Over the past decade we have witnessed the increasing sophistication of machine learning
algorithms applied in daily use from internet searches, voice recognition, social network …

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

QSAR. Despite this long tradition, machine learning methods gained substantial momentum
recently triggered by the success of deep learning in many application areas. 1 A wide …

The advancement and progress in technology and related techniques have created an
opportunity for progress in many scientific fields and various industries. Machine learning …

Background: Drug discovery, which is the process of discovering new candidate
medications, is very important for pharmaceutical industries. At its current stage, discovering …

Recently, using artificial intelligence (AI) in drug discovery has received much attention
since it significantly shortens the time and cost of developing new drugs. Deep learning (DL) …

The productivity of the pharmaceutical industry is on the decline. Failure rates in clinical
trials exceed 90% after therapies are tested in model organisms, and the cost to develop a …

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 …

Current pharmaceutical formulation development still strongly relies on the traditional trial-
and-error methods of pharmaceutical scientists. This approach is laborious, time-consuming …

Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …