3 citations · 7 across the 4 of their papers we have counts for
5 papers
Research Assistant: AstraZeneca's Agentic System for R&D
Piotr Grabowski, Mohamed Alameen, Jorge Bretones +16
We describe Research Assistant, an internal LLM-based system developed at AstraZeneca to help scientists and clinicians explore biomedical questions across a broad range of data so…
OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes
David Geleta, Andriy Nikolov, Mark ODonoghue +4
Duplication of nodes is a common problem encountered when building knowledge graphs (KGs) from heterogeneous datasets, where it is crucial to be able to merge nodes having the same…
ChemicalX: A Deep Learning Library for Drug Pair Scoring
Benedek Rozemberczki, Charles Tapley Hoyt, Anna Gogleva +9
In this paper, we introduce ChemicalX, a PyTorch-based deep learning library designed for providing a range of state of the art models to solve the drug pair scoring task. The prim…
A Unified View of Relational Deep Learning for Drug Pair Scoring
Benedek Rozemberczki, Stephen Bonner, Andriy Nikolov +3
In recent years, numerous machine learning models which attempt to solve polypharmacy side effect identification, drug-drug interaction prediction and combination therapy design ta…
MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy
Benedek Rozemberczki, Anna Gogleva, Sebastian Nilsson +3
We propose the molecular omics network (MOOMIN) a multimodal graph neural network used by AstraZeneca oncologists to predict the synergy of drug combinations for cancer treatment.…