Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

Recently, research on the development of artificial intelligence (AI)-based computational
toxicology models that predict toxicity without the use of animal testing has emerged …

The escalating use of novel chemicals and nanomaterials (NMs) across diverse sectors
underscores the need for advanced risk assessment methods to safeguard human health …

Abstract Three-dimensional (3D) printing is drastically redefining medicine production,
offering digital precision and personalized design opportunities. One emerging 3D printing …

This study focuses on the development of a machine learning ensemble approach for the
classification of Beta-Secretase 1 (BACE1) inhibitors in Quantitative Structure-Activity …

In modern drug discovery, the combination of chemoinformatics and quantitative structure–
activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling …

This study aimed to provide insights into the risk posed by psychopharmaceuticals and illicit
drugs in European surface waters, and to identify current knowledge gaps hampering this …

The prediction of compound properties from chemical structure is a main task for machine
learning (ML) in medicinal chemistry. ML is often applied to large data sets in applications …

LNC (leaf nitrogen content) in crops is significant for diagnosing the crop growth status and
guiding fertilization decisions. Currently, UAV (unmanned aerial vehicles) remote sensing …

Fungal infections or mycosis cause a wide range of diseases in humans and animals. The
incidences of community acquired; nosocomial fungal infections have increased …