Drug development is one of the most significant processes in the pharmaceutical industry.
Various computational methods have dramatically reduced the time and cost of drug …

The discovery and development of new medicines is expensive, time-consuming, and often
inefficient, with many failures along the way. Powered by artificial intelligence (AI), language …

Abstract Background The ChEMBL database is one of a number of public databases that
contain bioactivity data on small molecule compounds curated from diverse sources …

Drug toxicity evaluation is an essential process of drug development as it is reportedly
responsible for the attrition of approximately 30% of drug candidates. The rapid increase in …

The mission of translational science is to bring predictivity and efficiency to the development
and dissemination of interventions that improve human health. Ten years ago this year, the …

In silico toxicology is an emerging field. It gains increasing importance as research is aiming
to decrease the use of animal experiments as suggested in the 3R principles by Russell and …

Current gaps in drug safety sciences can result from the inability (1) to identify hazard across
multiple target organs,(2) to predict and risk assess with certainty against drug safety …

Various sources of information can be used to better understand and predict compound
activity and safety-related endpoints, including biological data such as gene expression and …

Introduction: Big-data-driven drug development resources and methodologies have been
evolving with ever-expanding data from large-scale biological experiments, clinical trials …

The application of artificial intelligence and machine learning (ML) methods is becoming
increasingly popular in computational toxicology and drug design; it is considered as a …