Over the last two centuries, medicines have evolved from crude herbal and botanical
preparations into more complex manufacturing of sophisticated drug products and dosage …

The advancements of information technology and related processing techniques have
created a fertile base for progress in many scientific fields and industries. In the fields of drug …

De novo drug design is a computational approach that generates novel molecular structures
from atomic building blocks with no a priori relationships. Conventional methods include …

As artificial intelligence (AI) applications become more pervasive, it is critical to understand
how knowledge workers with different levels and types of experience can team with AI for …

Machine learning enables computers to address problems by learning from data. Deep
learning is a type of machine learning that uses a hierarchical recombination of features to …

Highlights•Deep learning technology has gained remarkable success.•We highlight the
recent applications of deep learning in drug discovery research.•Some popular deep …

A variety of machine learning methods such as naive Bayesian, support vector machines
and more recently deep neural networks are demonstrating their utility for drug discovery …

The task of predicting the interactions between drugs and targets plays a key role in the
process of drug discovery. There is a need to develop novel and efficient prediction …

With a massive influx of multimodality data, the role of data analytics in health informatics
has grown rapidly in the last decade. This has also prompted increasing interests in the …

Small-molecule drug discovery can be viewed as a challenging multidimensional problem in
which various characteristics of compounds—including efficacy, pharmacokinetics and …