Predicting electrophoretic mobility of beta-blockers in a water-methanol based electrolyte system

Capillary isotachophoresis with electrospray-ionization mass-spectrometric detection: Cationic electrolyte systems in the medium-alkaline range for selective analysis of medium strong bases

This work extends the present working range of isotachophoresis (ITP) with electrospray-ionization mass-spectrometric (ESI-MS) detection and describes for the first time a functional cationic electrolyte system for analyses at medium-alkaline pH. So far no ITP-MS application was published on the analysis of medium strong bases although there is a broad spectrum of potential analytes like biogenic amines, alkaloids or drugs, where this technique promises interesting gains in both sensitivity and specificity. The presented results include a selection of suitable sufficiently volatile ESI-compatible system components, discussion of factors affecting system properties, and recommendations for functional ITP electrolyte systems. Theoretical conclusions based on calculations and computer simulations are confirmed by experiments with a model mixture of beta-blockers. Practical applicability of the method is demonstrated on the example of analysis of sotalol in dried blood spots where direct injection of aqueous extract, ITP stacking and MS detection provide a fast, simple and sensitive technique with limits of quantitation on the sub-nM level.

Oxidation of β-blockers by birnessite: Kinetics, mechanism and effect of metal ions

Manganese dioxides are ubiquitous in natural waters, soils, and sediments and play an important role in oxidative transformation of organic pollutants. This work presents the kinetics of the oxidation of selected β-blockers, betaxolol, metoprolol, and atenolol by birnessite (δ-MnO₂) as a function of concentration of the β-blocker, dosage of δ-MnO₂, and solution pH. The values of pseudo-first-order rate constants (k_obs) of β-blockers decreased in the order betaxolol > atenolol > metoprolol, which was positively correlated with their acid dissociation constants (K_a). Effect of series of metal ions (Fe³⁺, Cr³⁺, Al³⁺, Pb²⁺, Cu²⁺, Zn²⁺, Ni²⁺, Cd²⁺, Mg²⁺, and Ca²⁺) on the degradation of β-blockers by δ-MnO₂ was systematically examined. All of these metal ions inhibited the oxidation reaction under the same constant ionic strength. The inhibition efficiency was positively correlated with the logarithm of stability constant of metal ions in aqueous solution (logK_MeOH). By LC-ESI-MS/MS analyses, the oxidation of β-blockers primarily involved hydroxylation and cleavage of the parent molecules to the short branched chain compounds. An electron transfer mechanism for the oxidation of β-blockers by δ-MnO₂ was proposed. The oxidation was initiated by the electron transfer from the nonbonding electrons on nitrogen (N-electrons) of β-blockers to δ-MnO₂, followed by transformation of radical intermediates. These findings will help to understand the oxidation processes of β-blockers and predict the effect of metal ions on the removal of pollutants by δ-MnO₂ in the environment.

In-stream attenuation of neuro-active pharmaceuticals and their metabolites

In-stream attenuation was determined for 14 neuro-active pharmaceuticals and associated metabolites. Lagrangian sampling, which follows a parcel of water as it moves downstream, was used to link hydrological and chemical transformation processes. Wastewater loading of neuro-active compounds varied considerably over a span of several hours, and thus a sampling regime was used to verify that the Lagrangian parcel was being sampled and a mechanism was developed to correct measured concentrations if it was not. In-stream attenuation over the 5.4-km evaluated reach could be modeled as pseudo-first-order decay for 11 of the 14 evaluated neuro-active pharmaceutical compounds, illustrating the capacity of streams to reduce conveyance of neuro-active compounds downstream. Fluoxetine and N-desmethyl citalopram were the most rapidly attenuated compounds (t1/2 = 3.6 ± 0.3 h, 4.0 ± 0.2 h, respectively). Lamotrigine, 10,11,-dihydro-10,11,-dihydroxy-carbamazepine, and carbamazepine were the most persistent (t1/2 = 12 ± 2.0 h, 12 ± 2.6 h, 21 ± 4.5 h, respectively). Parent compounds (e.g., buproprion, carbamazepine, lamotrigine) generally were more persistent relative to their metabolites. Several compounds (citalopram, venlafaxine, O-desmethyl-venlafaxine) were not attenuated. It was postulated that the primary mechanism of removal for these compounds was interaction with bed sediments and stream biofilms, based on measured concentrations in stream biofilms and a column experiment using stream sediments.

