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

Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

Machine learning methods have been applied to many data sets in pharmaceutical research
for several decades. The relative ease and availability of fingerprint type molecular …

Machine learning (ML) and deep learning (DL) are a subset of artificial intelligence (AI) that
can automatically learn from data and can perform tasks such as predictions and decision …

Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …

In silico catalyst design is a grand challenge of chemistry. Traditional computational
approaches have been limited by the need to compute properties for an intractably large …

During drug development, safety is always the most important issue, including a variety of
toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial …

Blockade of the human ether-à-go-go-related gene (hERG) channel by small molecules
induces the prolongation of the QT interval which leads to fatal cardiotoxicity and accounts …

As expenditure on drug development increases exponentially, the overall drug discovery
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …

Adverse effects induced by drug–drug interactions may result in early termination of drug
development or even withdrawal of drugs from the market, and many drug–drug interactions …