J. R. Dry

Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA Damage Response inhibitors

The paper introduces a network biology-driven simulation method to predict effective drug combinations and identify biomarkers for DNA Damage Response inhibitors using cancer cell avatars.

A statistical framework for assessing pharmacological response and biomarkers using uncertainty estimates

The paper introduces a statistical framework using uncertainty estimates to identify biomarkers from drug screening data, finding 24 known and 6 novel biomarkers in cancer cell lines.

Multi-task learning predicts drug combination synergy in cells and in the clinic

This paper develops predictive models for drug synergy using multi-task learning, showing high accuracy in predicting synergistic drug pairs and their clinical relevance.