Machine Learning

Sneha Pushpa Ramesan, Jasmitha Boovadira Poonacha, Dilan Pathirana, et al. Next-generation discovery: empowering organoid research with machine learning, artificial intelligence, and mathematical modeling. Trends in Biotechnology. 2026. doi:10.1016/j.tibtech.2026.01.009

Vishwanatha M. Rao, Serena Zhang, Brian S. Plosky, et al. Generalist biological artificial intelligence in modeling the language of life. Nature Biotechnology. 2026:1-16. doi:10.1038/s41587-026-03064-w

Carlos Anerillas, Gisela Altés, Katarina Gresova, et al. SenCat: Cataloging human cell senescence through multi-omic profiling of multiple senescent primary cell types. Molecular Cell. 2026. doi:10.1016/j.molcel.2026.05.017

Amit Gangwal, Antonio Lavecchia. Artificial intelligence in preclinical research: enhancing digital twins and organ-on-chip to reduce animal testing. Drug Discovery Today. 2025;30(5):104360. doi:10.1016/j.drudis.2025.104360

Marie Corradi, Thomas Luechtefeld, Alyanne M. de Haan, et al. The application of natural language processing for the extraction of mechanistic information in toxicology. Frontiers in Toxicology. 2024;6. doi:10.3389/ftox.2024.1393662

Pauric Bannigan, Zeqing Bao, Riley J. Hickman, et al. Machine learning models to accelerate the design of polymeric long-acting injectables. Nature Communications. 2023;14(1):35. doi:10.1038/s41467-022-35343-w

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

Thomas Hartung. ToxAIcology - The evolving role of artificial intelligence in advancing toxicology and modernizing regulatory science. ALTEX. 2023;40(4):559-570. doi:10.14573/altex.2309191

Evrim Erdemoglu, Tekin Ahmet Serel, Erdener Karacan, et al. Artificial intelligence for prediction of endometrial intraepithelial neoplasia and endometrial cancer risks in pre- and postmenopausal women. AJOG Global Reports. 2023;3(1):100154. doi:10.1016/j.xagr.2022.100154

Ivan Stelmakh, Charvi Rastogi, Ryan Liu, Shuchi Chawla, Federico Echenique, Nihar B. Shah. Cite-seeing and reviewing: A study on citation bias in peer review. PLOS ONE. 18(7):e0283980. doi:10.1371/journal.pone.0283980