In Silico

Alexandra Maertens, Thomas Luechtefeld, Jean Knight, Thomas Hartung. Alternative methods go green! Green toxicology as a sustainable approach for assessing chemical safety and designing safer chemicals. ALTEX. 2024;41(1):3-19. doi:10.14573/altex.2312291

Madura KP Jayatunga, Margaret Ayers, Lotte Bruens, Dhruv Jayanth, Christoph Meier. How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessons. Drug Discovery Today. 2024;29(6):104009. doi:10.1016/j.drudis.2024.104009

Danilo Bzdok, Andrew Thieme, Oleksiy Levkovskyy, Paul Wren, Thomas Ray, Siva Reddy. Data science opportunities of large language models for neuroscience and biomedicine. Neuron. 2024. doi:10.1016/j.neuron.2024.01.016

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

Rizwan Qureshi, Muhammad Irfan, Taimoor Muzaffar Gondal, et al. AI in drug discovery and its clinical relevance. Heliyon. 2023;9(7). doi:10.1016/j.heliyon.2023.e17575

Weihai Ying. Phenomic Studies on Diseases: Potential and Challenges. Phenomics. 2023;3(3):285-299. doi:10.1007/s43657-022-00089-4

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

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

José Ramón Gutiérrez-Casares, Javier Quintero, Cristina Segú-Vergés, et al. In silico clinical trial evaluating lisdexamfetamine’s and methylphenidate’s mechanism of action computational models in an attention-deficit/hyperactivity disorder virtual patients’ population. Frontiers in Psychiatry. 2023;14:939650. doi:10.3389/fpsyt.2023.939650

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