26 citations · 34 across the 4 of their papers we have counts for
4 papers
Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data
Jamie C. Overbeek, Alexander Partin, Thomas S. Brettin +21
Cancer drug response prediction (DRP) models present a promising approach towards precision oncology, tailoring treatments to individual patient profiles. While deep learning (DL)…
CACTUS: Chemistry Agent Connecting Tool-Usage to Science
Andrew D. McNaughton, Gautham Ramalaxmi, Agustin Kruel +3
Large language models (LLMs) have shown remarkable potential in various domains, but they often lack the ability to access and reason over domain-specific knowledge and tools. In t…
Scaffold-Based Multi-Objective Drug Candidate Optimization
Agustin Kruel, Andrew D. McNaughton, Neeraj Kumar
In therapeutic design, balancing various physiochemical properties is crucial for molecule development, similar to how Multiparameter Optimization (MPO) evaluates multiple variable…
De novo design of protein target specific scaffold-based Inhibitors via Reinforcement Learning
Andrew D. McNaughton, Mridula S. Bontha, Carter R. Knutson +2
Efficient design and discovery of target-driven molecules is a critical step in facilitating lead optimization in drug discovery. Current approaches to develop molecules for a targ…