In Silico

Thomas Hartung. Artificial intelligence as the new frontier in chemical risk assessment. Frontiers in Artificial Intelligence. 2023;6:1269932. doi:10.3389/frai.2023.1269932

Breanne Kincaid, Przemyslaw Piechota, Emily Golden, Mikhail Maertens, Thomas Hartung, Alexandra Maertens. Using in silico tools to predict flame retardant metabolites for more informative exposomics-based approaches. Frontiers in Toxicology. 2023;5:1216802. doi:10.3389/ftox.2023.1216802

Bilal Shaker, Sajjad Ahmad, Jingyu Lee, Chanjin Jung, Dokyun Na. In silico methods and tools for drug discovery. Computers in Biology and Medicine. 2021;137:104851. doi:10.1016/j.compbiomed.2021.104851

Simone Brogi, Teodorico Castro Ramalho, Kamil Kuca, José L. Medina-Franco, Marian Valko. Editorial: In silico Methods for Drug Design and Discovery. Frontiers in Chemistry. 2020;8. https://www.frontiersin.org/articles/10.3389/fchem.2020.00612.

Eduardo Habib Bechelane Maia, Letícia Cristina Assis, Tiago Alves de Oliveira, Alisson Marques da Silva, Alex Gutterres Taranto. Structure-Based Virtual Screening: From Classical to Artificial Intelligence. Frontiers in Chemistry. 2020;8. https://www.frontiersin.org/articles/10.3389/fchem.2020.00343.

Lauro Ribeiro de Souza Neto, José Teófilo Moreira-Filho, Bruno Junior Neves, et al. In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery. Frontiers in Chemistry. 2020;8. https://www.frontiersin.org/articles/10.3389/fchem.2020.00093.

Maha Thafar, Arwa Bin Raies, Somayah Albaradei, Magbubah Essack, Vladimir B. Bajic. Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities. Frontiers in Chemistry. 2019;7. https://www.frontiersin.org/articles/10.3389/fchem.2019.00782.

Janet Piñero, Laura I. Furlong, Ferran Sanz. In silico models in drug development: where we are. Current Opinion in Pharmacology. 2018;42:111-121. doi:10.1016/j.coph.2018.08.007

Elisa Passini, Oliver J. Britton, Hua Rong Lu, et al. Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity. Frontiers in Physiology. 2017;8. https://www.frontiersin.org/articles/10.3389/fphys.2017.00668.

S Ekins, J Mestres, B Testa. In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. British Journal of Pharmacology. 2007;152(1):9-20. doi:10.1038/sj.bjp.0707305