Innovate

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

As a result of high carcinogenic potency of several N-nitrosamines in rodents, regulatory agencies are now requiring N-nitrosamine risk assessments to be performed on all marketed medical products. The EMA, U.S. FDA and other regulatory agencies have set acceptable daily intake (ADI) limits for some N-nitrosamines. These values are calculated from rodent carcinogenicity TD50 values for

Are you aware of the 5 OECD principles, which validate (Q)SAR models for their use in regulatory assessment of chemical safety? The Joint Research Centre (JRC) have established a harmonised template known as the QSAR Model Reporting Format (QMRF), which can be used to summarise key information on (Q)SAR models, including results of any validation

“As Adverse Outcome Pathways (AOPs) move from being an interesting scientific concept, to a useful practical application tool, this is an exciting time for both industry and Lhasa” … Regular Lhasa blog readers will have read this statement within our September blog “Shaping Lhasa Limited’s scientific direction through collaboration”. It is with great excitement that

It is common knowledge to those submitting drug substances for regulatory assessment, that an in silico assessment of mutagenic potential may be conducted in lieu of carcinogenicity or bacterial mutagenicity data for any impurities. A key requirement in ICH M7 states that “Two (Q)SAR prediction methodologies that complement each other should be applied. One methodology

“Our technology is designed by scientists, for scientists, in collaboration with industry stakeholders and regulators” At Lhasa Limited we often talk about the importance of industry involvement in shaping our direction. This involvement and collaboration takes places across many areas – perhaps most notably in recent years within the Mirabilis and Effiris consortia, where at

In this blog piece, we explore how Derek Nexus, our expert, knowledge-based toxicology software, performs against 7 alternative in silico skin sensitisation models. Providing qualitative predictions for many toxicity endpoints, including assessment of skin sensitisation, Derek can predict quantitative EC3 predictions for skin sensitisation as well as negative predictions for those query compounds which do