| Bridging the gap between in vitro and in vivo: dose and schedule predictions for the ATR inhibitor AZD6738 S Checkley, L MacCallum, J Yates, P Jasper, H Luo, J Tolsma, ... Scientific reports 5 (1), 1-12, 2015 | 68 | 2015 |
| Demonstration of the feasibility of predicting the flow of pharmaceutically relevant powders from particle and bulk physical properties H Barjat, S Checkley, T Chitu, N Dawson, A Farshchi, A Ferreira, ... Journal of pharmaceutical innovation 16, 181-196, 2021 | 24 | 2021 |
| Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity LJ Gardiner, AP Carrieri, J Wilshaw, S Checkley, EO Pyzer-Knapp, ... Scientific reports 10 (1), 9522, 2020 | 18 | 2020 |
| Combining human cell line transcriptome analysis and Bayesian inference to build trustworthy machine learning models for prediction of animal toxicity in drug development LJ Gardiner, AP Carrieri, J Wilshaw, S Checkley, EO Pyzer-Knapp, ... arXiv preprint arXiv:1911.04374, 2019 | | 2019 |
| Establishment of intestinal free mucus PK-efficacy relationship for gastrointestinal limited drugs J Zhang, C Bendtsen, S Checkley, B Zhang, P Liu, D Zhang, Z Cheng Drug Metabolism and Pharmacokinetics 1 (32), S92, 2017 | | 2017 |
| Bridging the gap between in vitro and in vivo: Dose and schedule predictions for the ATR inhibitor AZD6738 (vol 5, 13545, 2015) S Checkley, L MacCallum, J Yates, P Jasper, H Luo, J Tolsma, ... SCIENTIFIC REPORTS 6, 2016 | | 2016 |
| Engineering tuneable gene circuits in yeast S Checkley PQDT-UK & Ireland, 2015 | | 2015 |
| 251 A combined in vitro and mathematical modelling approach for understanding the impact of an inhibitor of ATR on DNA damage and repair after ionising radiation J Yates, S Checkley, L MacCallum, R Odedra, J Barnes, A Lau European Journal of Cancer, 84, 2014 | | 2014 |
