BACKGROUND AND THE PURPOSE OF THE STUDY Solubility of pharmaceuticals is still a challenging subject and solubilization using cosolvents is the most common technique used in the pharmaceutical industry. The purpose of this study was reporting and modeling the experimental molar solubility of pioglitazone hydrochloride (PGZ-HCl) in binary and ternary mixtures of ethanol (EtOH), N-methyl pyrrolid...

In this work we make predictions of several important molecular properties of academic and industrial importance to seek answers to two questions: 1) Can we apply efficient machine learning techniques, using inexpensive descriptors, to predict melting points to a reasonable level of accuracy? 2) Can values of this level of accuracy be usefully applied to predicting aqueous solubility? We presen...

In the present work, the Henderson-Hasselbalch (HH) equation has been employed for the development of a tool for the prediction of pH-dependent aqueous solubility of drugs and drug candidates. A new prediction method for the intrinsic solubility was developed, based on artificial neural networks that have been trained on a druglike PHYSPROP subset of 4548 compounds. For the prediction of acid/b...

Recombinant DNA technology is important in the mass production of proteins for academic, medical, and industrial use, and the prediction of the solubility of proteins is a significant part of it. However, the protein solubility when overexpressed in a host organism is difficult to predict. Thus, a model capable of accurately estimating the likelihood of proteins to form insoluble inclusion bodi...

This study investigates the influence of the solid-state properties melting point (T(m)), enthalpy of melting (DeltaH(m)) and entropy of melting (DeltaS(m)) of a drug on its intrinsic solubility (S(0)). For this purpose, 26 chemically and structurally diverse drugs covering the oral drug space were selected and the S(0), T(m), DeltaH(m) and DeltaS(m) were determined experimentally. The influenc...

This study proposes the SCRATCH model for the aqueous solubility estimation of a compound directly from its structure. The algorithm utilizes predicted melting points and predicted aqueous activity coefficients. It uses two additive, constitutive molecular descriptors (enthalpy of melting and aqueous activity coefficient) and two non-additive molecular descriptors (symmetry and flexibility). Th...

tant molecular property, playing a large role in the behavior of compounds in many areas of interest. Given the importance of solubility, a means of prediction based solely on molecular structure should prove a useful tool, as many compounds exist for which the solubility simply is not available. The solubility of chemicals and drugs in the water phase has an essential influence on the extent o...

Solubility is regarded as one of the key challenges in many drug discovery projects. Thus, it is essential to support lead finding and optimization efforts with appropriate solubility data. In silico solubility prediction remains challenging and therefore a screening assay is used as a first filter, followed by selected follow-up assays to reveal what causes the low solubility of a specific com...

The ability of two thermodynamic approaches to predict the solubility of solid compounds in hot pressurized water is studied and compared. The Regular Solution Theory, based on the solubility parameter concept, and UNIFACbased models were applied to calculate the solute activity coefficient and then, solubility predictions were compared with experimental data reported in the literature. The ana...