Prediction of solubility of active pharmaceutical ingredients by semi- predictive Flory Huggins/Hansen model (original) (raw)
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Calculation of drug-like molecules solubility using predictive activity coefficient models
Fluid Phase Equilibria, 2012
The A-UNIFAC, UNIFAC, and NRTL-SAC models are used to predict solubility in pure solvents of a set of drug-like molecules. To apply A-UNIFAC, a new set of residual interaction parameters between the ACOH group and six other groups had to be estimated. The solute model parameters of NRTL-SAC were also estimated for this set of molecules. NRTL-SAC showed better performance at 298.15 K, with an average absolute deviation of 37.6%. Solubility dependence with temperature was also studied: all models presented average deviations around 40%. In general, there is an improvement given by the A-UNIFAC over the UNIFAC in aqueous systems, proving the importance of taking association into account.
Solubility Prediction of Drugs in Mixed Solvents Using Partial Solubility Parameters
Journal of Pharmaceutical Sciences, 2011
Solubility of drugs in binary and ternary solvent mixtures composed of water and pharmaceutical cosolvents at different temperatures were predicted using the Jouyban-Acree model and a combination of partial solubility parameters as interaction descriptors in the solution. The generally trained version of the model produced the overall mean percentage deviation values for the back-calculated solubility of drugs in binary solvents of 34.3% and the predicted solubilities in ternary solvent mixtures of 38.0%. In addition, the applicability of the trained model for predicting the solvent composition providing the maximum solubility of a drug was investigated. The results of collected solubility data of drugs in various mixed solvents and the newly measured solubility data of five drugs in ethanol + propylene glycol + water mixtures at 25 • C showed that the model provided acceptable predictions and could be used in the pharmaceutical industry.
Recent Advances in Thermo and Fluid Dynamics, 2015
In this chapter, the applicability of two predictive activity coefficient-based models will be examined. The experimental data from five different types of VLE (vaporliquid equilibrium) and VLLE (vapor-liquid-liquid equilibrium) systems that are common in industry are used for the evaluation. The nonrandom two-liquid segment activity coefficient (NRTL-SAC) and universal functional activity coefficient (UNI-FAC) were selected to model the systems. The various thermodynamic relations existing in the open literature will be discussed and used to predict the solubility of active pharmaceutical ingredients and other small organic molecules in a single or a mixture of solvents. Equations of states, the activity coefficient, and predictive models will be discussed and used for this purpose. We shall also present some of our results on solvent screening using a single and a mixture of solvents.
European Journal of Pharmaceutics and Biopharmaceutics, 2019
In this review we will discuss how computational methods, and in particular classical molecular dynamics simulations, can be used to calculate solubility of pharmaceutically relevant molecules and systems. To the extent possible, we focus on the non-technical details of these calculations, and try to show also the added value of a more thorough and detailed understanding of the solubilization process obtained by using computational simulations. Although the main focus is on classical molecular dynamics simulations, we also provide the reader with some insights into other computational techniques, such as the COSMO-method, and also discuss Flory-Huggins theory and solubility parameters. We hope that this review will serve as a valuable starting point for any pharmaceutical researcher, who has not yet fully explored the possibilities offered by computational approaches to solubility calculations.
The E and C model for predicting the solubility of drugs in pure solvents
International Journal of Pharmaceutics, 1996
The E and C model for hydrogen bonding is used together with nonspecific solubility parameters to predict the solubility of a Lewis base solute in a series of solvents of several chemical classes. A linear relationship between enthalpies of hydrogen bonding calculated from the Drago model and entropies obtained from a few experimental solubilities allows the prediction of the entropy contribution for the other solvents. Correct orders of magnitude are predicted in solvents of all polarities (from benzene to glycerin) which were not used to obtain the empirical relationships. The results suggest that the E and C model may be useful to reduce the experimental work usually needed for predicting solubility of drugs in pure solvents of different acid-base characteristics.
J. Phys. Chem. B, 2011
The objectives of this study were (i) to develop a computational model based on molecular dynamics technique to predict the miscibility of indomethacin in carriers (polyethylene oxide, glucose, and sucrose) and (ii) to experimentally verify the in silico predictions by characterizing the drug-carrier mixtures using thermoanalytical techniques. Molecular dynamics (MD) simulations were performed using the COMPASS force field, and the cohesive energy density and the solubility parameters were determined for the model compounds. The magnitude of difference in the solubility parameters of drug and carrier is indicative of their miscibility. The MD simulations predicted indomethacin to be miscible with polyethylene oxide and to be borderline miscible with sucrose and immiscible with glucose. The solubility parameter values obtained using the MD simulations values were in reasonable agreement with those calculated using group contribution methods. Differential scanning calorimetry showed melting point depression of polyethylene oxide with increasing levels of indomethacin accompanied by peak broadening, confirming miscibility. In contrast, thermal analysis of blends of indomethacin with sucrose and glucose verified general immiscibility. The findings demonstrate that molecular modeling is a powerful technique for determining the solubility parameters and predicting miscibility of pharmaceutical compounds.
