Deriving acceptable limits for non-mutagenic impurities in medicinal products - Durational adjustments.

ICH Q3A/B guidelines are not intended for application during the clinical research phase of development and durationally adjusted qualification thresholds are not included. A central tenet of ICH Q3A is that lifetime exposure to 1 mg/day of an unqualified non-mutagenic impurity (NMI) is not a safety concern. An analysis of in vivo toxicology data from 4878 unique chemicals with established NO(A)ELs was conducted to determine whether durationally adjusted qualification limits can be supported. Although not recommended in ICH Q3A/B, a conservative approach was taken by using allometric scaling in the analysis. Following allometric scaling of the 5th percentile of the distribution of NO(A)ELs from available chronic toxicology studies, it was reconfirmed that there is a safety basis for the 1 mg/day qualification threshold in ICH Q3A. Additionally, allometric scaling of the 5th percentile of the distribution of NO(A)ELs from sub-acute and sub-chronic toxicology studies could support acceptable limits of 20 and 5 mg/day for an unqualified NMI for dosing durations of less than or greater than one month, respectively. This analysis supports durationally adjusted NMI qualification thresholds for pharmaceuticals that protect patient safety and contribute to 3Rs efforts for qualifying impurities using new approach methods.

Assessing the utility of common arguments used in expert review of in silico predictions as part of ICH M7 assessments.

Expert review of two predictions, made by complementary (quantitative) structure-activity relationship models, to an overall conclusion is a key component of using in silico tools to assess the mutagenic potential of impurities as part of the ICH M7 guideline. In lieu of a specified protocol, numerous publications have presented best practise guides, often indicating the occurrence of common prediction scenarios and the evidence required to resolve them. A semi-automated expert review tool has been implemented in Lhasa Limited's Nexus platform following collation of these common arguments and assignment to the associated prediction scenarios made by Derek Nexus and Sarah Nexus. Using datasets primarily donated by pharmaceutical companies, an automated analysis of the frequency these prediction scenarios occur, and the likelihood of the associated arguments assigning the correct resolution, could then be conducted. This article highlights that a relatively small number of common arguments may be used to accurately resolve many prediction scenarios to a single conclusion. The use of a standardised method of argumentation and assessment of evidence for a given impurity is proposed to improve the efficiency and consistency of expert review as part of an ICH M7 submission.

Strategies for Assessing Acceptable Intakes for Novel N-Nitrosamines Derived from Active Pharmaceutical Ingredients.

The detection of N-nitrosamines, derived from solvents and reagents and, on occasion, the active pharmaceutical ingredient (API) at higher than acceptable levels in drug products, has led regulators to request a detailed review for their presence in all medicinal products. In the absence of rodent carcinogenicity data for novel N-nitrosamines derived from amine-containing APIs, a conservative class limit of 18 ng/day (based on the most carcinogenic N-nitrosamines) or the derivation of acceptable intakes (AIs) using structurally related surrogates with robust rodent carcinogenicity data is recommended. The guidance has implications for the pharmaceutical industry given the vast number of marketed amine-containing drugs. In this perspective, the rate-limiting step in N-nitrosamine carcinogenicity, involving cytochrome P450-mediated α-carbon hydroxylation to yield DNA-reactive diazonium or carbonium ion intermediates, is discussed with reference to the selection of read-across analogs to derive AIs. Risk-mitigation strategies for managing putative N-nitrosamines in the preclinical discovery setting are also presented.

Practical and Science-Based Strategy for Establishing Acceptable Intakes for Drug Product N-Nitrosamine Impurities.

