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Collaboration & Data Sharing Initiatives

Collaboration and Data Sharing Initiatives Lhasa Limited

Lhasa Limited is an active scientific research organisation working in chemistry and related sciences. Our specialisation includes the development of software for toxicology and metabolism prediction and data management, however we are always looking to broaden our horizons.

Our software is developed in collaboration with Lhasa Limited members and the broader scientific community. As a not-for-profit organisation and educational charity Lhasa is ideally suited for creating and managing collaborative groups and promoting data sharing, without compromising the confidentiality of proprietary information.

Some of the organisations that have worked with Lhasa Limited in previous or current research projects, or that have donated data for the benefit of Lhasa Limited members, are listed in the tabs below.

If you would like to discuss a potential collaboration or if you have data you may wish to donate to existing programs and associated databases, please contact us via the appropriate form.

Dr. Andrew Teasdale, AstraZeneca, states:

"It is my view that pre-competitive collaboration and data sharing has been arguably the single most effective means of progression in a number of key regulatory areas over the last decade. Key examples of this include ICH M7 and ICH Q3D. In the case of ICH M7, this has led to the development of an addendum to the guideline that has allowed, for the first time, agreed safety limits for a range of key reagents – removing the uncertainties around acceptance or otherwise of limits proposed by an individual sponsor. Similar exercises have driven major improvements to in silico tools used in the assessment and control of mutagenic impurities.

In the case of ICH Q3D, collaboration has led not only to establishment of key, risk-based principles used in the effective risk assessment of products, but also the development of a excipient database that is allowing a crucial insight into the extent of risk associated with excipients, putting the risk into proper context. In all these cases and many more, organisations have established more effective ways of working that save time/money and effort. Key in such arrangements is having the right forum and platform. Lhasa have shown themselves, over a period of 20 years, to be an excellent facilitator of such knowledge sharing collaborations, something I and many in the industry hope will continue both in current and new areas."



Pre-competitive and even competitive collaboration is becoming more commonplace in industry as organisations look to work together for mutual gain. The benefits to be seen from collaboration include cost savings, reduced environmental impact or the derivation of knowledge that would be unfeasible by one organisation alone.

Various arrangements can exist, but the one most often used today is the role of an 'honest broker'1, whereby an independent, third party is responsible for coordinating the activities of a consortium. As a not-for-profit organisation, Lhasa Limited has a long and successful track record in this role and has, and continues to be, regularly trusted with proprietary data.


Lhasa Limited - an honest broker and trusted holder of data

Lhasa Limited was founded on the basis of data and knowledge sharing. Building on its reputation as the 'honest broker', Lhasa Limited has continued to work on the basis of ‘shared knowledge, shared progress’ for more than 30 years. Over this time, Lhasa has regularly been trusted with proprietary data and this can be seen in the many successful consortia that we continue to be involved in. The continued success of such consortia is demonstrative of how working with Lhasa makes a real difference to the research and development process of its members.

Just one example is the Vitic Intermediates data sharing consortium, which aims to share mutagenicity data on common pharmaceutical synthetic intermediates. Lhasa's CEO recently had this to say on the group:

“The fact that the Vitic Intermediates data sharing consortium, initiated by Lhasa, has now entered its 9th year, and is still growing, is a testament to the tangible benefits of data sharing for all participants.  Lhasa Limited is honoured to be repeatedly recognised as the original honest broker and trusted holder of proprietary data”.


  1. Elder, D. P., White, A., Harvey, J., Teasdale, A., Williams, R. V., Covey-Crump, E. "Mutagenic Impurities: Precompetitive/Competitive Collaborative and Data Sharing Initiatives" Organic Process Research & Development DOI: 10.1021/acs.oprd.5b00128

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There are various benefits to pre-competitive and competitive collaboration and data sharing as explored by Elder1. Here, we provide an overview of how collaboration and data sharing can help you. For the benefits associated with each particular project, please refer to the project pages. 

  • Time and cost savings
    • Reduction in the need to duplicate experiments done by others offers both time and cost savings.
  • Improved quality
    • Making use of data that might not otherwise be available, improves your in-house prediction systems to achieve more specific and accurate results.
    • Gain from improvements to Lhasa Limited prediction systems, with more robust predictions covering the chemical space that is right for you.
  • Weight of argument
    • Work together to influence the introduction of new/changes to regulation and advise on the best approaches to take for your organisation.
  • Shared knowledge, shared progress
    • Gain the opportunity to enter into a dialogue with peers encountering the same challenges as you and overcome those challenges as a unit.
    • Gain access to data that is not in the public domain, leading to more informed decisions.


  1. Elder, D. P., White, A., Harvey, J., Teasdale, A., Williams, R. V., Covey-Crump, E. "Mutagenic Impurities: Precompetitive/Competitive Collaborative and Data Sharing Initiatives" Organic Process Research & Development DOI: 10.1021/acs.oprd.5b00128

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A summary of our current collaborations can be seen below. We are currently in the process of updating this section of our website, where relevant please click the project name to find out about a project in more detail.


Initiated in 2017 and using Lhasa’s Vitic platform, the AI/PDE project brings together top pharmaceutical organisations to share and harmonise Acceptable Intake (AI) and Permitted Daily Exposure (PDE) data.

Aromatic Amines

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 who are sharing data for drug precursors, with the aim to build a database to enable the development of improved predictive models.

