- Vitic is a structure searchable database. It offers researchers and scientists rapid access to high-quality toxicity data.
- A trusted toxicity system, Vitic contains data implemented by scientists at Lhasa Limited, who continually work on the database with current toxicological knowledge.
- Using Vitic is a quick and inexpensive way to identify potentially toxic chemicals, and therefore reject unsuitable drug candidates.
Whether your industry is cosmetics, pharmaceuticals, chemicals or academia, Vitic enables you to:
- Evaluate the potential toxicity of existing or prospective chemicals through exploitation of large chemical libraries.
- Make decisions about which chemicals are likely to have ‘more favourable’ toxic profiles, when you do not have a complete experimental profile of the chemical.
- Save time and money by selecting compounds with a favourable outlook, rather than carrying out toxicity experiments on a large number of chemicals.
- Share internal toxicity data and knowledge with your colleagues by capturing it within Vitic.
- Improve the properties of a chemical in the R&D pipeline by slightly redesigning its molecular structure.
- Learn using the extensive data in this expertly curated database as a toxicology training tool
In keeping with our philosophy that shared knowledge leads to shared progress, Lhasa Limited is a facilitator of collaborative knowledge and pre-competitive data sharing project. Lhasa has a reputation as an expert in our field, trusted by our members to handle sensitive and confidential intellectual property (Elder et al. 2015)
Vitic is the core component of various data sharing projects. Our involvement in such projects includes:
- Leading and supporting cross-company learning through pre-competitive data sharing. Projects include AI/PDE, Aromatic Amines, Excipients, Elemental Impurities and Production Intermediates.
- Contributing to the EU MIP-DILI project through curation and hosting of commercially sensitive data.
For more information on Vitic, or to request a demonstration, please contact us.
Barber et al. (2015) ‘Establishing best practice in the application of expert review of mutagenicity under ICH M7’, Regulatory Toxicology and Pharmacology, vol. 73, no. 1, pp. 367-377.
Elder et al. (2015) ‘Mutagenic Impurities: Precompetitive/Competitive Collaborative and Data Sharing Initiatives’, Organic Process Research & Development, vol.19, no. 11, May, pp. 1486-1494.
Macmillan et al. (2016) ‘Predicting skin sensitisation using a decision tree integrated testing strategy with an in silico model and in chemico/in vitro assays’, Regulatory Toxicology and Pharmacology, vol. 76, April, pp. 30-38.