A General Treatment of Solubility. 3. Principal Component Analysis (PCA) of the Solubilities of Diverse Solutes in Diverse Solvents

Article discussing a general treatment of solubility and principle component analysis (PCA) of the solubilities of diverse solutes in diverse solvents

A General Treatment of Solubility 4. Description and Analysis of a PCA Model for Ostwald Solubility Coefficients

Article discussing a general treatment of solubility and a description and analysis of a principal component analysis (PCA) model for Ostwald solubility coefficients

The calculation of physicochemical descriptors and their application in predicting properties of drugs and other compounds.

The work presented may be divided into two main sections: The first section focuses on the important aspect of compound descriptor determination. The method by which descriptors are obtained indirectly through compound solubility in organic solvents and direct water-solvent partition measurements is illustrated by example for drug compounds. This approach is extended through the derivation of gas-water and water-solvent partition equations for the n-alcohols which in the future will be available for use in descriptor determination. Importantly, the equation coefficients are also interpreted to deduce various physicochemical properties of the homologous series of alcohols. An alternative method to assign descriptors is probed through reversed-phase HPLC. Measurements are recorded for a series of solutes on several bonded phases and multivariate analysis is used to investigate the interrelationship between columns in an effort to isolate the most suitable phases. The second section is concerned with application of the Abraham General Solvation Equation to examine processes of special interest in drug design; aqueous solubility and intestinal absorption. An algorithm to predict water solubility is obtained containing an additional cross-term which is found to compensate at least partly for a melting point correction term. The amended equation is shown to be comparable in accuracy to commercially available packages for a test set of 268 structurally diverse compounds. Of further importance in drug delivery is the process of intestinal absorption. An extensive literature search provides evaluated absorption data for a large set of drug compounds and forms a strong basis for subsequent QSAR analysis. Intestinal absorption is found to be comparable in humans and rat, and predominantly dependent on the hydrogen-bonding capability of the drug. The mechanism of absorption is considered through transformation of the percent absorption data to an overall rate constant

Quantitative Structure - Skin permeability Relationships

This paper reviews in silico models currently available for the prediction of skin permeability with the main focus on the quantitative structure-permeability relationship (QSPR) models. A comprehensive analysis of the main achievements in the field in the last decade is provided. In addition, the mechanistic models are discussed and comparative studies that analyse different models are discussed

Predicting hydrophobic solvation by molecular simulation : 2. new united-atom model for alkanes, alkenes and alkynes

Existing united-atom models for non-polar hydrocarbons lead to systematic deviations in predicted solvation free energies in hydrophobic solvents. In this paper, an improved set of parameters is proposed for alkane molecules that corrects this systematic deviation and accurately predicts solvation free energies in hydrophobic media, while simultaneously providing a very good description of pure liquid densities. The model is then extended to alkenes and alkynes, again yielding very accurate predictions of solvation free energies and densities for these classes of compounds. For alkynes in particular, this work represents the first attempt at a systematic parameterization using the united-atom approach. Averaging over all 95 solute/solvent pairs tested, the mean signed deviation from experimental data is very close to zero, indicating no systematic error in the predictions. The fact that predictions are robust even for relatively large molecules suggests that the new model may be applicable to solvation of non-polar macromolecules without accumulation of errors. The root mean squared deviation of the simulations is only 0.6 kJ/mol, which is lower than the estimated uncertainty in the experimental measurements. This excellent performance constitutes a solid basis upon which a more general model can be parameterized to describe solvation in both polar and non-polar environments

Predicting hydrophobic solvation by molecular simulation : 1. testing united-atom alkane models

