Temperature Dependence of the Solubility of Acetaminophen in Propylene Glycol + Ethanol Mixtures

A streamlined molecular-dynamics workflow for computing solubilities of molecular and ionic crystals

Computing the solubility of crystals in a solvent using atomistic simulations is notoriously challenging due to the complexities and convergence issues associated with free-energy methods, as well as the slow equilibration in direct-coexistence simulations. This paper introduces a molecular-dynamics workflow that simplifies and robustly computes the solubility of molecular or ionic crystals. This method is considerably more straightforward than the state-of-the-art, as we have streamlined and optimised each step of the process. Specifically, we calculate the chemical potential of the crystal using the gas-phase molecule as a reference state, and employ the S0 method to determine the concentration dependence of the chemical potential of the solute. We use this workflow to predict the solubilities of sodium chloride in water, urea polymorphs in water, and paracetamol polymorphs in both water and ethanol. Our findings indicate that the predicted solubility is sensitive to the chosen potential energy surface. Furthermore, we note that the harmonic approximation often fails for both molecular crystals and gas molecules at or above room temperature, and that the assumption of an ideal solution becomes less valid for highly soluble substances.

Comparative Drug Solubility Studies Using Shake-Flask Versus a Laser-Based Robotic Method

Drug solubility is of central importance to the pharmaceutical sciences, but reported values often show discrepancies. Various factors have been discussed in the literature to account for such differences, but the influence of manual testing in comparison to a robotic system has not been studied adequately before. In this study, four expert researchers were asked to measure the solubility of four drugs with various solubility behaviors (i.e., paracetamol, mesalazine, lamotrigine, and ketoconazole) in the same laboratory with the same instruments, method, and material sources and repeated their measurements after a time interval. In addition, the same solubility data were determined using an automated laser-based setup. The results suggest that manual testing leads to a handling influence on measured solubility values, and the results were discussed in more detail as compared to the automated laser-based system. Within the framework of unavoidable uncertainties of solubility testing, it is a possibility to combine minimal experimental testing that is preferably automated with mathematical modeling. That is a practical suggestion to support future pharmaceutical development in a more efficient way.

Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media

The solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen and phenacetin solubility data in neat and binary solvent mixtures was used for the development of a nonlinear deep machine learning model using new intuitive molecular descriptors derived from COSMO-RS computations. The literature dataset was augmented with results of new measurements in aqueous binary mixtures of 4-formylmorpholine, DMSO and DMF. The solubility values back-computed with the developed ensemble of neural networks are in perfect agreement with the experimental data, which enables the extensive screening of many combinations of solvents not studied experimentally within the applicability domain of the trained model. The final predictions were presented not only in the form of the set of optimal hyperparameters but also in a more intuitive way by the set of parameters of the Jouyban-Acree equation often used in the co-solvency domain. This new and effective approach is easily extendible to other systems, enabling the fast and reliable selection of candidates for new solvents and directing the experimental solubility screening of active pharmaceutical ingredients.

Accounting for the Presence of Molecular Clusters in Modeling and Interpreting Nucleation and Growth

The effect of molecular cluster formation on the estimation of kinetic parameters for primary nucleation and growth in different systems has been studied using computationally generated data and three sets of experimental data in the literature. It is shown that the formation of molecular clusters decreases the concentration of monomers and hence the thermodynamic driving force for crystallization, which consequently affects the crystallization kinetics. For a system exhibiting a strong tendency to form molecular clusters, accounting for cluster formation in a kinetic model is critical to interpret kinetic data accurately, for instance, to estimate the specific surface energy γ from a set of primary nucleation rates. On the contrary, for a system with negligible cluster formation, a consideration of cluster formation does not affect parameter estimation outcomes. Moreover, it is demonstrated that using a growth kinetic model that accounts for cluster formation allows the estimation of γ from typical growth kinetic data (i.e., de-supersaturation profiles of seeded batch crystallization), which is a novel method of estimating γ developed in this work. The applicability of the novel method to different systems is proven by showing that the estimated values of γ are closely comparable to the actual values used for generating the kinetic data or the corresponding estimates reported in the literature.

Solubility of paracetamol in ethanol by molecular dynamics using the extended Einstein crystal method and experiments

Li and co-workers [Li et al., J. Chem. Phys. 146, 214110 (2017)] have recently proposed a methodology to compute the solubility of molecular compounds from first principles, using molecular dynamics simulations. We revise and further explore their methodology that was originally applied to naphthalene in water at low concentration. In particular, we compute the solubility of paracetamol in an ethanol solution at ambient conditions. For the simulations, we used a force field that we previously reparameterized to reproduce certain thermodynamic properties of paracetamol but not explicitly its solubility in ethanol. In addition, we have determined the experimental solubility by performing turbidity measurements using a Crystal16 over a range of temperatures. Our work serves a dual purpose: (i) methodologically, we clarify how to compute, with a relatively straightforward procedure, the solubility of molecular compounds and (ii) applying this procedure, we show that the solubility predicted by our force field (0.085 ± 0.014 in mole ratio) is in good agreement with the experimental value obtained from our experiments and those reported in the literature (average 0.0585 ± 0.004), considering typical deviations for predictions from first principle methods. The good agreement between the experimental and the calculated solubility also suggests that the method used to reparameterize the force field can be used as a general strategy to optimize force fields for simulations in solution.

Inclusion Complexes of a New Family of Non-Ionic Amphiphilic Dendrocalix[4]arene and Poorly Water-Soluble Drugs Naproxen and Ibuprofen

The inclusion complexes of a new family of nonionic amphiphilic calix[4]arenes with the anti-inflammatory hydrophobic drugs naproxen (NAP) and ibuprofen (IBP) were investigated. The effects of the alkyl chain’s length and the inner core of calix[4]arenes on the interaction of the two drugs with the calix[4]arenes were explored. The inclusion complexes of Amphiphiles 1a–c with NAP and IBP increased the solubility of these drugs in aqueous media. The interaction of 1a–c with the drugs in aqueous media was investigated through fluorescence, molecular modeling, and ¹H-NMR analysis. TEM studies further supported the formation of inclusion complexes. The length of lipophilic alkyl chains and the intrinsic cyclic nature of cailx[4]arene derivatives 1a–c were found to have a significant impact on the solubility of NAP and IBP in pure water.