Photodegradation of selected β-blockers in aqueous fulvic acid solutions: kinetics, mechanism, and product analysis

The photodegradation of the widely used β-blockers atenolol and metoprolol were investigated in the presence of fulvic acid (FA) under simulated sunlight. Both atenolol and metoprolol undergo indirect photodegradation in the FA solutions. The triplet excited state of FA ((3)FA(∗)) was verified to be main reactive species responsible for the photosensitized degradation of β-blockers. An electron transfer mechanism for the interaction between β-blockers and (3)FA(∗) was proposed on the basis of a series of experiments. Magnetic property of metal ions exhibited significant impact on photosensitized degradation. Diamagnetic metal ions such as Mg(2+), Ca(2+), Zn(2+), and Al(3+) negligibly affected the degradation. In contrast, paramagnetic metal ions including Mn(2+), Cu(2+), Fe(3+), and Cr(3+) markedly inhibited the reactions in the order of Cr(3+) < Fe(3+) < Cu(2+) < Mn(2+). The inhibition was related to the complexation ability with FA. By LC-ESI-MS/MS analysis, deisopropyl-atenolol (metoprolol) was identified as the main photosensitized product. The degradation pathways of β-blockers involving electron transfer processes were proposed. This finding strongly suggests that (3)FA(∗) was important reactive species for the degradation of β-blockers in natural waters.

Extended delivery of ophthalmic drugs by silicone hydrogel contact lenses

We developed extended wear silicone hydrogel soft contact lenses that deliver ophthalmic drugs for an extended period of time ranging from weeks to months. Silicone hydrogels comprising of N,N-dimethylacrylamide, 3-methacryloxypropyltris(trimethylsiloxy)silane, bis-alpha,omega-(methacryloxypropyl) polydimethylsiloxane, 1-vinyl-2-pyrrolidone, and ethylene glycol dimethacrylate were prepared with varying ratios of monomers and transport of three different ophthalmic drugs, timolol, dexamethasone, and dexamethasone 21-acetate was explored. All the silicone hydrogels of 0.1 mm thickness exhibit diffusion limited transport and extended release varying 20 days up to more than three months depending on the compositions of hydrophobic and hydrophilic components of silicone hydrogels. Also, there are multiple time scales in transport of at least certain molecules, which is perhaps due to the complex microstructure of these gels. The mechanical and physical properties of lenses such as ion permeability, equilibrium water content, transparency, and surface contact angles of some of the gels are suitable for contact lens application.

Theoretical and empirical approaches to express the mobility of small ions in capillary electrophoresis

A discussion is given about the concepts of the ion mobility, the analyte property which governs migration and thus separation selectivity in CE. It deals with small organic and inorganic ions, not with charged polymers or large particles like colloids. The discussion is directed to two main concepts. (i) The first is based on physico-chemistry of ion conductance in solution, and distinguishes three types of mobility. The absolute mobility is the limiting mobility at zero ionic strength; it depends on the solvent and the temperature. It is obtained by extrapolation of the actual mobilities, those of the fully charged particles at finite ion concentration. The observed reduction of the absolute mobility with ionic concentration is related to an ion cloud, and is formulated by the established theories of ion conductance. It explains the actual mobility as function of (beside other factors) the ionic strength, the viscosity and relative permittivity of the solvent, the temperature, the relaxation time of solvent polarisation and the distance of closest approach between ion and counterion. The effective mobility, finally, is the mobility when association and dissociation equilibria play a role. Most important are acid-base reactions, but complexation, ion pairing and homo- and heteroconjugation were considered as well. (ii) The second approach treats mobility data with different mathematical methods, and formulates their dependence on variables like solvent composition with appropriate algorithms. These empirical methods mainly include least squares and neural network-based methods. The least square methods ranges from the simplest model, which uses only the molecular weight of the analyte, to more complicated model requiring three-dimensional structural descriptors of the solutes. Neural networks have been applied to model the mobility using different input variables and various architectures. Work comparing the accuracy of least squares and neural network methods was discussed; the results showed that the neural network method leads to a more accurate mobility calculation. However, the least squares methods could give some information to the factors affecting the mobility of the analytes. The resulting methods allow the prediction of mobilities under different experimental conditions with certain accuracy. It has been shown that using such models, it is possible to predict mobility of analytes after training the models by a minimum number of data to speed up the method development stage.

