Taravat Ghafourian

The enhancement effect of surfactants on the penetration of lorazepam through rat skin

Lorazepam is an anxiolytic, antidepressant agent, having suitable feature for transdermal delivery. The percutaneous permeation of lorazepam was investigated in rat skin after application of a water:propylene glycol (50:50%v/v). The enhancing effects of various surfactants (sodium lauryl sulfate (SLS), cetyltrimethylammonium bromide (CTAB), benzalkonium chloride or Tween 80) with different concentrations on the permeation of lorazepam were evaluated using Franz diffusion cells fitted with rat skins. Flux, K(p), lag time and enhancement ratios (ERs) of lorazepam were measured over 24 h and compared with control sample. Furthermore, lorazepam solubility in presence of surfactants was determined. The in vitro permeation experiments with rat skin revealed that the surfactant enhancers varied in their ability to enhance the flux of lorazepam. The permeation profile of lorazepam in presence of the cationic surfactant, CTAB, reveals that an increase in the concentration of CTAB results in an increase in the flux of lorazepam in comparison with the control. But an increase in concentration of CTAB or benzalkounium chloride from 0.5 to 1% w/w or from 1 to 2.5% w/w resulted in a reduction in ER, respectively. Benzalkonium chloride which possessed the highest lipophilicity (logP=1.9) among cationic surfactants provided the greatest enhancement for lorazepam flux (7.66-fold over control) at 1% w/w of the surfactant. CTAB (logP<1) and sodium lauryl sulphate at a concentration of 5% w/w (the highest concentration) exhibited the greatest increase in flux of lorazepam compared with control (9.82 and 11.30-fold, respectively, over control). This is attributed to the damaging effect of the cationic and anionic surfactants on the skin at higher concentration. The results also showed that the highest ER was obtained in presence of 1% w/w surfactant with the exception of SLS and CTAB. The increase in flux at low enhancer concentrations is normally attributed to the ability of the surfactant molecules to penetrate the skin and increase its permeability. Reduction in the rate of transport of the drug present in enhancer systems beyond 1% w/w is attributed to the ability of the surfactant molecules to form micelles and is normally observed only if interaction between micelle and the drug occurs.

The effect of surfactants on the skin penetration of diazepam

The percutaneous permeation of diazepam was investigated in rat skin after application of a water-propylene glycol (50:50% v/v) using a diffusion cell technique. The effect of various surfactants (sodium lauryl sulfate (SLS), cetyltrimethylammonium bromide (CTAB), benzalkonium chloride or Tween 80) with different concentrations on skin permeability were evaluated. Flux, K(p), lag time and enhancement ratios (ERs) of diazepam were measured over 10 h and compared with control sample (containing no surfactant). Furthermore, diazepam solubility in presence of surfactants was determined. The in vitro permeation experiments with rat skin revealed that the surfactant enhancers varied in their ability to enhance the flux of diazepam. Benzalkonium chloride which possessed the highest lipophilicity (logP=1.9) among cationic surfactants provided the greatest enhancement for diazepam flux (7.98-fold over control). CTAB (logP<1) at a concentration of 1% w/w exhibited no significant increase in flux of diazepam compared to control (1.16-fold over control). The results also showed that the highest ER was obtained in presence of 1% w/w surfactant with the exception of SLS and CTAB. The increase in flux at low enhancer concentrations is normally attributed to the ability of the surfactant molecules to penetrate the skin and increase its permeability. Reduction in the rate of transport of the drug present in enhancer systems beyond 1% w/w is attributed to the ability of the surfactant to form micelles and is normally observed only if interaction between micelle and the drug occurs. The results showed that the nature of enhancer greatly influences cutaneous barrier impairment.

The effect of terpene concentrations on the skin penetration of diclofenac sodium.

