In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

The International Council for Harmonization (ICH) M7 guideline describes a hazard assessment process for impurities that have the potential to be present in a drug substance or drug product. In the absence of adequate experimental bacterial mutagenicity data, (Q)SAR analysis may be used as a test to predict impurities' DNA reactive (mutagenic) potential. However, in certain situations, (Q)SAR software is unable to generate a positive or negative prediction either because of conflicting information or because the impurity is outside the applicability domain of the model. Such results present challenges in generating an overall mutagenicity prediction and highlight the importance of performing a thorough expert review. The following paper reviews pharmaceutical and regulatory experiences handling such situations. The paper also presents an analysis of proprietary data to help understand the likelihood of misclassifying a mutagenic impurity as non-mutagenic based on different combinations of (Q)SAR results. This information may be taken into consideration when supporting the (Q)SAR results with an expert review, especially when out-of-domain results are generated during a (Q)SAR evaluation.

Background: The treatment of severe aortic stenosis has evolved considerably since the introduction of transcatheter aortic valve replacement (TAVR), yet trends in complications for patients undergoing TAVR or surgical aortic valve replacement (SAVR) at a national level have yet to be evaluated. Methods and Results: We performed a retrospective cohort study using Medicare data to evaluate temporal trends in complications among beneficiaries, aged ≥65 years, treated with elective isolated transfemoral TAVR or SAVR between 2012 and 2019. The study end point was the occurrence of a major complication (composite outcome) during index and up to 30 days after. Multivariable logistic regression was used to assess odds of complications for TAVR and SAVR, individually over time, and for TAVR versus SAVR, over time. The cohort included 211 212 patients (mean±SD age, 78.6±7.3 years; 45.0% women). Complication rates during index following elective isolated aortic valve replacement decreased from 49% in 2012 to 22% in 2019. These reductions were more pronounced for TAVR (41% to >19%, Δ=22%) than SAVR (51% to >47%, Δ=4%). After risk adjustment, the risk of any complication with TAVR was 47% ( P <0.0001) lower compared with SAVR in 2012, and 78% ( P <0.0001) lower in 2019. TAVR was independently associated with reduced odds of complications each year compared with 2012, with the magnitude of benefit increasing over time (2013 versus 2012: odds ratio [OR], 0.89 [95% CI, 0.81–0.97]; 2019 versus 2012: OR, 0.35 [95% CI, 0.33–0.38]). These findings are consistent for complications up to 30 days from index. Conclusions: Between 2012 and 2019, the risk of complications after aortic valve replacement among Medicare beneficiaries decreased significantly, with larger absolute and relative changes among patients treated with TAVR than SAVR.

The carcinogenic potency categorisation approach (CPCA) has recently been introduced by health authorities. In this model, structural features from recent literature, industry proposals, and analyses performed by health authorities, provide a rapid assessment of the potential acceptable intake (AI) for a nitrosamine impurity. As with other screening regulatory values (such as the ICH M7 Threshold of Toxicological Concern), the CPCA is conservative and can be considered a de minimis risk management framework. In cases where a nitrosamine drug substance-related impurity (NDSRI) is present below the CPCA limit, the framework provides resolution from a toxicological perspective (i.e., no further toxicology studies are required). Where an NDSRI is above the CPCA limit, the framework provides for the initiation of additional activities (i.e., the CPCA is not the only possible limit). Read-across approaches are described in both the CPCA and M7 guidance and can provide a limit with more specific applicability than the general model. The use of available experimental data (in vitro or in vivo), is valuable in order to provide an even more specific limit. The CPCA provides a framework; however, data should permit changing the AI from initial structural assessment, based on increasing data, to ultimately increase precision of the AI.