Molecular Thermodynamic Modeling of Mixed Solvent Solubility
Industrial & Engineering Chemistry Research, 2010
A method based on statistical mechanical fluctuation solution theory for composition derivatives of activity coefficients is employed for estimating dilute solubilities of 11 solid pharmaceutical solutes in nearly 70 mixed aqueous and nonaqueous solvent systems. The solvent mixtures range from nearly ideal to strongly nonideal. The database covers a temperature range from 293 to 323 K. Comparisons with available data and other existing solubility methods show that the method successfully describes a variety of observed mixed solvent solubility behaviors using solute-solvent parameters from global regression of ternary data as well as predictions based on pure solvent solubilities with an average error of about 10% on mole fractions.
Industrial & Engineering Chemistry Research, 2016
In this work, the NRTL-SAC and the Pharma UNIFAC models are evaluated with respect to the capability of prediction of solid-liquid equilibria of pharmaceutical compounds in organic solvents. The original NRTL-SAC model is extended through the introduction of temperaturedependent binary interaction parameters, and the two versions of the model are parametrized using VLE data. The performance of the NRTL-SAC models for correlation and prediction of the solubility of eight medium-sized flexible pharmaceutical or pharmaceutically similar molecules in multiple pure, organic solvents is examined: risperidone, fenofibrate, fenoxycarb, tolbutamide, meglumine, butyl paraben, butamben and salicylamide. The performance of the Pharma UNIFAC model is evaluated using data for six of these compounds. In general, it is found that introducing a dependence on temperature to the binary interaction parameters of the NRTL-SAC model can improve its capability for modeling and prediction of the solubility of active pharmaceutical ingredients. For prediction of solubility data the Pharma UNIFAC model generally performs below the two NRTL-SAC models. Averaged over all evaluated systems where the solubility was predicted with each method, the root mean squared logarithmic error in predicted mole fraction solubility obtained for Pharma UNIFAC (30 systems) and for the original and the modified temperature-dependent forms of the NRTL-SAC model (29 systems) are 1.64, 1.17 and 1.09, respectively. Comparing only those systems for which all models were evaluated (18 systems), the RMSLE values are 1.42, 1.06 and 0.87, respectively.
Journal of Pharmaceutical Sciences, 1993
A modification of the extended Hansen method is used for estimating the solubility of sulfadiazine and other organic drug molecules in a number of individual solvents ranging from nonpolar to highly polar. The equations obtained for each drug involve the partial solubility parameters of the solvents and allow the prediction of solubility of these drugs in a new solvent. Furthermore, a number of drugs (e.g., sulfadiazine, sulfamethoxypyridazine, naphthalene, and some benzoic acid derivatives) are combined in a single expression including the ideal solubility of the drugs and the partial solubility parameters of the solvents. The equation fits the solubilities of these drugs in a wide variety of solvents and may be used to predict the solubility of other sulfonamides and benzoic acid derivatives in semipolar and highly polar solvents. The solvatochromic parameter approach is also used in models for predicting the solubility of single drugs in individual solvents. It was tested with multiple solutes as was the partial solubility parameter approach. However, the latter approach is superior; the parameters of the solubility parameter method are all statistically significant for drugs tested individually or together in a single equation, a condition that is not obtained with the solvatochromic model.
Experimental and computational screening models for prediction of aqueous drug solubility
Pharmaceutical Research, 2002
To devise experimental and computational models to predict aqueous drug solubility. Methods. A simple and reliable modification of the shake flask method to a small-scale format was devised, and the intrinsic solubilities of 17 structurally diverse drugs were determined. The experimental solubility data were used to investigate the accuracy of commonly used theoretical and semiexperimental models for prediction of aqueous drug solubility. Computational models for prediction of intrinsic solubility, based on lipophilicity and molecular surface areas, were developed. Results. The intrinsic solubilities ranged from 0.7 ng/mL to 6.0 mg/ mL, covering a range of almost seven log 10 units, and the values determined with the new small-scale shake flask method agreed well with published solubility data. Solubility data computed with established theoretical models agreed poorly with the experimentally determined solubilities, but the correlations improved when experimentally determined melting points were included in the models. A new, fast computational model based on lipophilicity and partitioned molecular surface areas, which predicted intrinsic drug solubility with a good accuracy (R 2 of 0.91 and RMSE tr of 0.61) was devised.