Although abundant literature data are available on liquid-liquid phase equilibrium for select hydrocarbonwater systems at ambient or near ambient temperatures, a deficiency exists for data at elevated temperatures. In this study, we sought to (a) evaluate existing mutual hydrocarbon-water liquid-liquid equilibrium (LLE) data, (b) develop an experimental apparatus capable of measuring accurately the hydrocarbon-water (LLE) mutual solubilities, and (c) perform measurements on the benzene-water, toluene-water, and 3-methylpentane-water systems. A continuous flow apparatus was utilized to measure the LLE mutual solubilities at temperatures ranging from ambient to 500 K, which is near the three-phase critical end point of the benzene-water and toluene-water systems. The well-documented benzene-water system was used to validate the reliability of the sampling and analytical techniques employed. Generally, the present measurements showed adequate agreement with available literature data. An error propagation analysis for the three systems indicates maximum expected uncertainties of 4 % and 8 % in the water-phase and organic-phase solubility measurements, respectively. This study provides valuable LLE mutual solubility data and demonstrates the efficacy of the experimental apparatus in making accurate measurements.

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The permeation coefficient characterizes the ability of a chemical to penetrate the dermis, and the current study describes our efforts to develop structure-based models for the permeation coefficient. Specifically, we have integrated non-linear, quantitative structure-property relationship (QSPR) models, genetic algorithms (GAs), and neural networks to develop a reliable model. Case studies were conducted to investigate the effects of structural attributes on permeation using a carefully characterized database.Upon careful evaluation, a permeation coefficient data set consisting of 333 data points for 258 molecules was identified, and these data were added to our extensive thermophysical database. Of these data, permeation values for 160 molecular structures were deemed suitable for our modeling efforts. We employed established descriptors and constructed new descriptors to aid the development of a reliable QSPR model for the permeation coefficient. Overall, our new nonlinear QSPR model had an absolute-average percentage deviation, root-mean-square error, and correlation coefficient of 8.0%, 0.34, and 0.93, respectively. Cause-and-effect analysis of the structural descriptors obtained in this study indicates that that three size/shape and two polarity descriptors accounted for approximately 70% of the permeation information conveyed by the descriptors.

The nonrandom two-liquid (NRTL) model is utilized widely in phase equilibria calculations and employs three adjustable parameters (two interaction parameters and the non-randomness factor) that are determined through regression of experimental data for a specific binary vaporliquid equilibrium (VLE) system. The two interaction parameters (and) account for the difference between the pure-component liquid interactions (11 g and 22 g) and mixed-component liquid interactions (12 g and 21 g). The main disadvantage of the NRTL model is the strong correlation between the two parameters of the model. In this work, we propose a new modification to the NRTL model which addresses the limitation of the original model. The newly modified model recasts the formulation of the NRTL model parameters in such a way that the new parameters reflect two different characteristics. It also allows one of the two new model parameters to be generalized in terms of pure-component properties, which reduces the NRTL model to a one-parameter model. The original and modified NRTL models yield comparable precision in representing experimental equilibrium properties. Some of the benefits of our modification include easy generalizability of the parameters, ability to classify VLE behaviors based on a single model parameter and fewer convergence problems in parameter regressions.

Using chemical penetration enhancers (CPEs), transdermal drug delivery (TDD) offers an alternative route for insulin administration, wherein the CPEs reversibly reduce the barrier resistance of the skin. However, there is a lack of sufficient information concerning the effect of CPE chemical structure on insulin permeation. To address this limitation, we examined the effect of CPE functional groups on the permeation of insulin. A virtual design algorithm that incorporates quantitative structure-property relationship (QSPR) models for predicting the CPE properties was used to identify 43 potential CPEs. This set of CPEs was prescreened using a resistance technique, and the 22 best CPEs were selected. Next, standard permeation experiments in Franz cells were performed to quantify insulin permeation.Our results indicate that specific functional groups are not directly responsible for enhanced insulin permeation. Rather, permeation enhancement is produced by molecules that exhibit positive log K ow values and possess at least one hydrogen donor or acceptor. Toluene was the only exception among the 22 potential CPEs considered. In addition, toxicity analyses of the 22 CPEs were performed. A total of eight CPEs were both highly enhancing (permeability coefficient at least four times the control value) and non-toxic, five of which are new discoveries.