With a half billion calculations per assessment, REACHAcross™ enables you to perform a QSAR in minutes versus days required for a manual assessment.
REACHAcross™ leverages previously conducted animal experimental data to accurately calculate the probability for producing a hazard while reducing the need for expensive and unnecessary animal testing or costly consulting fees.
Advanced machine learning algorithms identify the most relevant chemical analogs from one of the largest toxicology databases available ensuring reliable results, proven to be just as accurate as other available approaches and animal testing, but at a much lower cost.
The UL REACHAcross™ report includes chemical structures, similarity index score and hazard categories for nearest neighbors and hazard probability predictions for the chemical. This enables you to use the REACHAcross report beyond REACH registrations.
Easy to Use
REACHAcross™ makes it easy to operate and get the information you need; no expertise, qualifications or training required.
Large Curated Database
With one of the largest collections of chemical structures and endpoints (and growing) the database includes:
Advanced Machine Learning
Machine-learning engine builds networks of chemicals based on molecular structure, while complex algorithms make half a billion calculations per assessment to find associations between chemicals and endpoints. This enables the delivery of complete results for both existing and new chemicals.
REACHAcross™ has been validated according to OECD QSAR Validation Principles with sensitivities greater than 80%, matching the quality and accuracy of animal test results.