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Innovate

Discover the latest innovations in computer-aided reasoning and information systems.

A new life in Leeds at Lhasa 1

Animal-Free Safety Assessment (AFSA) Masterclass launched

We are delighted to announce our participation in the Animal-Free Safety Assessment for Cosmetics (AFSA) Masterclass. Launched in March 2023, this free, online training programme is designed to build capacity and confidence in animal-free safety assessment of cosmetics and ingredients. Over the last three years, our scientists have helped to build a one-of-a-kind educational course […]

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Establishing best practice for impurity purge by solubility

Establishing best practice for impurity purge by solubility

We are delighted to share our vital new article ‘Establishing best practice for the application and support of solubility purge factors’ which was recently published in Organic Process Research & Development (OPRD). The paper has been written by Lhasa Principal Scientist Michael Burns, alongside industry expert co-authors from AstraZeneca, GSK, Hoffman LaRoche and other forward

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Ensuring data quality in Vitic three benchmarks for data quality success 1

Ensuring data quality in Vitic; three benchmarks for data quality success

Evaluating the potential toxicity of chemicals is an important part of the drug development process. Optimizing a data set that provides quality over quantity is critical in the search for suitable drug candidates. Developed by our scientists, Vitic is a chemical database and information management system that provides rapid access to high-quality toxicity data from

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Supporting N nitrosamine risk assessments for drug products

Supporting N-nitrosamine risk assessments for drug products

The nitrosamine crisis first erupted in July 2018, when the FDA announced voluntary recall of several drugs containing Valsartan: a medicine used to treat high blood pressure and heart failure. Due to an unreported change in synthesis of Valsartan, the potentially cancer-causing chemical N-nitrosodimethylamine (or NDMA) was detected in the marketed drug product. This resulted

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LCDB Blog Image

5 things you should know about the data in the Lhasa Carcinogenicity Database (LCDB)

With technical input from Andrew Thresher. Would your toxicology assessments benefit from free access to long-term carcinogenicity study data? The Lhasa Carcinogenicity Database (LCDB) is a widely used, free resource of long-term carcinogenicity study data. In this article we explore 5 things you should know about the data in the LCDB. 1. The Lhasa Carcinogenicity

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Expert review blog

Is expert review an essential step when assessing mutagenic potential of drug impurities?

When assessing the mutagenic potential of drug impurities in silico, the ICH M7 guideline states that two complementary (Q)SAR prediction methodologies should be applied. A provision for the application of ‘expert knowledge’ is also mentioned within the guideline. However, as (Q)SAR models continue to be updated and their predictive performance and structural coverage improves, this raises

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Controlling pCotentially mutagenic impurities – 8 top tips from industry experts

Controlling potentially mutagenic impurities – 8 top tips from industry experts

Article written by Ally Reeves with top tips provided by Sara Atkinson. A key consideration within drug substance synthesis is the potential presence of mutagenic impurities. Potentially mutagenic impurities (PMIs) often arise from reagents which are essential for the synthesis of a final active pharmaceutical ingredient (API) meaning that the risk is therefore often unavoidable.

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Replace Reduce Refine – How Lhasa Limited are supporting the 3Rs

Replace, Reduce, Refine – How Lhasa Limited are supporting the 3Rs

The three words “replace“, “reduce” and “refine” provide an indispensable framework for performing more humane animal research. Also know as the 3Rs, the principle aims to limit the number of animals used in experiments, replace animal tests with alternatives and minimise the distress placed on animals. Last year, a revolutionary guideline on Defined Approaches for

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