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 …
Continue reading “Instem’s Computational Toxicology and Genetic Toxicology Groups at GTA 2021”
We are happy to be presenting at this year’s virtual SOT meeting1 on a number of topics throughout the course of the event. On Monday 15th March at 3pm (EST), we are covering some new areas at the session “Hot Topics in Computational Toxicology: New Developments that Support Regulatory Submissions.” This includes a discussion on …
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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 …
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 …
One of the most common questions we are asked is how an overall toxicity assessment for a given chemical is arrived at, especially when there are conflicting study results available. To answer this question, it is often helpful to review the process of producing the content in Leadscope’s databases, which is overseen by Leadscope’s Manager …
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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 …
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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 …
As Candice described in her recent blog “So many pieces of information!” – making actionable decisions is extremely complicated, especially when integrating the results from in silico models alongside historical in vivo studies and in vitro experiments. When is there sufficient information to make a decision? Well, it depends the type of decision and the …
Continue reading “Why is it important to define confidence?”
Nitrosamine impurities currently belong to a “cohort of concern” because of their potential to be potent mutagenic carcinogens, as described in the ICH M7 guideline1. They are also coming under increasing regulatory scrutiny with the US Food and Drug Administration and European Medicines Agency recently issuing new guidelines2,3 for examination of this class. These guidelines …
Continue reading “Establishing potency categories for Nitrosamine impurities”
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 …
Continue reading “Can the burden on industry and regulators be reduced?”
