Lhasa Limited shared knowledge shared progress

Aromatic Amines

The Aromatic Amines project aims to improve the understanding and predictability of the Ames test outcome for primary aromatic amines. This project is one of several projects initiated by Lhasa Limited that enables pre-competitive data sharing.

Vitic Aromatic Amines logo

Insight

Aromatic amines are widely used in the synthesis of pharmaceuticals but are often found to have mutagenic activity, and 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. The data sharing group consists of pharmaceutical companies, with the aim to build a database to enable the development of improved predictive models.

  • This project focuses on one chemical class, the aromatic amines, for which it is notoriously difficult to predict Ames activity. The remit of the projects 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 (2017.1.0) consists of:
    • 666 compounds.
    • 9,402 Genetic Toxicity In-Vitro records and 17,321 associated Dose-response Data supplementary records.
    • 666 summary records in the Ames Calls tables and 5,084 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.

 

 

Benefits

Benefits

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
    • Lhasa Limited’s systematic peer-review process guarantees a high-quality, standardised dataset that you can be confident using.
    • 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.
  • 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.
    • 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).

 

 

Stronger together

Why Lhasa?

Lhasa Limited - an honest broker and trusted holder of data

Lhasa is a not-for-profit organisation and we believe 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. These include:

 

  • Elemental Impurities Shares analytical data on the levels of trace metals within batches of excipients and aims to increase understanding of the level of risk posed by elemental impurities.
  • eTOX A toxicity database combining public data and preclinical legacy reports from participating pharmaceutical companies.
  • iPiE Aims to develop frameworks to support the environmental testing of new pharmaceuticals and to help prioritise testing of legacy APIs
  • Vitic Excipients Shares data on the effects of pharmaceutical excipients and aims to refine experiments and contribute towards a reduction of animal numbers required for testing.
  • Vitic Intermediates Shares data resulting from Ames mutagenicity assays performed on common Intermediates and compounds containing functional groups of interest.

Get Involved

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.

References

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

http://www.lhasalimited.org/publications/improvements-to-in-silico-predictivity-after-access-to-proprietary-data/3930

Contact Us

© 2017 Lhasa Limited | Registered office: Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK Tel: +44 (0)113 394 6020
VAT number 396 8737 77 | Lhasa Limited is registered as a charity (290866)| Company Registration Number 01765239 (England and Wales).

QuestionPro supports sample survey questions such as multiple choice, drop-down menu, likert-scale, semantic differential, matrix, constant sum, drag-and-drop, slider-scale, net-promoter scale, and many more question types.