We present a systematic test of the performance of three popular united-atom force fields – OPLS-UA, GROMOS and TraPPE – at predicting hydrophobic solvation, more precisely at describing the solvation of alkanes in alkanes. Gibbs free energies of solvation were calculated for 52 solute/solvent pairs from Molecular Dynamics simulations and thermodynamic integration making use of the IBERCIVIS volunteer computing platform. Our results show that all force fields yield good predictions when both solute and solvent are small linear or branched alkanes (up to pentane). However, as the size of the alkanes increases, all models tend to increasingly deviate from experimental data in a systematic fashion. Furthermore, our results confirm that specific interaction parameters for cyclic alkanes in the united-atom representation are required in order to account for the additional excluded volume within the ring. Overall, the TraPPE model performs best for all alkanes, but systematically underpredicts the magnitude of solvation free energies by about 6% (RMSD of 1.2 kJ/mol). Conversely, both GROMOS and OPLS-UA systematically overpredict solvation free energies (by ~13% and 15%, respectively). The systematic trends suggest that all models can be improved by a slight adjustment of their Lennard-Jones parameters

A universal segment approach for the prediction of the activity coefficient.

Doctor of Philosophy in Chemical Engineering. University of KwaZulu-Natal, Durban 2016.This study comprised an investigation into solid-liquid equilibrium prediction, measurement and modelling for active pharmaceutical ingredients, and solvents, employed in the pharmaceutical industry. Available experimental data, new experimental data, and novel measuring techniques, as well as existing predictive thermodynamic activity coefficient model revisions, were investigated. Thereafter, and more centrally, a novel model for the prediction of activity coefficients, at solid-liquid equilibrium, which incorporates global optimization strategies in its training, is presented. The model draws from the segment interaction (via segment surface area), approach in solidliquid equilibrium modelling for molecules, and extends this concept to interactions between functional groups. Ultimately, a group-interaction predictive method is proposed that is based on the popular UNIFAC-type method (Fredenslund et al. 1975). The model is termed the Universal Segment Activity Coefficient (UNISAC) model. A detailed literature review was conducted, with respect to the application of the popular predictive models to solid-liquid phase equilibrium (SLE) problems, involving structurally complex solutes, using experimental data available in the literature (Moodley et al., 2016 (a)). This was undertaken to identify any practical and theoretical limitations in the available models. Activity coefficient predictions by the NRTL-SAC ((Chen and Song 2004), Chen and Crafts, 2006), UNIFAC (Fredenslund et al., 1975), modified UNIFAC (Dortmund) (Weidlich and Gmehling, 1987), COSMO-RS (OL) (Grensemann and Gmehling, 2005), and COSMOSAC (Lin and Sandler, 2002), were carried out, based on available group constants and sigma profiles, in order to evaluate the predictive capabilities of these models. The quality of the models is assessed, based on the percentage deviation between experimental data and model predictions. The NRTL-SAC model is found to provide the best replication of solubility rank, for the cases tested. It, however, was not as widely applicable as the majority of the other models tested, due to the lack of available model parameters in the literature. These results correspond to a comprehensive comparison conducted by Diedrichs and Gmehling (2011). After identifying the limitations of the existing predictive methods, the UNISAC model is proposed (Moodley et al, 2015 (b)). The predictive model was initially applied to solid-liquid systems containing a set of 18 structurally diverse, complex pharmaceuticals, in a variety of solvents, and compared to popular qualitative solubility prediction methods, such as NRTLSAC and the UNIFAC based methods. Furthermore, the Akaike Information Criterion (AIC) (Akaike, 1974) and Focused Information Criterion (FIC) (Claeskens and Hjort, 2003) were used to establish the relative quality of the solubility predictions. The AIC scores recommend the UNISAC model for over 90% of the test cases, while the FIC scores recommend UNISAC in over 75% of the test cases. The sensitivity of the UNISAC model parameters was highlighted during the initial testing phase, which indicated the need to employ a more rigorous method of determining parameters of the model, by optimization to the global minimum. It was decided that the Krill Herd algorithm optimization technique (Gandomi and Alavi, 2012), be employed to accomplish this. To verify the suitability of this decision, the algorithm was applied to phase stability (PS) and phase equilibrium calculations in non-reactive (PE) and reactive (rPE) systems, where global minimization of the total Gibbs energy is necessary. The results were compared to other methods from the literature (Moodley et al., 2015 (c)). The Krill Herd algorithm was found to reliably determine the desired global optima in PS, PE and rPE problems. The algorithm outperformed or matched all other methods considered for comparison, including swarm intelligence and genetic algorithms, with an average success rate of 89.5 %, and with an average number of function evaluations of 1406. The UNISAC model was then reviewed, and extended, to incorporate the significantly more detailed group fragmentation scheme of Moller et al. (2008), to improve the range of application of the model. New UNISAC segment group area parameters that were obtained by data fitting, using the Krill Herd Algorithm as an optimization tool, were calculated. This Extended UNISAC model was then used to predict SLE compositions, or temperatures, of a large volume of experimental binary and ternary system data, available in the literature, (over 4000 data points), and was compared to predictions by the UNIFAC-based and COSMO-based models (Moodley et al., 2016 (d)). The AIC scores suggest that the Extended UNISAC model is superior to the original UNIFAC, modified UNIFAC (Dortmund) (2013), COSMO-RS(OL), and COSMO-SAC models, with relative AIC scores of 1.95, 4.17, 2.17 and 2.09. In terms of percentage deviations alone between experimental and predicted values, the modified UNIFAC (Dortmund) model, and original UNIFAC models, proved superior at 21.03% and 29.03% respectively; however, the Extended UNISAC model was a close third at 32.99%. As a conservative measure to ensure that inter-correlation of the training set did not occur, previously unmeasured data was desired as a test set, to verify the ability of the Extended UNISAC model to estimate data outside of the training set. To accomplish this, SLE measurements were conducted for the systems diosgenin/ estriol/ prednisolone/ hydrocortisone/ betulin and estrone. These measurements were undertaken in over 10 diverse organic solvents, and water, at atmospheric pressure, within the temperature range 293.2-328.2 K, by employing combined digital thermal analysis and thermal gravimetric analysis, to determine compositions at saturation (Moodley et al., 2016 (e), Moodley et al., 2016 (f), Moodley et al., 2016 (g)). This previously unmeasured test set data was compared to predictions by the Extended UNISAC, UNIFAC-based and COSMO-based methods. It was found that the Extended UNISAC model can qualitatively predict the solubility in the systems measured (where applicable), comparably to the other popular methods tested. The desirable advantage is that the number of model parameters required to describe mixture activities is far lower than for the group contribution and COSMO-based methods. Future developments of the Extended UNISAC model were then considered, which included the preliminary testing of alternate combinatorial expressions, to better account for size-shape effects on the activity coefficient. The limitations of the Extended UNISAC model are also discussed