Modeling drug solubility in water-cosolvent mixtures using an artificial neural network

Application of the artificial neural network (ANN) to calculate the solubility of drugs in water-cosolvent mixtures was shown using 35 experimental data sets. The networks employed were feedforward backpropagation errors with one hidden layer. The topology of neural network was optimized and the optimum topology achieved was a 6-5-1 architecture. All data points in each set were used to train the ANN and the solubilities were back-calculated employing the trained networks. The differences between calculated solubilities and experimental values was used as an accuracy criterion and defined as mean percentage deviation (MPD). The overall MPD (OMPD) and its S.D. obtained for 35 data sets was 0.90 +/- 0.65%. To assess the prediction capability of the method, five data points in each set were used as training set and the solubility at other solvent compositions were predicted using trained ANNs whereby the OMPD (+/-S.D.) for this analysis was 9.04 +/- 3.84%. All 496 data points from 35 data sets were used to train a general ANN model, then the solubilities were back-calculated using the trained network and MPD (+/-S.D.) was 24.76 +/- 14.76%. To test the prediction capability of the general ANN model, all data points with odd set numbers from 35 data sets were employed to train the ANN model, the solubility for the even data set numbers were predicted and the OMPD (+/-S.D.) was 55.97 +/- 57.88%. To provide a general ANN model for a given cosolvent, the experimental data points from each binary solvent were used to train ANN and back-calculated solubilities were used to calculate MPD values. The OMPD (+/-S.D.) for five cosolvent systems studied was 2.02 +/- 1.05%. A similar numerical analysis was used to calculate the solubility of structurally related drugs in a given binary solvent and the OMPD (+/-S.D.) was 4.70 +/- 2.02%. ANN model also trained using solubility data from a given drug in different cosolvent mixtures and the OMPD (+/-S.D.) obtained was 3.36 +/- 1.66%. The results for different numerical analyses using ANN were compared with those obtained from the most accurate multiple linear regression model, namely the combined nearly ideal binary solvent/Redlich-Kister equation, and the ANN model showed excellent superiority to the regression model.

A simple relationship between dielectric constant of mixed solvents with solvent composition and temperature

A simple computational method for calculating dielectric constants of solvent mixtures based on Redlich-Kister extension was proposed. The model was applied to the experimental dielectric constant of binary and ternary solvent mixtures at fixed and/or various temperatures and showed accurate results. Overall average percentage deviation (OAPD) between calculated and experimental dielectric constants was calculated as an accuracy criterion. The OAPDs for correlative and predictive analyses of dielectric constants in binary solvents at a fixed temperature were 0.56 and 1.42%, respectively. The corresponding values for binary solvents at different temperatures were 1.29 and 1.92%, respectively. The OAPDs for correlative and predictive analyses of dielectric constants of a nonaqueous ternary solvent mixture at various temperatures were 1.61 and 3.05%. The accuracy of the proposed models has also been compared with those of previously published models and results showed that the proposed models were superior and capable of providing more accurate results.

Surface Tension Calculation of Mixed Solvents with Respect to Solvent Composition and Temperature by Using Jouyban-Acree Model

Applicability of a solution model, i.e. Jouyban-Acree model (JAM), for calculating surface tension of binary and ternary solvents at various temperatures has been shown employing experimental surface tension data collected from the literature. The accuracy of the model was evaluated by calculating average percentage deviation (APD) between calculated and observed values. The obtained overall APD (+/-S.D.) for JAM using binary solvent data were 4.06 (+/-4.27) and 8.07 (+/-9.78)%, respectively for correlative and predictive analyses. The corresponding values for the best similar model from the literature were 8.86 (+/-6.40) and 37.10 (+/-27.65)% and the mean APD differences between JAM and previously published model were significant (p<0.003). The capability of JAM for correlating surface tension of ternary solvents at various temperatures was also shown and the overall APD was 1.39 (+/-0.37)%.

Electrophoretic behavior of alprenolol in mixed solvent electrolyte systems

The electrophoretic mobilities of alprenolol have been determined in a mixed solvent background electrolyte system containing sodium acetate (40 mM)+acetic acid (40 mM) as buffering agent and different volume fractions of water, methanol and ethanol using capillary electrophoresis. The mobility of alprenolol has been used to test the prediction capability of a model trained by previously reported mobility data of five beta-blocker drugs at the same electrophoretic conditions. The average percentage mean deviations (APMD) between experimental and predicted values were used as an accuracy criterion. The APMD (+/-SD) obtained for alprenolol data in binary/ternary solvent electrolyte system employing the mobility values in mono-solvent buffers was 4.37 (+/-3.50)% and the corresponding value for an ab initio prediction method was 7.65 (+/-4.30)%.