Michelle O. Kenyon

The in vivo Pig-a assay: A report of the International Workshop On Genotoxicity Testing (IWGT) Workgroup.

The in vivo Pig-a assay uses flow cytometry to measure phenotypic variants for antibody binding to cell surface glycosylphosphatidylinositol (GPI)-anchored proteins. There is good evidence suggesting that the absence of antibody binding is the result of a mutation in the endogenous X-linked Pig-a gene, which forms the rationale for the assay. Although the assay has been performed with several types of hematopoietic cells and in a variety of mammalian species, including humans, currently it is optimized only for measuring CD59-deficient (presumed Pig-a mutant) erythrocytes in the peripheral blood of rats. An expert workgroup formed by the International Workshop on Genotoxicity Testing considered the state of assay development and the potential of the assay for regulatory use. Consensus was reached on what is known about the Pig-a assay and how it should be conducted, and recommendations were made on additional data and refinements that would help to further enhance the assay for use in hazard identification and risk assessment.

In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: an industry survey.

With the increasing emphasis on identification and low level control of potentially genotoxic impurities (GTIs), there has been increased use of structure-based assessments including application of computerized models. To date many publications have focused on the ability of computational models, either individually or in combination, to accurately predict the mutagenic effects of a chemical in the Ames assay. Typically, these investigations take large numbers of compounds and use in silico tools to predict their activity with no human interpretation being made. However, this does not reflect how these assessments are conducted in practice across the pharmaceutical industry. Current guidelines indicate that a structural assessment is sufficient to conclude that an impurity is non-mutagenic. To assess how confident we can be in identifying non-mutagenic structures, eight companies were surveyed for their success rate. The Negative Predictive Value (NPV) of the in silico approaches was 94%. When human interpretation of in silico model predictions was conducted, the NPV increased substantially to 99%. The survey illustrates the importance of expert interpretation of in silico predictions. The survey also suggests the use of multiple computational models is not a significant factor in the success of these approaches with respect to NPV.

Establishing best practise in the application of expert review of mutagenicity under ICH M7.

The ICH M7 guidelines for the assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals allows for the consideration of in silico predictions in place of in vitro studies. This represents a significant advance in the acceptance of (Q)SAR models and has resulted from positive interactions between modellers, regulatory agencies and industry with a shared purpose of developing effective processes to minimise risk. This paper discusses key scientific principles that should be applied when evaluating in silico predictions with a focus on accuracy and scientific rigour that will support a consistent and practical route to regulatory submission.

Principles and procedures for implementation of ICH M7 recommended (Q)SAR analyses.

The ICH M7 guideline describes a consistent approach to identify, categorize, and control DNA reactive, mutagenic, impurities in pharmaceutical products to limit the potential carcinogenic risk related to such impurities. This paper outlines a series of principles and procedures to consider when generating (Q)SAR assessments aligned with the ICH M7 guideline to be included in a regulatory submission. In the absence of adequate experimental data, the results from two complementary (Q)SAR methodologies may be combined to support an initial hazard classification. This may be followed by an assessment of additional information that serves as the basis for an expert review to support or refute the predictions. This paper elucidates scenarios where additional expert knowledge may be beneficial, what such an expert review may contain, and how the results and accompanying considerations may be documented. Furthermore, the use of these principles and procedures to yield a consistent and robust (Q)SAR-based argument to support impurity qualification for regulatory purposes is described in this manuscript.

A practical application of two in silico systems for identification of potentially mutagenic impurities

The International Conference on Harmonization (ICH) M7 guidance for the assessment and control of DNA reactive impurities in pharmaceutical products includes the use of in silico prediction systems as part of the hazard identification and risk assessment strategy. This is the first internationally agreed guidance document to include the use of these types of approaches. The guideline requires the use of two complementary approaches, an expert rule-based method and a statistical algorithm. In addition, the guidance states that the output from these computer-based assessments can be reviewed using expert knowledge to provide additional support or resolve conflicting predictions. This approach is designed to maximize the sensitivity for correctly identifying DNA reactive compounds while providing a framework to reduce the number of compounds that need to be synthesized, purified and subsequently tested in an Ames assay. Using a data set of 801 chemicals and pharmaceutical intermediates, we have examined the relative predictive performances of some popular commercial in silico systems that are in common use across the pharmaceutical industry. The overall accuracy of each of these systems was fairly comparable ranging from 68% to 73%; however, the sensitivity of each system (i.e. how many Ames positive compounds are correctly identified) varied much more dramatically from 48% to 68%. We have explored how these systems can be combined under the ICH M7 guidance to enhance the detection of DNA reactive molecules. Finally, using four smaller sets of molecules, we have explored the value of expert knowledge in the review process, especially in cases where the two systems disagreed on their predictions, and the need for care when evaluating the predictions for large data sets.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscopes expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated.

