New book on Mutagenic Impurities

We have been really happy to contribute to a number of chapters in an important new book edited by Dr. Andrew Teasdale: “Mutagenic Impurities: Strategies for Identification and Control”1 This will be an essential read for students and professionals in the field of genotoxic impurities (GTIs) assessment covering topics including a history of the regulatory …

Instem’s Computational Toxicology and Genetic Toxicology Groups at GTA 2021

We are pleased to be attending this year’s virtual GTA meeting1 and will be presenting on several topics throughout the course of the event. On Thursday May 6th, Dr. Kevin Cross will be presenting “Predicting N-Nitrosamine Activity from Structure-Activity Relationships” as part of a Symposium on “The 3Rs and in Silico Modeling”. This presentation addresses …

N-nitrosamine SAR Working group

Leadscope, Inc. (an Instem company), in collaboration with Lhasa Limited are leading a working group of pharmaceutical toxicologists and consultants investigating the carcinogenic potency and structure-activity relationships of N-nitrosamines. This is in response to the recent discovery of N-nitrosamines in marketed pharmaceuticals and the regulatory changes that have resulted. The working group is run by …

New acute toxicity (Q)SAR manuscript

Late last year we reviewed a collaboration to assess whether acute (Q)SAR models are fit-for-purpose1 to support classification and labeling, since the use of an alternative approach would support the 3Rs. As part of this exercise, a series of primarily proprietary chemicals with acute toxicity data were run through the different acute (Q)SAR methodologies and …

Are (Q)SAR models fit-for-purpose for classification and labelling?

We were recently involved in a cross-industry project to determine whether (Q)SAR models were fit-for-purpose for classification and labelling. To test this hypothesis, a series of companies across different industrial sectors each compiled a data set of chemicals with experimental acute rat oral data. These chemicals were run against the first version of the Leadscope …

Understanding false negatives

For toxicological tests, a false negative (i.e., predicting a chemical is negative when it is in fact positive) is one type of error. It is often desirable to minimize the number of false negatives to decrease the risk of missing a toxic chemical. Computational toxicology is a rapid high-throughput test of multiple chemicals, and like …

Can the burden on industry and regulators be reduced?

About 6 years ago, the International Conference on Harmonization (ICH) published the M7 guideline “Assessment and Control of DNA reactive (mutagenic) Impurities in Pharmaceuticals to limit Potential Carcinogenic Risk”.[1] This was a landmark moment for computational toxicology, as it was the first time such methods were recognized by the ICH as a regulatory test. An …