/ml to 15.4 +/- 7.9 ng/ml (P < 0.01) and AUC0-6h from 21.7 +/- 4.9 ng x hr/ml to 43.3 +/- 23.4 ng x hr/ml (P < 0.01), while Cmax of diltiazem was decreased from 74.2 +/- 36.4 ng/ml to 58.6 +/- 18.9 ng/ml (P < 0.05) and its AUC0-6h from 365 +/- 153 ng x hr/ml to 287 +/- 113 ng x hr/ml (P < 0.01). Compared to simvastatin monotherapy, combined treatment further reduced LDL-cholesterol levels by 9%, from 129 +/- 16 mg/dl to 119 +/- 17 mg/dl (P < 0.05). No adverse events were observed throughout the study. These apparent pharmacokinetic interactions, namely the increase of HMG-CoA reductase inhibitor concentration by diltiazem and the decrease of diltiazem concentration by simvastatin, enhance the cholesterol-lowering effects of simvastatin during combined treatment.