Drug-discovery and drug-development endeavors are laborious, costly and time consuming.
These programs can take upward of 12 years and cost US $2.5 billion, with a failure rate of …

Artificial intelligence (AI) has played a vital role in computer-aided drug design (CADD). This
development has been further accelerated with the increasing use of machine learning (ML) …

To apply federated learning to drug discovery we developed a novel platform in the context
of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n 831472) …

Early in silico assessment of the potential of a series of compounds to deliver a drug is one
of the major challenges in computer-assisted drug design. The goal is to identify the right …

Highlights•Artificial intelligence (AI) is transforming the drug discovery process by providing
actionable insights from huge amount of data.•Deep-learning models, especially generative …

Biochemical and cell-based assays are essential to discovering and optimizing efficacious
and safe drugs, agrochemicals and cosmetics. However, false assay readouts stemming …

The success of language models, especially transformer-based architectures, has trickled
into other scientific domains, giving rise to the concept of “scientific language models” that …

Abstract New Approach Methodologies (NAMs) have ushered in a new era in the field of
toxicology, aiming to replace animal testing. However, despite these advancements, they …

Parkinson's Disease is a progressive neurodegenerative disorder afflicting almost 12 million
people. Increased understanding of its complex and heterogenous disease pathology …

In silico approaches have acquired a towering role in pharmaceutical research and
development, allowing laboratories all around the world to design, create, and optimize …