Pressure is mounting on companies to manufacture and use products that are safe and effective and also more sustainable through their full lifecycle. The practice of predictive toxicology, or computational toxicology, can help companies meet the multitude of needs presented by green chemistry and sustainable product design requirements while also serving as an alternative to animal testing.
As the pace of product innovation increases, traditional toxicological test methods are lagging behind. Companies need access to more advanced tools and resources to efficiently and successfully evaluate new chemical substances for potential end-point hazards.
Leveraging a curated database of 70 million structures and 80,908 chemicals with 833,844 labeled hazard endpoints, our innovative digital solution utilizes an advanced algorithm, machine learning, and analysis of millions of chemical combinations to predict chemical hazards similar to the reproducibility accuracy of animal testing.
This ground-breaking solution offers the best of both worlds: automated computational QSAR using one of the largest chemical toxicology databases available, combined with the reliability of read across.
Our solution works by building large networks of chemicals based on properties such as molecular structure and health endpoint interactions. A user simply enters a CAS number, SMILES code or chooses to draw a chemical structure within the interface as inputs to predict 9 end-points: skin sensitization, acute dermal irritation, acute eye irritation, acute inhalation toxicity, acute oral toxicity, acute dermal toxicity, mutagenicity, acute aquatic toxicity, and chronic aquatic toxicity.
Results generated from our solution can be used for a number of purposes, including:
- Chemical Registration Submissions – Facilitating chemical assessments while reducing animal testing, this objective computational approach provides valuable data to support chemical registration hazard information requirements. This is particularly helpful when you have data gaps that need to be filled in order to construct a robust submission.
- Green Chemistry and Alternatives Assessment – Proactively assess potential chemical hazards upfront early in the product development process to design chemistries with inherently less hazards and to inform commercialization decisions. When evaluating candidate alternative chemicals, gain valuable information and insight to avoid “regrettable substitutions”.
- Research Safety Data Sheets (R-SDS) – For new research chemicals with no or very little data, and even for existing chemicals in use with hazard data gaps, it is challenging to characterize hazards to support proper hazard communication in the absence of animal test data. UL’s Cheminformatics Tool Kit will enable manufacturers and formulators to efficiently and accurately assess the hazards of chemicals and create robust SDS’, labels, and relevant transportation, hygiene, and laboratory safety information.
UL’s solution affords the following benefits:
- Results in minutes as compared to the days or months required with traditional methods.
- Data within the same range of statistical accuracy as animal testing, without its expense to conduct and the litany of regulations required to be met.
- Ability for the user to validate and edit the chemical structure upon input of CAS Number or SMILES code, and the ability to draw chemical structures within the interface as inputs.