Terpenes and sesquiterpenes have been suggested as promising non-toxic, non-irritating transdermal penetration enhancers. This investigation aimed to study the effect of terpene concentration on the transdermal absorption of diclofenac sodium from ethanol:glycerin:phosphate buffer solution (60:10:30). Therefore, enhancing effects of various terpenes (menthone, limonenoxide, carvone, nerolidol and farnsol) with different concentrations (0.25, 0.5, 1, 1.5 and 2.5%, v/v) on the permeation of diclofenac sodium were evaluated using Franz diffusion cells fitted with rat skin. Furthermore, solubility of diclofenac sodium in the vehicle in presence of different concentrations of terpenes was determined. The results showed that despite the negligible effect of terpenes on the drug solubility, there was a profound skin penetration enhancement effect, although the terpene enhancers varied in their ability to enhance the flux of diclofenac sodium. The results showed that at the highest concentration of terpene (2.5%, v/v) the rank order of enhancement effect for diclofenac sodium was nerolidol>farnesol>carvone>methone>limonenoxide, whereas at the low concentration of 0.25% the rank order was farnesol>carvone>nerolidol>menthone>limonenoxide. No direct relationship existed between terpene concentration and the permeation rate. The most outstanding penetration enhancer was nerolidol, providing an almost 198-fold increase in permeability coefficient of diclofenac sodium, followed by farnesol with a 78-fold increase.

The Impact of variable selection on the modelling of oestrogenicity

Many oestrogenic chemicals exert their activity via specific interactions with the oestrogen receptor (ER). The objective of the present study was to identify significant descriptors associated with the ER binding affinities of a large and diverse set of compounds to drive quantitative structure–activity relationships (QSARs). To this end, a variety of statistical methods were employed for variable selection. These included stepwise regression and partial least squares (PLS) analyses, as well as a non-linear recursive partitioning method (Formal Inference-based Recursive Modelling). A total of 157 molecular descriptors including quantum mechanical, graph theoretical, indicator variables and log P were used in the study. Furthermore, cluster analysis of variables was performed to identify groups of descriptors representing similar molecular features. Hierarchical PLS analyses were performed, where the scores of the significant components of either PLS or principle component analysis (PCA), performed separately on each cluster, were used as the variables for the top model. This reduced the number of the variables representing the larger clusters, leading to a similar number of descriptors for each distinct molecular feature. The results showed that the most important molecular properties for stronger ER binding affinity are molecular size and shape, the presence of a phenol moiety as well as other aromatic groups, hydrophobicity and presence of double bonds. The best PLS model obtained, in terms of predictive ability, was a hierarchical PLS model. However, a rigorous validation study showed that the MLR model using descriptors selected by stepwise regression has greater predictive power than the PLS models.

Validated models for predicting skin penetration from different vehicles

The permeability of a penetrant though skin is controlled by the properties of the penetrants and the mixture components, which in turn relates to the molecular structures. Despite the well-investigated models for compound permeation through skin, the effect of vehicles and mixture components has not received much attention. The aim of this Quantitative Structure Activity Relationship (QSAR) study was to develop a statistically validated model for the prediction of skin permeability coefficients of compounds dissolved in different vehicles. Furthermore, the model can help with the elucidation of the mechanisms involved in the permeation process. With this goal in mind, the skin permeability of four different penetrants each blended in 24 different solvent mixtures were determined from diffusion cell studies using porcine skin. The resulting 96 kp values were combined with a previous dataset of 288 kp data for QSAR analysis. Stepwise regression analysis was used for the selection of the most significant molecular descriptors and development of several regression models. The selected QSAR employed two penetrant descriptors of Wiener topological index and total lipole moment, boiling point of the solvent and the difference between the melting point of the penetrant and the melting point of the solvent. The QSAR was validated internally, using a leave-many-out procedure, giving a mean absolute error of 0.454 for the logkp value of the test set.

The effect of glycyrrhizin on the release rate and skin penetration of diclofenac sodium from topical formulations

The influence of glycyrrhizin extracted from Glycyrrhiza glabra var. glandulifera (licorice roots) on the percutaneous absorption of diclofenac sodium from sodium carboxymethylcellulose (NaCMC) gels or oil-in-water (o/w) emulsion was investigated. Skin permeation experiments were carried out using excised abdominal rat skin. The results showed that the efficiency of glycyrrhizin as an enhancer agent is greater in gel formulations than it is in the emulsions. The enhancer with the concentration of 0.1% w/w in gel increased diclofenac sodium flux value to tenfold compared with the control gel.

