The release of OECD QSAR Toolbox version 4.9 marks a major step forward for chemical risk assessment, bringing fresh datasets, refined metabolic simulators, and seamless data interoperability to your desktop. If you are a toxicologist looking to integrate in silico approaches into your daily hazard identification and data gap filling, this update makes navigating computational workflows easier than ever. Key Updates in Toolbox 4.9 Enhanced Interoperability with IUCLID & EFSA: Import...

As regulatory demands expand — from screening Endocrine Disrupting Chemicals (EDCs) to evaluating PBT/vPvB and PMT substances — toxicologists face unprecedented volumes of chemical data. Modern in silico toxicology is not meant to replace wet-lab expertise; it acts as an early-stage accelerator that saves time, cuts testing costs, and focuses experimental resources where they matter most. What We Are Presenting at EUROTOX 2026 ToxNavigation will be at the Austria Center Vienna from September...

As toxicologists, we are constantly told that Machine Learning (ML) and Artificial Intelligence (AI) are the future of hazard identification. The promise is alluring: faster assessments, lower costs, and a significant reduction in animal testing. But for many in our field, these computational methods still feel like a "black box." A groundbreaking new perspective paper published in the Journal of Cheminformatics sheds light on a frustrating reality. After reviewing nearly 2,300 scientific...