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 …

Graph neural networks (GNN) has been considered as an attractive modelling method for
molecular property prediction, and numerous studies have shown that GNN could yield …

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 …

Artificial Intelligence revolutionizes the drug development process that can quickly identify
potential biologically active compounds from millions of candidate within a short period. The …

Absorption, distribution, metabolism, and excretion (ADME), which collectively define the
concentration profile of a drug at the site of action, are of critical importance to the success of …

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

Motivation The absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drugs
plays a key role in determining which among the potential candidates are to be prioritized. In …

Machine learning approaches were introduced for better or comparable predictive ability
than statistical analysis to predict postoperative outcomes. We sought to compare 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 …