Complex Nitrosamines

The complex nitrosamine data sharing initiative launched in 2021 in response to the nitrosamine impurity crisis within the pharmaceutical industry. The consortium aims to use the data to improve structure activity relationships (SARs) for complex nitrosamines - identifying trends in compound complexity versus mutagenic potential.

Elemental Impurities

This project is designed to share analytical data on the levels of trace metals within batches of excipients used in the formulation of pharmaceutical drug products. The aim of the collaboration is to increase understanding of the level of risk posed by elemental impurities potentially present in excipients.    


Enhancing TRANslational SAFEty Assessment through Integrative Knowledge Management (eTRANSAFE).


An Integrated European ‘Flagship’ Programme Driving Mechanism-based Toxicity Testing and Risk Assessment for the 21st century.


Partners working on this project are sharing data on the effects of pharmaceutical excipients with the aim of refining experiments and contributing towards a reduction in the number of animals required for testing. Also, it presents a viable solution for reacting to the REACH initiative, which requires data sharing between companies wishing to register the same chemicals, in order to avoid duplication of animal experiments.

Food & Drug Administration RCA

In late 2011, Lhasa Limited signed a research collaboration agreement (RCA) with the U.S. Food and Drug Administration (FDA) which is building upon the successes of the previous Cooperative Research and Development Agreement (CRADA) that expired in December 2011.

The agreement allows for the continued development of knowledge in Lhasa's software for toxicity, metabolism and chemical degradation prediction, and for the inclusion of publicly available data from the RCA to be entered into the Vitic toxicity database. 

Production Intermediates

Vitic Intermediates data sharing consortium allows members to share Ames mutagenicity data on pharmaceutical synthetic intermediates.  Currently 10 pharmaceutical companies are members of the consortium and to date they have shared 1,211 compounds with 18,934 associated genetic toxicity in vitro data records.  

The mutagenic status of process intermediates is of paramount importance under the ICH M7 Guideline (Assessment and Control of DNA Reactive [Mutagenic] impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk)1.  Many process intermediates are common across organisations and the sharing of such data allows participants to avoid duplicating costly and time consuming tests.  In addition participants and Lhasa’s wider membership group benefit as this data allows for the improvement and validation of in silico prediction systems including Derek and Sarah Nexus.

  1. http://www.ich.org/products/guidelines/multidisciplinary/article/multidisciplinary-guidelines.html.

* Figures correct at time of writing

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Get involved

To find out more about collaborative or data sharing opportunities at Lhasa Limited, please get in touch or submit your data using the data submission form.

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Some of our previous collaborations can be seen below.

Chemical Degradation Project

This project was a collaboration with various industry experts with the following key objectives:

  • Provide a system that would predict forced degradation pathways
  • support regulatory submissions
  • Inform the early stages of drug development relating to drug stability, and compatibility of adjuvants and formulants.

On completion of this project, Zeneth was launched as a new product in Lhasa Limited's product portfolio. 


This collaboration developed testing strategies and supporting methods for health and environmental safety evaluation. This project resulted in the addition of ecotoxicity data for skin sensitisation into the Vitic database and the development of a software tool (Eco Derek) to guide users through their testing strategies.

eTOX Project

The eTOX project aimed to develop innovative methodological strategies and novel software tools to better predict the toxicological profiles of new drug candidates. Lhasa Limited acted as a central contributor to eTOX through the hosting and managing of all confidential data shared by the pharmaceutical partners.

iPiE Project

This project aimed to develop frameworks to support the environmental testing of new pharmaceuticals and to help prioritise testing of legacy APIs. Lhasa Limited worked to develop the iPiE database, as well as the Integrated Software System that support this intelligent testing. 

John Moores University, Liverpool

Sponsored by Lhasa Limited, this project looked at developing strategies to capture the validity of predictions from Derek for Windows and similar systems. This work also looked at ways of defining the prediction space for Derek for Windows rules and alerts, in an effort to attach measures of confidence to predictions.

The Meteor Environmental Pathway Prediction System (MEPPS)

This was a collaboration between Lhasa Limited and the University of Minnesota to use information from the university’s Pathway Prediction System to create a knowledge-based system for predicting microbial degradation pathways using the same technology as Meteor. This work aimed to assist studies relating to a wide range of issues such as the environmental impact of chemicals, agrochemicals and pharmaceutical products undergoing biodegradation.


Drug Induced Liver Injury (DILI) is recognised as a major health problem; however, it is poorly predicted by methods currently used by the pharmaceutical industry. Initiated in 2012 and using the Vitic Nexus platform, MIP-DILI was a five-year IMI/EFPIA funded consortium concerned with the Mechanism Based Integration Systems for the Prediction of Drug Induced Liver Injury (MIP-DILI).


Mirabilis is the result of an ongoing collaboration between Lhasa Limited and various pharmaceutical partners, to develop a systematic assessment of the risk of potentially mutagenic impurities remaining in a final drug product when introduced or created during synthesis. 

On completion of this project, Mirabilis was launched as a new product in Lhasa Limited's product portfolio. 

Sheffield University

This project, sponsored by Lhasa Limited, looked at conducting research into new approaches for data mining, to support the development of rules and alerts for Derek Nexus (formerly Derek for Windows) and similar systems. This work was published in a paper and also detailed in a webinar.

University of Surrey PhD sponsorship

This collaboration with Prof Paul Krause (Computing) and Dr Brendan Howlin (Chemistry) was fully sponsored by Lhasa Limited as a continuation to the KTP Project completed in March 2013. The project aimed to develop novel methodologies for the interpretation of highly accurate machine learning based predictions.


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