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 …

With the financial requirements and high time associated with bringing a commercial drug to
the market, the application of computer-aided drug design has been recognized as a …

Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of
drug development in the costly late stage, it has been widely recognized that drug ADMET …

Highlights•Evolution of Bayer's in silico ADMET platform, modelling pharmacokinetic and
physicochemical endpoints.•Application of machine learning, deep learning and artificial …

For a new molecular entity (NME) to become a drug, it is not only essential to have the right
biological activity also be safe and efficient, but it is also required to have a favorable …

Innovations in information and communication technology infuse all branches of science,
including life sciences. Nevertheless, healthcare is historically slow in adopting …

In this article, we propose the deep neural network Adversarial Threshold Neural Computer
(ATNC). The ATNC model is intended for the de novo design of novel small-molecule …

A few decades ago, drug discovery and development were limited to a bunch of medicinal
chemists working in a lab with enormous amount of testing, validations, and synthetic …

Hetero-bifunctional PROteolysis TArgeting Chimeras (PROTACs) represent a new emerging
class of small molecules designed to induce polyubiquitylation and proteasomal-dependent …