Machine learning in preclinical drug discovery

DB Catacutan, J Alexander, A Arnold… - Nature Chemical …, 2024‏ - nature.com
Drug-discovery and drug-development endeavors are laborious, costly and time consuming.
These programs can take upward of 12 years and cost US $2.5 billion, with a failure rate of …

A review of large language models and autonomous agents in chemistry

MC Ramos, CJ Collison, AD White - Chemical Science, 2025‏ - pubs.rsc.org
Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …

Do large language models understand chemistry? a conversation with chatgpt

CM Castro Nascimento… - Journal of Chemical …, 2023‏ - ACS Publications
Large language models (LLMs) have promised a revolution in answering complex questions
using the ChatGPT model. Its application in chemistry is still in its infancy. This viewpoint …

Equiformer: Equivariant graph attention transformer for 3d atomistic graphs

YL Liao, T Smidt - ar** molecules with text for generative pre-training
Z Liu, W Zhang, Y **a, L Wu, S **e, T Qin… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Generative pre-trained Transformer (GPT) has demonstrates its great success in natural
language processing and related techniques have been adapted into molecular modeling …

Scieval: A multi-level large language model evaluation benchmark for scientific research

L Sun, Y Han, Z Zhao, D Ma, Z Shen, B Chen… - Proceedings of the …, 2024‏ - ojs.aaai.org
Recently, there has been growing interest in using Large Language Models (LLMs) for
scientific research. Numerous benchmarks have been proposed to evaluate the ability of …

Are large language models superhuman chemists?

A Mirza, N Alampara, S Kunchapu… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Large language models (LLMs) have gained widespread interest due to their ability to
process human language and perform tasks on which they have not been explicitly trained …