Announcement • Jun 30
VivoSim Labs, Inc. announced delayed annual 10-K filing On 06/29/2026, VivoSim Labs, Inc. announced that they will be unable to file their next 10-K by the deadline required by the SEC. VIVS
Live News • Jun 30
VivoSim Labs AI Models Top Traditional Testing in Liver Toxicity at Major Conference VivoSim Labs presented new data at the European Society of Toxicology’s annual conference showing its AI-enabled NAMkind Liver and Intestine models achieved over 90% sensitivity in predicting liver toxicity and reduced false positives compared with traditional animal testing.
The company says more accurate liver tox prediction can help pharmaceutical clients avoid costly late-stage drug failures, and the data aligns with U.S. FDA encouragement for human-relevant new approach methodologies, which could support wider use of VivoSim’s testing platforms.
VivoSim Labs shares last closed at $1.06, with the stock down 43.6% year to date.
If regulators and drug developers continue to lean into NAM-based approaches, VivoSim’s technology could become more embedded in preclinical workflows. The commercial outcome will depend on how quickly pharma customers integrate these models into existing programs and how the company prices and scales the service. Announcement • Jun 29
Vivosim Labs Demonstrates Superiority of Ai-Enabled Namkind Liver and Intestine Platforms in Liver Toxicity Prediction At European Toxicology Meeting VivoSim Labs, Inc. announced that data demonstrating the power of its advanced 3D human tissue models will be featured in two presentations at the European Society of Toxicology’s annual conference. The presentations collectively showcase the best-in-industry predictive power of VivoSim's proprietary AI-enabled NAMkind Liver and NAMkind GI platforms. In liver toxicology testing, across a set of compounds where animal models and traditional methods provide 50% to 65% sensitivity, VivoSim’s models provided greater than 90% sensitivity at detecting true positives for liver toxicity. Whereas current methodologies including animal in vivo testing can result in greater than 10% false positives, VivoSim’s liver toxicology methods result in fewer than 5% false positives. The United States Food and Drug Administration is actively encouraging human-relevant NAMs in place of animal studies, a push that is resulting in greater pharma demand for new technologies. VivoSim’s novel models offer perhaps the most predictive tool to make FDA’s vision a reality. VivoSim’s superior results are achieved by a combination of the best biological model with the most representative primary human cell types, leveraging multiple endpoints as readouts for best prediction, and training AI prediction models with multiple endpoints that provide a rich data set, yielding high prediction accuracy. In addition to testing traditional oral pill small molecules, VivoSim is establishing competitive advantages across new biotech modalities such as antibodies, siRNA, and gene therapies. The company has done extensive testing of Antibody Drug Conjugates (ADCs), with comparable accuracy results in terms of predicting the clinical profiles of ADCs for liver toxicity and diarrhea. Globally, hundreds of ADC candidates are now in active clinical development against over 50 molecular targets — 41 of them already in Phase III — and the pipeline remains overwhelmingly oncology-focused, led by HER2- and TROP2-directed programs in breast and lung cancer. Therapies still fail in human trials, most often on safety or efficacy. The findings show that the Company’s human-relevant models can predict liver and gastrointestinal toxicity — for both traditional small molecules and complex antibody-drug conjugates (ADCs) — with accuracy that tracks real clinical outcomes. The data are being presented at The 23rd International Congress of the European Society of Toxicology In Vitro (ESTIV 2026) in Maastricht, the Netherlands, which takes place from June 29 to July 2, 2026. Key highlights of the presented data demonstrating VivoSim’s ability to achieve definitive translational signatures across complex organ systems: High-Accuracy Liver Profiling: Benchmarked against a clinical small-molecule dataset of 92 compounds, the NAMkind Liver spheroid model achieved a predictive accuracy of 91%, with 90% sensitivity, 95% specificity, and 99% precision under repeat-dose conditions. The multi-endpoint profiling suite effectively minimized false negatives and successfully resolved intra-class toxicities, such as within thiazolidinediones (TZDs). Mechanistic GI Insights: Using the multicellular human intestinal barrier model (NAMkind GI), VivoSim successfully integrated multiple endpoints including barrier function to resolve distinct mechanistic classes of tyrosine kinase inhibitor (TKI)-induced diarrhea. Deconvolution of ADC Toxicity: Critically, both platforms demonstrated a unique capacity to evaluate advanced modalities by differentiating ADC risk based on structural properties. The GI model established that Trastuzumab-deruxtecan-mediated injury is exposure-dependent and payload-driven through detailed histological tracking. Meanwhile, the Liver model successfully differentiated hepatic risk based on linker stability and payload permeability when comparing Trastuzumab Emtansine and Trastuzumab Deruxtecan. 
