Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?

Assessing the impact of generative AI on medicinal chemistry

(2020) W. Patrick Walters et al.   NATURE BIOTECHNOLOGY

Deep learning enables rapid identification of potent DDR1 kinase inhibitors

(2019) Alex Zhavoronkov et al.   NATURE BIOTECHNOLOGY

Artificial Intelligence for Clinical Trial Design

(2019) Stefan Harrer et al.   TRENDS IN PHARMACOLOGICAL SCIENCES

Adversarial Threshold Neural Computer for Molecular de Novo Design

(2018) Evgeny Putin et al.   MOLECULAR PHARMACEUTICS

3D Molecular Representations Based on the Wave Transform for Convolutional Neural Networks

(2018) Denis Kuzminykh et al.   MOLECULAR PHARMACEUTICS

Unexplored therapeutic opportunities in the human genome

(2018) Tudor I. Oprea et al.   NATURE REVIEWS DRUG DISCOVERY

Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery

(2018) Daniil Polykovskiy et al.   MOLECULAR PHARMACEUTICS

Causality modeling for directed disease network

(2016) Sunjoo Bang et al.   BIOINFORMATICS

A comprehensive map of molecular drug targets

(2016) Rita Santos et al.   NATURE REVIEWS DRUG DISCOVERY

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology

(2016) Artur Kadurin et al.   Oncotarget

COMPARISON AND ENUMERATION OF CHEMICAL GRAPHS

(2013) Tatsuya Akutsu et al.   Computational and Structural Biotechnology Journal

Too many roads not taken

(2011) Aled M. Edwards et al.   NATURE

Understanding drug-likeness

(2011) Oleg Ursu et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

A manifesto for clinical pharmacology from principles to practice

(2010) Jeffrey K. Aronson   BRITISH JOURNAL OF CLINICAL PHARMACOLOGY

Model-Free Drug-Likeness from Fragments

(2010) Oleg Ursu et al.   Journal of Chemical Information and Modeling