Improving the understanding and predictability of the Ames test outcome for primary aromatic amines.
- A collaboration of pharmaceutical organisations sharing data from Ames mutagenicity assays for primary aromatic amines.
- The group aims to build a database to enable the development of improved predictive models.
Aromatic amines are widely used in the synthesis of pharmaceuticals but are often found to have mutagenic activity. The prediction of such activity has proven difficult. The Consortium for the Investigation of the Genotoxicity of Aromatic Amines (CIGAA) aims to improve the understanding and predictability of the Ames test outcome for primary aromatic amines (Harvey and Patel, 2015). The data sharing group consists of pharmaceutical companies and aims to build a database to enable the development of improved predictive models.
- This project focuses on one chemical class, aromatic amines, for which it is notoriously difficult to predict Ames activity. The remit of the project is to collect Ames data for the aromatic amines, perform further data analysis and refine aromatic amine mutagenicity predictions.
- The shared data is derived from Ames mutagenicity assays performed on aromatic amines.
- Constant member contributions mean that the database is ever growing. The latest Aromatic Amines Database (2022.1.0) consists of:
- 1,103 Structures records
- 16,923 Genetic Toxicity In-Vitro records and 86,565 associated Dose-response Data supplementary records.
- 1,103 summary records in the Ames Calls tables and 9,780 Subset Calls supplementary table records.
- Lhasa Limited acts as an honest broker and expertly curates the data from participating organisations. This allows a level of anonymity, whereby the submitting companies are known to each other, but who submitted what is known to Lhasa Limited only.
The benefits that can be achieved by being part of the CIGAA include:
- Advancing the Knowledge of Aromatic Amines - By participating in this consortium, you are actively helping the progression towards more accurate predictions for this difficult-to-predict chemical class. The shared data can be used to build and validate new SAR models for the prediction of the potential mutagenic activity of aromatic amines.
- Access High-Quality Data - Data and structures are highly relevant for those working in drug development.; the database includes information such as starting materials, synthetic building blocks, predicted degradants, known synthetic intermediates and impurities. Also, Lhasa Limited’s systematic peer-review process guarantees a high-quality, standardised dataset that you can be confident using.
- Further Evidence for Expert Review under ICH M7 - Having access to proprietary data enables a more informed expert assessment. Finding relevant supporting examples for your impurities by structure, substructure or similarity searching can add weight to expert review (Barber et al. 2015).
- Utilise Proprietary Data - Joining this data sharing venture gives you the chance to make use of existing information that is not in the public domain.
- Time and Cost Savings - The sharing of data in regards to aromatic amines reduces duplication of data across companies, avoiding the need to repeat potentially costly experiments. Also, the ability to search for chemically similar compounds in Vitic enables read-across studies to be performed quickly and easily. This in turn can inform decisions in the synthesis planning process, allowing users to avoid problematic compounds and unnecessary testing.
- Improved Coverage of Chemical Space - Derek alerts are built on public, proprietary and regulatory data (including data from the FDA). Through the sharing of aromatic amine data, the coverage and predictivity of Derek Nexus has been improved, and new aromatic amine alerts have been developed (Macmillan, 2016).
Why Choose Lhasa?
Lhasa Limited - an honest broker and trusted holder of data
Lhasa is a not-for-profit organisation and believes that shared knowledge can lead to shared progress. Recognised as the original "Honest Broker", Lhasa Limited has repeatedly been trusted with proprietary data and this can be seen with our involvement in other collaborative data sharing projects.
Members of the Aromatic Amines group include prominent members of the pharmaceutical industry and we are always happy to hear from interested parties.
To find out more about data sharing opportunities at Lhasa Limited, please get in touch.
- Patel et al. (2018) 'A pharma-wide approach to address the genotoxicity prediction of primary aromatic amines', Computational Toxicology, vol. 7, pp. 27-35. https://doi.org/10.1016/j.comtox.2018.06.002
- Harvey and Patel (2015) 'CIGAA - Consortium for the Investigation of Genotoxicity of Aromatic Amines', Lhasa Limited
- 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. http://dx.doi.org/10.1016/j.yrtph.2015.07.018
- Macmillan. (2016) 'Improvements to in silico predictivity after access to proprietary data', Lhasa Limited