Latest Articles
Our Presentations at SOT 2025
MN-AM.com enjoyed attending the 64th Annual Meeting and ToxExpo of the Society of Toxicology in Orlando, Florida, USA in March 2025. Your participation with visiting our booth, our poster presentation, our hosted session, and discussing with us our science and
Visit MN-AM at the SOT Annual Meeting and ToxExpo 2025
MN-AM.com is excited to attend the upcoming 64th Annual Meeting and ToxExpo of the Society of Toxicology in Orlando, Florida, USA in March 2025. We cordially invite you to visit our booth no. 530 at the ToxExpo. We will demonstrate
MN-AM Company (Molecular Networks GmbH and Altamira LLC) is acquired by Lhasa Limited, the Leader in Decision Making Software for In Silico Chemical Safety
January 30, 2025 – MN-AM Company, Molecular Networks GmbH (MN) in Nürnberg Germany and Altamira LLC (AM) in Columbus Ohio USA, announced on January 30th 2025 their acquisition by Lhasa Limited.Lhasa, a UK not-for-profit organisation, creates world-leading in silico solutions
Product Updates
Release of Version 5.0.0 of CORINA Classic
Release of Version 4.2023 of ChemTunes.ToxGPS
Release of Version 4.4.0 of CORINA Classic
Events
Our Presentations at SOT 2025
Visit MN-AM at the SOT Annual Meeting and ToxExpo 2025
Our Presentations at SOT 2024
Presentations
Presentations at the SOT 2023 Meeting
Visit Us at the ASCCT 2022 Annual Meeting
Presentations at the SOT 2022 Meeting
Latest Publications
The evolution of the EFSA OpenFoodTox database
Iovine N, Roncaglioni A, Sartori L, Yang C, Benfenati E. “The evolution of the EFSA OpenFoodTox database”, Journal of Toxicological Studies, 3(1), 1798.
Maintenance, update and further development of EFSA’s Chemical Hazards: OpenFoodTox 2.0
Benfenati E, Roncaglioni A, Iovine N, Marzo M, Toropov A, Toropova A, Ciacci A, Lettieri M, Sartori L, Yang C, Magdziarz T, Hobocienski B, Mostrag A. “Maintenance, update and further development of EFSA’s Chemical Hazards: OpenFoodTox 2.0”, EFSA Supporting Publication 2024:EN-8590.
High Throughput Read-Across for Screening a Large Inventory of Related Structures by Balancing Artificial Intelligence/Machine Learning and Human Knowledge
Yang C, Rathman JF, Mostrag A, Ribeiro JV, Hobocienski B, Magdziarz T, Kulkarni S, Barton-Maclaren T. “High Throughput Read-Across for Screening a Large Inventory of Related Structures by Balancing Artificial Intelligence/Machine Learning and Human Knowledge”, Chem. Res. Toxicol. 2023.