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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 […]

Mutagenic impurities can be expected in any drug product; however, this is not a concern providing they are present below the safe limit. The objective of a carcinogenicity study is to identify compounds that can cause tumours in animals, which is imperative to understanding the cancer risk posed to humans. ICH M7 in practice The

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

By 2025, 36% of world data will be healthcare data. (Yes, thirty-six percent!). Considering this statistic, now more than ever, it is important that we are working to ensure existing data is utilised to make better safety assessment decisions more quickly – whilst also relying less on animal testing. Within many sectors of the life

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

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

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

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.

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

Nitrite analysis of excipients is a new and analytically challenging area, with many organisations working quickly to determine the best practice and techniques to use. The Nitrites in Excipients data sharing consortium was established in September 2020 and is part of Lhasa Limited’s effort to support the global challenge of nitrosamine risk assessment. Currently the