The Formation of Pharmaceutical Co-crystals by Spray Drying. An Investigation into the Chemical and Physical Factors Affecting the Production of Pharmaceutical Co-crystals by Fast Evaporation and Spray Drying

Crystal engineering study using spray dryer was performed for scale-up and rapid, continuous crystallisation of co-crystals from solution. The study emphasise on developing co-crystals of two structurally similar compounds, caffeine (CAF) and theophylline (THEO) with various di-carboxylic acids. The incongruently soluble pair of CAF and THEO with di-carboxylic acids acquires large solubility difference which is important to consider for its utility in product development. Based on previous assumption that maleic acid (MAL) elevates CAF’s solubility; solubility of the two similar compounds was tested in various dicarboxylic acids. Other solubility enhancement strategies such as introduction of surfactant and binary solvents were also scrutinised. A kinetically similar bench-scale technique, rotary evaporator (rotavap) was investigated as a pre-screening tool for the production of co-crystals via spray drying. Furthermore, various process parameters within the spray dryer were optimised to control the kinetic conditions which influence co-crystallisation and quality of the product. Another polymorphic co-crystal pair, CBZ (carbamazepine) and SAC (saccharin) was examined in various solvents and its degradation was evaluated over a period of few months. In this study, a two-step conversion of CBZ into its degradate was hypothesised. Rotavap delivered a true reflection of co-crystal favoured via spray drying apart from co-crystal pairs depicting polymorphism. Spray dryer offered a unique environment favouring metastable forms of co-crystals irrespective of the starting component stoichiometry; generating CAF:MAL 2:1. However, due to process limitation and solubility constraint, the impurity of CAF in CAF:MAL 2:1 co-crystals could not be abolished

