Artificial Intelligence in Drug Discovery

Introduction;

The History of Artificial Intelligence and Chemistry;

Chemical Topic Modelling – An Unsupervised Approach Originating from Text-mining to Organize Chemical Data;

Deep Learning and Chemical Data;

Concepts and Applications of Conformal Prediction in Computational Drug Discovery;

Non-applicability Domain. The Benefits of Defining “I don’t know” in Artificial Intelligence;

Predicting Protein-Ligand Binding-Affinities;

Virtual Screening with Convolutional Neural Networks;

Machine Learning in the Area of Molecular Dynamics Simulations;

Compound Design Using Generative Neural Networks;

Junction Tree Variational Autoencoder for Molecular Graph Generation;

AI via Matched Molecular Pair Analysis;

Molecular de novo Design Through Deep Generative Models;

Active Learning for Drug Discovery and Automated Data Curation;

Data-driven Prediction of Organic Reaction Outcomes;

ChemOS: an Orchestration Software to Democratize Autonomous Discovery;

Summary and Outlook