biostudies-literatureUnknown207(2)Chandra MOak Ridge Institute for Science and EducationUS Food and Drug AdministrationNational Center for Toxicological ResearchUS FDAIn vitro to in vivo extrapolation (IVIVE) of toxicogenomics (TGx) data is essential for enhancing mechanism-based toxicity evaluations and minimizing animal use. However, translating in vitro findings to in vivo responses remains challenging. Generative adversarial networks (GANs) show potential in synthesizing gene expression data but often miss subtle, toxicologically relevant signals. We developed AIVIVE (artificial intelligence-aided IVIVE), a novel framework integrating GANs with local optimizers guided by biologically relevant gene modules to improve prediction accuracy. AIVIVE was trained using rat liver in vitro and in vivo transcriptomic data from the Open TG-GATEs (Toxicogenomics Project-Genomics-Assisted Toxicity Evaluation System) database. AIVIVE was evaluated using cosine simToxicological sciences : an official journal of the Society of Toxicology361-371https://www.ebi.ac.uk/biostudies/studies/S-EPMC12469192biostudies-literatureAIVIVE: a novel AI framework for enhanced in vitro to in vivo extrapolation (IVIVE) of toxicogenomics data.PMC12469192Chandra MLi TTong WfalseAIVIVE: a novel AI framework for enhanced in vitro to in vivo extrapolation (IVIVE) of toxicogenomics data.In vitro to in vivo extrapolation (IVIVE) of toxicogenomics (TGx) data is essential for enhancing mechanism-based toxicity evaluations and minimizing animal use. However, translating in vitro findings to in vivo responses remains challenging. Generative adversarial networks (GANs) show potential in synthesizing gene expression data but often miss subtle, toxicologically relevant signals. We developed AIVIVE (artificial intelligence-aided IVIVE), a novel framework integrating GANs with local optimizers guided by biologically relevant gene modules to improve prediction accuracy. AIVIVE was trained using rat liver in vitro and in vivo transcriptomic data from the Open TG-GATEs (Toxicogenomics Project-Genomics-Assisted Toxicity Evaluation System) database. AIVIVE was evaluated using cosine sim2025-01-01T00:00:00Z2025 Oct2026-06-03T21:31:50.981Z2026-05-01T03:11:21.168ZS-EPMC124691924069211310.1093/toxsci/kfaf100