enviPath builds on more than two decades of research and innovation by its founders and team. Our products are grounded in over 20 years of peer‑reviewed scientific work, combining modern software architecture with intuitive interfaces, machine learning, and AI-driven approaches to tackle critical challenges in chemistry. Founded in 2024 in Aotearoa New Zealand by Tim Lorsbach and Joerg Wicker, enviPath brings together an experienced team of chemists, software engineers, and machine learning researchers dedicated to transforming complex chemical knowledge into powerful, accessible tools.
January 2010
Publication: Predicting biodegradation products and pathways: a hybrid knowledge- and machine learning-based approach
December 2015
First release of enviPath
January 2016
Publication: enviPath – The environmental contaminant biotransformation pathway resource
April 2016
Publication: A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction
February 2017
Publication: Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data
September 2021
Publication: Holistic evaluation of biodegradation pathway prediction: assessing multi-step reactions and intermediate products
August 2024
Publication: Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath
17 October 2024
enviPath Limited incorporated in New Zealand.
February 2025
Publication: Predictive modeling of biodegradation pathways using transformer architectures.
February 2025
UniServices invests into enviPath.
May 2025
enviPath at SETAC Europe 2025 in Vienna with a booth and co-hosting a workshop.
August 2025
enviPath at the Norwegian Environmental Toxicology Symposium (NETS) in Stavanger.
November 2025
enviPath showcase at the European Chemical Agency (ECHA) in Helsinki.
January 2026
enviPath 2.0 released! Now enviPath is way faster in predicting, loading, and browsing; is more stable, with fewer crashes and fewer bugs; integrates our research of the last 10 years – and there is even more to come in the next weeks; has an advanced queuing system, so your predictions do not get lost, and resources are distributed fairly among users; scales up; looks much better – the whole system got a much-needed facelift!