Investigating Anions and Hydrophobicity of Deep Eutectic Solvents by Experiment and Computational Simulation

Deep eutectic solvents are a new generation of ionic liquid-like solvents formed by combining hydrogen bond acceptor with hydrogen bond donor which result in the depression of the melting point of the solvent. Like ionic liquids, anions play a critical role in tuning the polarity, physicochemical properties, and thermodynamic behavior of deep eutectic solvent (DES). Choline chloride is the most widely used quaternary ammonium salt (QAS) in the literature and has remarkable advantages from reduced cost to low toxicity and volatility. Choline bromide and choline iodide are other QAS that have not been used often for DES synthesis and applications, probably with the opinion that chlorides form stronger hydrogen bonds. Developing new DES from these anions will broaden the scope of green solvents selection for diverse applications. The first objective of this dissertation looked into the synthesis and characterization of DES from choline chloride, choline bromide, and choline iodide with malic acid, malonic acid, and urea. Also, we studied the thermodynamic behavior of the solvents by measuring their vapor pressure, density, and infinite activity coefficient in polar and nonpolar solvents. The results show that choline bromide can sometimes be used to replace choline chloride because both QAS share comparable physicochemical behavior. In most cases, choline iodide forms weaker hydrogen bonding with the donors leading to the formation of a solid at room temperature. Nevertheless, all the solvents have melting temperature below 100℃. In summary, DES can be synthesized from the choline cation bonded with the halides, with the melting point and nature of the solvent dependent on the hydrogen bond donor (HBD). Secondly, despite the rapid rise in publications and applications since their inception in 2001, most of the DES synthesized are generally hydrophilic. The low cost, low toxicity, and bioavailability of DES make the solvent green and sustainable for diverse applications. Conversely, the hydrophilicity of DES practically limits their application to only polar compounds, which is a major drawback of the solvent. For the past three years, hydrophobic deep eutectic solvents (HDES) have emerged as alternative extractive media capable of extracting nonpolar molecules from aqueous environments. In chapter three of this dissertation, the general objective was to design a cost-effective hydrophobic DES from choline chloride and fatty acids. Varying the alkyl chain of the fatty acid broadened our understanding about the role of HBD in DES and also helped in the tunability of the HDES polarity. Due to the infancy of HDES, for the first time, this dissertation expands on the design, synthesis, and physicochemical characterization of HDES developed from choline chloride and fatty acids. To understand the hydrogen-bonding pattern of HDES, a multivariate unsupervised principal component analysis was used to cluster HDES by using known DES as a control. The HDES was able to extract about 70% of piperine, a bioactive compound from Piper nigrum. In the future, it is believed that HDES could replace the majority of toxic organic solvents used for analytical purposes. Lastly, the electronic and molecular properties of the HDES synthesized were studied by using a solvatochromic molecular probes and a hybrid density functional theory at 6-31G (d) basis set. The empirical polarity assay and quantum theoretical calculations showed that decreasing the alkyl chain length of the hydrogen bond donor increases viscosity of the DES. Optimization of the DES molecular geometry indicates a reduced bond angle between the C15-O16-H17 atoms in choline chloride, signifying a change in electronegativity of the central atom (O16) during DES formation. From our results, we predict a possible molecular reorientation between the donor and the acceptor molecules during DES formation. The combined theoretical calculations and experimental approaches are useful to establish clear correlations between electronic parameters and physiochemical parameters like polarity, viscosity, and stability of carboxylic acid-DES and can be extended to other conventional solvents