Industry 4.0 has started to transform the manufacturing industries by embracing
digitalization, automation, and big data, aiming for interconnected systems, autonomous …

The urge of developing modern alternatives regarding industrial production has led to the
creation of novel techniques that help overcome critical disadvantages from traditional batch …

In this study, machine learning (ML) computations were carried out for description of drug
solubility in supercritical carbon dioxide. Supercritical solvent has been used in this work …

This research aims to examine a neural network (artificial intelligence) as an alternative
model to examine the neuromarketing phenomenon. Neuromarketing is comparatively new …

Cocrystal engineering is gaining interest across various disciplines since it can effectively
tune the properties of solid substances via noncovalent synthesis by introducing new …

Modeling drug solubility in a supercritical solvent was studied via a number of machine
learning approaches. The model solute simulated here was Lornoxicam, and its solubility at …

Computational analysis of drug solubility was carried out using machine learning approach.
The solubility of Decitabine as model drug in supercritical CO2 was studied as function of …

Neural network applications, as an emerging machine learning technology, are increasingly
being integrated into pharmaceutical manufacturing technologies, offering significant …

Twin-screw granulation has emerged as a key process in powder processing industries and
in the pharmaceutical sector to produce granules with controlled properties. This …

We developed a novel methodology for simulation and computation of species adsorption
on the surface of ordered nanoporous materials. The main aim was to develop an advanced …