Modeling VLE and LLE of Deep Eutectic Solvents (DES) and Ionic Liquids (IL) Using PC-SAFT Equation of State. Part II

This study aims to use Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) to describe the phase behavior of systems containing DESs and ILs. The DESs are based on Tetrabutylammonium chloride ([N4444]Cl) and Tetrabutylammonium bromide (TBAB) as hydrogen bond acceptors, and levulinic acid (LevA) and Diethylene Glycol (DEG) as hydrogen bond donors in the mole ratio of 1:2 and 1:4, respectively. The predicted phase equilibrium data from PC-SAFT has been compared to those from COSMO-RS and NRTL predictions. ILs studied in this work are low viscosity ether-functionalized pyridinium-based ILs [EnPy][NTf2] and [CmPy][NTf2], while 1-(2-methoxyethyl)-1-methylpyrrolidiniumbis(trifluoromethylsulfonyl)-amide) ([COC2mPYR][NTf2]) and 1-propyl-3-methylimidazolium bis{trifluoromethylsulfonyl}imide ([Pmim][NTf2]) were used for the study of the LLE systems with n-heptane + thiophene and n-hexane + ethylbenzene, respectively. In the last part, mixtures of linear alkanes and perfluoroalkanes have been studied to predict the phase behavior of perfluoroalkylalkanes with their linear alkane counterparts and comparisons have been made against SAFT-Mie pair potential.

Predicting Deliquescence Relative Humidities of Crystals and Crystal Mixtures

The presence of water in the form of relative humidity (RH) may lead to deliquescence of crystalline components above a certain RH, the deliquescence RH (DRH). Knowing the DRH values is essential, e.g., for the agrochemical industry, food industry, and pharmaceutical industry to identify stability windows for their crystalline products. This work applies the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) to purely predict the DRH of single components (organic acids, sugars, artificial sweeteners, and amides) and multicomponent crystal mixtures thereof only based on aqueous solubility data of the pure components. The predicted DRH values very well agree with the experimental ones. In addition, the temperature influence on the DRH value could be successfully predicted with PC-SAFT. The DRH prediction also differentiates between formation of hydrates and anhydrates. PC-SAFT-predicted phase diagrams of hydrate-forming components illustrate the influence of additional components on the hydrate formation as a function of RH. The DRH prediction via PC-SAFT allows for the determining of the stability of crystals and crystal mixtures without the need for time-consuming experiments.

Multi-criteria Optimization for Parameterization of SAFT-type Equations of State for Water

Finding appropriate parameter sets for a given equation of state (EoS) to describe different properties of a certain substance is an optimization problem with conflicting objectives. Such problem is commonly addressed by single-criteria optimization in which the different objectives are lumped into a single goal function. We show how multi-criteria optimization (MCO) can be beneficially used for parameterizing equations of state. The Pareto set, which comprises a set of optimal solutions of the MCO problem, is determined. As an example, the perturbed-chain statistical associating fluid theory (PC-SAFT) EoS is used and applied to the description of the thermodynamic properties of water, focusing on saturated liquid density and vapor pressure. Different options to describe the molecular nature of water by the PC-SAFT EoS are studied and for all variants, the Pareto sets are determined, enabling a comprehensive assessment. When compared to literature models, Pareto optimization yields improved models.

Stability of Pharmaceutical Co-Crystals at Humid Conditions Can Be Predicted

Knowledge of the stability of pharmaceutical formulations against relative humidity (RH) is essential if they are to become pharmaceutical products. The increasing interest in formulating active pharmaceutical ingredients as stable co-crystals (CCs) triggers the need for fast and reliable in-silico predictions of CC stability as a function of RH. CC storage at elevated RH can lead to deliquescence, which leads to CC dissolution and possible transformation to less soluble solid-state forms. In this work, the deliquescence RHs of the CCs succinic acid/nicotinamide, carbamazepine/nicotinamide, theophylline/citric acid, and urea/glutaric acid were predicted using the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT). These deliquescence RH values together with predicted phase diagrams of CCs in water were used to determine critical storage conditions, that could lead to CC instability, that is, CC dissolution and precipitation of its components. The importance of CC phase purity on RH conditions for CC stability is demonstrated, where trace levels of a separate phase of active pharmaceutical ingredient or of coformer can significantly decrease the deliquescence RH. The use of additional excipients such as fructose or xylitol was predicted to decrease the deliquescence RH even further. All predictions were successfully validated by stability measurements at 58%, 76%, 86%, 93%, and 98% RH and 25 °C.

Relationship between thermodynamic perturbation and scaled particle theories for fused dimers fluids

Various approaches are reviewed that use scaled particle theories to describe dumbbell fluids made of tangent or overlapped hard spheres. Expressions encountered in the literature are written in a form similar to that presented in the thermodynamic perturbation theory introduced by Wertheim for chains and developed in statistical associating fluid theory (SAFT). Analogies and differences observed in these two types of theoretical descriptions allow one to propose alternative theoretical expressions to describe dumbbell fluids with overlapping spheres.

In-Silico Screening of Lipid-Based Drug Delivery Systems

Purpose This work proposes an in-silico screening method for identifying promising formulation candidates in complex lipid-based drug delivery systems (LBDDS). Method The approach is based on a minimum amount of experimental data for API solubilites in single excipients. Intermolecular interactions between APIs and excipients as well as between different excipients were accounted for by the Perturbed-Chain Statistical Associating Fluid Theory. The approach was applied to the in-silico screening of lipid-based formulations for ten model APIs (fenofibrate, ibuprofen, praziquantel, carbamazepine, cinnarizine, felodipine, naproxen, indomethacin, griseofulvin and glibenclamide) in mixtures of up to three out of nine excipients (tricaprylin, Capmul MCM, caprylic acid, Capryol™ 90, Lauroglycol™ FCC, Kolliphor TPGS, polyethylene glycol, carbitol and ethanol). Results For eight out of the ten investigated model APIs, the solubilities in the final formulations could be enhanced by up to 100 times compared to the solubility in pure tricaprylin. Fenofibrate, ibuprofen, praziquantel, carbamazepine are recommended as type I formulations, whereas cinnarizine and felodipine showed a distinctive solubility gain in type II formulations. Increased solubility was found for naproxen and indomethacin in type IIIb and type IV formulations. The solubility of griseofulvin and glibenclamide could be slightly enhanced in type IIIb formulations. The experimental validation agreed very well with the screening results. Conclusion The API solubility individually depends on the choice of excipients. The proposed in-silico-screening approach allows formulators to quickly determine most-appropriate types of lipid-based formulations for a given API with low experimental effort. Graphical abstract