Artificial intelligence and specifically machine learning applications are nowadays used in a
variety of scientific applications and cutting-edge technologies, where they have a …

The aqueous solubility of active pharmaceutical ingredients is one of the most important
features to be considered during the development of parenteral formulations in the …

The ability to evaluate pure compound properties of various molecular species is an
important prerequisite for process simulation in general and in particular for computer-aided …

A pair of popular thermodynamic models for pharmaceutical applications, namely, the
perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state and the …

The bioavailability of poorly water-soluble active pharmaceutical ingredients (APIs) can be
improved via the formulation of an amorphous solid dispersion (ASD), where the API is …

The first evidence of native cyclodextrins fusion was registered using fast scanning
calorimetry (FSC) with heating rates up to 40,000 K s− 1. The endothermal effects, detected …

A profound understanding of the physicochemical properties of organic crystals is crucial for
topics from material science to drug discovery. Using molecular dynamics (MD) simulations …

Several approaches to predict and model drug solubility have been used in the drug
discovery and development processes during the last decades. Each of these approaches …

New drug candidates often require bio-enabling formation technologies such as lipid-based
formulations, solid dispersions, or nanosized drug formulations. Development of such more …

In response to the increasing application of machine learning (ML) across many facets of
pharmaceutical development, this pilot study investigated if ML, using artificial neural …