Quantitative adverse outcome pathway (qAOP) models for toxicity prediction N Spinu, MTD Cronin, SJ Enoch, JC Madden, AP Worth Archives of toxicology 94 (5), 1497-1510, 2020 | 112 | 2020 |
Development and analysis of an adverse outcome pathway network for human neurotoxicity N Spinu, A Bal-Price, MTD Cronin, SJ Enoch, JC Madden, AP Worth Archives of toxicology 93 (10), 2759-2772, 2019 | 99 | 2019 |
Derivation, characterisation and analysis of an adverse outcome pathway network for human hepatotoxicity E Arnesdotter, N Spinu, J Firman, D Ebbrell, MTD Cronin, T Vanhaecke, ... Toxicology 459, 152856, 2021 | 35 | 2021 |
Towards a qAOP framework for predictive toxicology-linking data to decisions A Paini, I Campia, MTD Cronin, D Asturiol, L Ceriani, TE Exner, W Gao, ... Computational Toxicology 21, 100195, 2022 | 30 | 2022 |
Probabilistic modelling of developmental neurotoxicity based on a simplified adverse outcome pathway network N Spīnu, MTD Cronin, J Lao, A Bal-Price, I Campia, SJ Enoch, ... Computational Toxicology 21, 100206, 2022 | 25 | 2022 |
Prediction of the neurotoxic potential of chemicals based on modelling of molecular initiating events upstream of the adverse outcome pathways of (developmental) neurotoxicity D Gadaleta, N Spīnu, A Roncaglioni, MTD Cronin, E Benfenati International Journal of Molecular Sciences 23 (6), 3053, 2022 | 17 | 2022 |
A scheme to evaluate structural alerts to predict toxicity–assessing confidence by characterising uncertainties MTD Cronin, FJ Bauer, M Bonnell, B Campos, DJ Ebbrell, JW Firman, ... Regulatory Toxicology and Pharmacology 135, 105249, 2022 | 13 | 2022 |
Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project A Furuhama, A Kitazawa, J Yao, CE Matos Dos Santos, J Rathman, ... SAR and QSAR in Environmental Research 34 (12), 983-1001, 2023 | 10 | 2023 |
A matter of trust: learning lessons about causality will make qAOPs credible N Spīnu, MTD Cronin, JC Madden, AP Worth Computational Toxicology 21, 100205, 2022 | 9 | 2022 |
A strategy to define applicability domains for read-across C Pestana, SJ Enoch, JW Firman, JC Madden, N Spīnu, MTD Cronin Computational Toxicology 22, 100220, 2022 | 8 | 2022 |
Modelling of quantitative Adverse Outcome Pathways N Spīnu PQDT-Global, 2021 | 4 | 2021 |
A Real-world Toxicity Atlas Shows that Adverse Events of Combination Therapies Commonly Result in Additive Interactions A Küēükosmanoglu, S Scoarta, M Houweling, N Spinu, T Wijnands, ... Clinical Cancer Research 30 (8), 1685-1695, 2024 | 3 | 2024 |
Will qAOPs modernise toxicology? MTD Cronin, N Spīnu, AP Worth Computational Toxicology 21, 100199, 2022 | 2 | 2022 |
The predictivity of QSARs for toxicity: Recommendations for improving model performance MTD Cronin, H Basiri, G Chrysochoou, SJ Enoch, JW Firman, N Spīnu, ... Computational Toxicology 33, 100338, 2025 | | 2025 |
Cyclosporin A toxicity on endothelial cells differentiated from induced pluripotent stem cells: Assembling an adverse outcome pathway Z Mazidi, M Wieser, N Spinu, A Weidinger, AV Kozlov, K Vukovic, ... Toxicology in Vitro 103, 105954, 2025 | | 2025 |
S29-03 GENESIS: Generative Exploration of NEurotoxicity Targets through SImilarity Assessment of SMILES N Spīnu, OJM Béquignon, D Gadaleta Toxicology Letters 399, S50-S51, 2024 | | 2024 |
Do we really need animal testing to keep us safe? T Capdevila, F Lahr, L Lukačević, N Marčetić, N Spinu | | |
Fluoride Action Network N Spinu, MTD Cronin, J Lao, A Bal-Price, I Campia, SJ Enoch, ... | | |
Computational Toxicology A Paini, I Campia, MTD Cronin, D Asturiol, L Ceriani, TE Exner, W Gao, ... | | |
Assessment of the Confidence of a Novel In Silico Classification Scheme for Environmental Toxicology MTD Cronin, F Bauer, DJ Ebbrell, JW Firman, S Gutsell, G Hodges, ... SETAC North America 41st Annual Meeting, 0 | | |