Compensatory erythropoiesis has no impact on the outcome of the in vivo Pig-a mutation assay in rats following treatment with the haemolytic agent 2-butoxyethanol

The Pig-a assay has rapidly gained international interest as a useful tool for assessing the mutagenic potential of compounds in vivo. Although a large number of compounds, including both mutagens and non-mutagens, have been tested in the rat Pig-a assay in haematopoietic cells, there is limited understanding of how perturbations in haematopoiesis affect assay performance. Of particular concern is the possibility that regenerative haematopoiesis alone, without exposure to a genotoxic agent, could result in elevated Pig-a mutant cell frequencies. To address this concern, Wistar-Han rats were dosed by oral gavage with a non-genotoxic haemolytic agent, 2-butoxyethanol (2-BE). Dose levels ranging from 0 to 450 mg/kg were tested using both single administration and 28-day treatment regimens. Haematology parameters were assessed at minimum within the first 24h of treatment and 8 days after the final administration. Pig-a mutant frequencies were assessed on Days 15 and ~30 for both treatment protocols and also on Days 43 and 57 for the 28-day protocol. Even at doses of 2-BE that induced marked intravascular lysis and strong compensatory erythropoiesis, the average Pig-a mutant phenotype red blood cell and reticulocyte frequencies were within the historical vehicle control distribution. 2-BE therefore showed no evidence of in vivo mutagenicity in these studies. The data suggest that perturbations in haematopoiesis alone do not lead to an observation of increased mutant frequency in the Pig-a assay.

Evaluation of the in vivo mutagenicity of isopropyl methanesulfonate in acute and 28-day studies.

Understanding the mutagenic dose response could prove beneficial in the management of pharmaceutically relevant impurities. For most alkyl ester impurities, such as isopropyl methanesulfonate (IPMS), little in vivo mutagenicity data exist for dose analysis. The likelihood of a sublinear dose response for IPMS was assessed by comparing the Swain Scott constant, the SN1/SN2 reaction mechanism and the O6:N7 guanine adduct ratio to that of more well‐known alkyl esters. Based on available information, IPMS was predicted to have a mutagenic profile most like ethyl nitrosourea. To test this hypothesis, mature male Wistar Han rats were administered IPMS using acute (single administration at 3.5 to 56 mg/kg) or subchronic (28 days at 0.125 to 2 mg/kg/day) exposures. The in vivo Pig‐a mutation assay was used to identify mutant phenotype reticulocyte (Ret) and red blood cell (RBC) populations. The maximum mutant response occurred approximately 15 and 28 days after the last dose administration in the mutant Ret and RBC populations respectively in the acute study and on Day 29 and 56 in the mutant Ret and RBC populations, respectively, in the subchronic study. A comparison of RBC mutant frequencies from acute and subchronic protocols suggests a sublinear response; however, this was not substantiated by statistical analysis. A No Observed Effect Level (NOEL) of 0.25 mg/kg/day resulted in a Permitted Daily Exposure equivalent to the Threshold of Toxicological Concern. An estimate of the NOEL based on the previously mentioned factors, in practice, would have pre‐empted further investigation of the potent mutagen IPMS. Environ. Mol. Mutagen. 56:322–332, 2015.

Determination of compound-specific acceptable daily intakes for 11 mutagenic carcinogens used in pharmaceutical synthesis

The synthesis of pharmaceutical products often involves the use of reactive starting materials and intermediates. Low levels may be present in the final product as impurities and of particular concern are impurities that have mutagenic and carcinogenic potential. Regulatory guidance documents provide a general framework to minimise human exposure to these impurities; however, compound-specific recommendations are limited. Our practical experience with 11 pharmaceutical impurities is presented. The genotoxicity and carcinogenicity data are summarised and the approach used to derive an acceptable daily intake (ADI) is described for each chemical. We have highlighted the considerations and challenges associated with calculating ADIs based on available carcinogenicity data. This may provide a useful reference to others in the pharmaceutical industry regarding impurity control, where the weight of evidence indicates the chemical is a mutagenic carcinogen.

In silico toxicology protocols

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.