QSAR models for the prediction of plasma protein binding.

INTRODUCTION The prediction of plasma protein binding (ppb) is of paramount importance in the pharmacokinetics characterization of drugs, as it causes significant changes in volume of distribution, clearance and drug half life. This study utilized Quantitative Structure - Activity Relationships (QSAR) for the prediction of plasma protein binding. METHODS Protein binding values for 794 compounds were collated from literature. The data was partitioned into a training set of 662 compounds and an external validation set of 132 compounds. Physicochemical and molecular descriptors were calculated for each compound using ACD labs/logD, MOE (Chemical Computing Group) and Symyx QSAR software packages. Several data mining tools were employed for the construction of models. These included stepwise regression analysis, Classification and Regression Trees (CART), Boosted trees and Random Forest. RESULTS Several predictive models were identified; however, one model in particular produced significantly superior prediction accuracy for the external validation set as measured using mean absolute error and correlation coefficient. The selected model was a boosted regression tree model which had the mean absolute error for training set of 13.25 and for validation set of 14.96. CONCLUSION Plasma protein binding can be modeled using simple regression trees or multiple linear regressions with reasonable model accuracies. These interpretable models were able to identify the governing molecular factors for a high ppb that included hydrophobicity, van der Waals surface area parameters, and aromaticity. On the other hand, the more complicated ensemble method of boosted regression trees produced the most accurate ppb estimations for the external validation set.

The Use of Atomic Charges and Orbital Energies as Hydrogen-bonding-donor Parameters for QSAR Studies: Comparison of MNDO, AM1 and PM3 Methods

Hydrogen‐bonding, important in drug‐receptor interactions, also determines the solubility and partitioning of drugs between phases. It is, therefore, important to incorporate the effects of hydrogen‐bonding in studies of quantitative structure‐activity relationships (QSAR).

Modelling the effect of mixture components on permeation through skin

A vehicle influences the concentration of penetrant within the membrane, affecting its diffusivity in the skin and rate of transport. Despite the huge amount of effort made for the understanding and modelling of the skin absorption of chemicals, a reliable estimation of the skin penetration potential from formulations remains a challenging objective. In this investigation, quantitative structure-activity relationship (QSAR) was employed to relate the skin permeation of compounds to the chemical properties of the mixture ingredients and the molecular structures of the penetrants. The skin permeability dataset consisted of permeability coefficients of 12 different penetrants each blended in 24 different solvent mixtures measured from finite-dose diffusion cell studies using porcine skin. Stepwise regression analysis resulted in a QSAR employing two penetrant descriptors and one solvent property. The penetrant descriptors were octanol/water partition coefficient, logP and the ninth order path molecular connectivity index, and the solvent property was the difference between boiling and melting points. The negative relationship between skin permeability coefficient and logP was attributed to the fact that most of the drugs in this particular dataset are extremely lipophilic in comparison with the compounds in the common skin permeability datasets used in QSAR. The findings show that compounds formulated in vehicles with small boiling and melting point gaps will be expected to have higher permeation through skin. The QSAR was validated internally, using a leave-many-out procedure, giving a mean absolute error of 0.396. The chemical space of the dataset was compared with that of the known skin permeability datasets and gaps were identified for future skin permeability measurements.

The effect of structural QSAR parameters on skin penetration.

The permeability coefficients (log kp) of solutes through stratum corneum have been previously related to the octanol-water partition coefficients (log Poct) and solvatochromic parameters. In this study, permeation coefficient data are related to the theoretical chemistry-derived structural parameters and also molecular connectivity and molecular shape indices. The results show that these parameters are comparable with the solvatochromic parameters in correlation with log kp. Log Poct can be corrected by the theoretical parameters to explain permeation coefficients and the equilibrium distribution of compounds between the stratum corneum and water (log Km). Diffusion estimated from the expression log(D/h)=log kp-log Km, where D is the diffusion coefficient and h is the path length for diffusion was also analyzed successfully by the structural parameters.