Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Highlights•Artificial intelligence (AI) is transforming the drug discovery process by providing
actionable insights from huge amount of data.•Deep-learning models, especially generative …

Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …

Molecular discovery is a multi-objective optimization problem that requires identifying a
molecule or set of molecules that balance multiple, often competing, properties. Multi …

De novo drug design is a pivotal issue in pharmacology and a new area of focus in AI for
science research. A central challenge in this field is to generate molecules with specific …

The goal of drug discovery is to uncover new molecules with specific chemical properties
that can be used to cure diseases. With the accessibility of machine learning techniques, the …

Process synthesis experiences a disruptive transformation accelerated by artificial
intelligence. We propose a reinforcement learning algorithm for chemical process design …

Recently, we have released the de novo design platform REINVENT in version 2.0. This
improved and extended iteration supports far more features and scoring function …

Background: The lengthy and expensive process of develo** a novel medicine often takes
many years and entails a significant financial burden due to its poor success rate …

Reinforcement learning (RL) has been applied to various domains in computational
chemistry and has found wide‐spread success. In this review, we first motivate the …