LEEDS, England, January 20, 2015 /PRNewswire/ --
Lhasa Limited, a leading global supplier of knowledge based software and associated databases, today announces the first release of Mirabilis, software that can help experts assess and predict the likelihood for the potential carryover of impurities.
Mirabilis is the result of collaboration between Lhasa Limited, AbbVie, AstraZeneca, Eli Lilly, GSK, Hoffman-La Roche, Novartis and Pfizer to develop a systematic approach for the risk assessment of impurities remaining in a final drug product when introduced or created during synthesis. The ICH M7 Guidelineallows for multiple approaches for the control of impurities ranging from reliance on analytical testing, chemistry purge arguments or a combination of the two. Many impurities are highly reactive and thus will not typically survive subsequent synthetic and purification steps and therefore present negligible risk of carry over into the final product. This approach, an extension of previously published methodology,, is working towards a common industry framework and tool for assessing the purge of an impurity.
The first version of Mirabilis allows a user to enter their synthesis scheme(s), highlight the impurities of concern and estimate the purge values for them at each stage. Supporting expert information is provided to aid the user. The software tracks the impurities from introduction to final product allowing very easy analysis of the route, creating a record of it and any subsequent changes which are made. A key aspect of this collaboration is the creation of a reactivity database of purge values which are rarely reported in the literature and will serve as a significant asset to users. The consortium is heavily involved in the decisions for the future direction of the software and the functionality included.
Andrew Teasdale of AstraZeneca said "I'm hugely excited by the excellent progress made this year, both in terms of the software and the knowledge and data to support predictions. Scientific studies performed to underpin the knowledgebase have been truly ground breaking in significantly enhancing our knowledge of the fate of impurities in chemical reactions".
Liz Covey-Crump, Business Development Manager at Lhasa added "The first year of the Mirabilis project has been a great success. Good progress has been made in the development of the software which will be released to Members in December 2014. Members of the consortium have been carrying out experimental work in order to generate data to support the reactivity purge prediction. All the consortium members have participated in expert elicitation, a process to capture knowledge of the reactivity of various impurity classes under typical transformation conditions."
- Teasdale, Andrew, Genotoxic Impurities: Strategies for Identification and Control, 221-247 (2010). ISBN: 978-0-470-49919-1, http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470499192.html
- Teasdale, A., Elder, D. P., Chang, S.-J., Wang, S., Thompson, R., Benz, N. & Sanchez, I. (2013). Risk assessment of genotoxic impurities (GTIs) in new chemical entities - strategies to demonstrate control. Organic Process Research & Development, 17(2), 221-230. doi:10.1021/op300268u
About Lhasa Limited
Lhasa Limited is a not-for-profit organisation that facilitates collaborative data sharing projects in the pharmaceutical, cosmetics and chemistry-related industries. A pioneer in the production of knowledge-based systems for forward thinking scientists, Lhasa limited continues to draw on over thirty years of experience to create user-friendly, state of the art in silico prediction and database systems.
We believe in 'Shared Knowledge, Shared Progress'. Our not-for-profit, member driven status is designed to facilitate collaborative working and confidential data sharing between organisations. We run collaborative projects with industry, academia and regulatory bodies to continually enhance all our products.
Lhasa's products include the Derek Nexus expert system for predicting toxicity, Sarah Nexus, a transparent statistical system for predicting mutagenicity, Vitic Nexus for managing chemical data and information, Meteor Nexus for predicting metabolic fate and Zeneth for predicting forced degradation pathways.
For further information on this collaboration and information about how you can join please contact firstname.lastname@example.org or call +44-113-394-6020.
SOURCE Lhasa Limited