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

In the past, conventional drug discovery strategies have been successfully employed to
develop new drugs, but the process from lead identification to clinical trials takes more than …

Introduction: Artificial intelligence (AI) has inspired computer-aided drug discovery. The
widespread adoption of machine learning, in particular deep learning, in multiple scientific …

Network pharmacology is an emerging area of systematic drug research that attempts to
understand drug actions and interactions with multiple targets. Network pharmacology has …

The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in
order to ensure safe application on living organisms. Artificial intelligence (AI) and machine …

In their seminal work on quantitative structure− activity relationship (QSAR), Hansch and co-
workers predicted in 1962 that Hammett functions and partition coefficients would become …

Because of the increasing demand of greener solvents, deep eutectic solvents (DES) have
just emerged as low-cost alternative solvents for a broad range of applications. However …

Given the rapid development of nanotechnology, it is crucial to understand the effects of
nanoparticles on living organisms. However, it is laborious to perform toxicological tests on a …

Robotics and automation provide potentially paradigm shifting improvements in the way
materials are synthesized and characterized, generating large, complex data sets that are …

Highlights•Review of the state-of-the-art in uncertainty quantification in drug
design.•Examples from drug-design settings are provided.•Impact on decision making is …