James Yates

Bridging the gap between in vitro and in vivo: Dose and schedule predictions for the ATR inhibitor AZD6738

P. Jasper, J. Tolsma, Stephen Checkley, 2015, Scientific Reports.

A Spatially Resolved Mechanistic Growth Law for Cancer Drug Development Predicting Tumor Growing Fractions

G. Derks, Carina M. Dunlop, Adam Nasim, 2021, bioRxiv.

Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs

M. Chaplain, Sara J Hamis, G. Powathil, 2019, Bulletin of Mathematical Biology.

Preclinical Characterization of AZD5305, A Next-Generation, Highly Selective PARP1 Inhibitor and Trapper

M. O’Connor, S. Fawell, Glen Hawthorne, 2022, Clinical cancer research : an official journal of the American Association for Cancer Research.

Corrigendum: Bridging the gap between in vitro and in vivo: Dose and schedule predictions for the ATR inhibitor AZD6738

Claus Bendtsen, Stephen Checkley, Linda MacCallum, 2016, Scientific Reports.

Bridging in vitro and in vivo research via an agent-based modelling approach: predicting tumour responses to an ATR-inhibiting drug

M. Chaplain, J. Yates, Sara J Hamis, 2020 .

Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs

Mark A. J. Chaplain, Gibin G. Powathil, M. Chaplain, 2019, Bulletin of Mathematical Biology.

Radiation in Combination with Immune Checkpoint Blockade and DNA Damage Response Inhibitors in Mice: Dosage Optimization in MC38 Syngeneic Tumors via Modelling and Simulation

L. Aarons, H. Mistry, K. Ogungbenro, 2023, The Journal of Pharmacology and Experimental Therapeutics.