During the development of a pharmaceutical formulation, a powerful tool is needed to extract
the key points from the complicated process parameters and material attributes. Artificial …

The solubility of organic molecules is crucial in organic synthesis and industrial chemistry; it
is important in the design of many phase separation and purification units, and it controls the …

Determining the aqueous solubility of molecules is a vital step in many pharmaceutical,
environmental, and energy storage applications. Despite efforts made over decades, there …

The discovery and development of drugs is a long and expensive process with a high
attrition rate. Computational drug discovery contributes to ligand discovery and optimization …

While accurate prediction of aqueous solubility remains a challenge in drug discovery,
machine learning (ML) approaches have become increasingly popular for this task. For …

Predicting both accurate and reliable solubility values has long been a crucial but
challenging task. In this work, surrogated model-based methods were developed to …

Drug discovery (DD) research is aimed at the discovery of new medications. Solubility is an
important physicochemical property in drug development. Active pharmaceutical ingredients …

Aqueous organic redox flow batteries offer an environmentally benign, tunable, and safe
route to large-scale energy storage. The energy density is one of the key performance …

Neural networks and deep learning have been successfully applied to tackle problems in
drug discovery with increasing accuracy over time. There are still many challenges and …

In this work, a novel strategy that combined molecular thermodynamic and machine learning
was proposed to accurately predict the solubility of drugs in various solvents. The strategy …