Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive
abilities and to address difficult healthcare challenges including complex biological …

Abstract Machine learning (ML) promises to tackle the grand challenges in chemistry and
speed up the generation, improvement and/or ordering of research hypotheses. Despite the …

Therapeutics machine learning is an emerging field with incredible opportunities for
innovatiaon and impact. However, advancement in this field requires formulation of …

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

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

This work introduces a method to tune a sequence-based generative model for molecular de
novo design that through augmented episodic likelihood can learn to generate structures …

In the past few years, de novo molecular design has increasingly been using generative
models from the emergent field of Deep Learning, proposing novel compounds that are …

Drug discovery based on artificial intelligence has been in the spotlight recently as it
significantly reduces the time and cost required for developing novel drugs. With the …

Deep learning methods applied to drug discovery have been used to generate novel
structures. In this study, we propose a new deep learning architecture, LatentGAN, which …

A major challenge in computational chemistry is the generation of novel molecular structures
with desirable pharmacological and physiochemical properties. In this work, we investigate …