The potential for N-nitrosamine impurities in pharmaceutical products presents a challenge for the quality management of medicinal products. N-Nitrosamines are considered cohort-of-concern compounds due to the potent carcinogenicity of many of the structurally simple chemicals within this structural class. In the past 2 years, a number of drug products containing certain active pharmaceutical ingredients have been withdrawn or recalled from the market due to the presence of carcinogenic low-molecular-weight N,N-dialkylnitrosamine impurities. Regulatory authorities have issued guidance to market authorization holders to review all commercial drug substances/products for the potential risk of N-nitrosamine impurities, and in cases where a significant risk of N-nitrosamine impurity is identified, analytical confirmatory testing is required. A key factor to consider prior to analytical testing is the estimation of the daily acceptable intake (AI) of the N-nitrosamine impurity. A significant proportion of N-nitrosamine drug product impurities are unique/complex structures for which the development of low-level analytical methods is challenging. Moreover, these unique/complex impurities may be less potent carcinogens compared to simple nitrosamines. In the present work, our objective was to derive AIs for a large number of complex N-nitrosamines without carcinogenicity data that were identified as potential low-level impurities. The impurities were first cataloged and grouped according to common structural features, with a total of 13 groups defined with distinct structural features. Subsequently, carcinogenicity data were reviewed for structurally related N-nitrosamines relevant to each of the 13 structural groups and group AIs were derived conservatively based on the most potent N-nitrosamine within each group. The 13 structural group AIs were used as the basis for assigning AIs to each of the structurally related complex N-nitrosamine impurities. The AIs of several N-nitrosamine groups were found to be considerably higher than those for the simple N,N-dialkylnitrosamines, which translates to commensurately higher analytical method detection limits.

In Vivo Mutagenicity Testing of Arylboronic Acids and Esters.

Arylboronic acids and esters (referred to collectively as arylboronic compounds) are commonly used intermediates in the synthesis of pharmaceuticals but pose a challenge for chemical syntheses because they are often positive for bacterial mutagenicity in vitro. As such, arylboronic compounds are then typically controlled to levels that are acceptable for mutagenic impurities, that is, the threshold of toxicological concern (TTC). This study used ICH M7 guidance to design and conduct a testing strategy to investigate the in vivo relevance of the in vitro positive findings of arylboronic compounds. Eight arylboronic compounds representing a variety of chemical scaffolds were tested in Sprague Dawley and/or Wistar rats in the in vivo Pig-a (peripheral blood reticulocytes and mature red blood cells) and/or comet assays (duodenum and/or liver). Five of the eight compounds were also tested in the micronucleus (peripheral blood) assay. The arylboronic compounds tested orally demonstrated high systemic exposure; thus the blood and bone marrow were adequately exposed to test article. One compound was administered intravenously due to formulation stability issues. This investigation showed that arylboronic compounds that were mutagenic in vitro were not found to be mutagenic in the corresponding in vivo assays. Therefore, arylboronic compounds similar to the scaffolds tested in this article may be considered non-mutagenic and managed in accordance with the ICH Q3A/Q3B guidelines. Environ. Mol. Mutagen. 2019. © 2019 Wiley Periodicals, Inc.

Genetic toxicology in silico protocol.

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.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: is aromatic N-oxide a structural alert for predicting DNA-reactive mutagenicity?

(Quantitative) structure-activity relationship or (Q)SAR predictions of DNA-reactive mutagenicity are important to support both the design of new chemicals and the assessment of impurities, degradants, metabolites, extractables and leachables, as well as existing chemicals. Aromatic N-oxides represent a class of compounds that are often considered alerting for mutagenicity yet the scientific rationale of this structural alert is not clear and has been questioned. Because aromatic N-oxide-containing compounds may be encountered as impurities, degradants and metabolites, it is important to accurately predict mutagenicity of this chemical class. This article analysed a series of publicly available aromatic N-oxide data in search of supporting information. The article also used a previously developed structure-activity relationship (SAR) fingerprint methodology where a series of aromatic N-oxide substructures was generated and matched against public and proprietary databases, including pharmaceutical data. An assessment of the number of mutagenic and non-mutagenic compounds matching each substructure across all sources was used to understand whether the general class or any specific subclasses appear to lead to mutagenicity. This analysis resulted in a downgrade of the general aromatic N-oxide alert. However, it was determined there were enough public and proprietary data to assign the quindioxin and related chemicals as well as benzo[c][1,2,5]oxadiazole 1-oxide subclasses as alerts. The overall results of this analysis were incorporated into Leadscope's expert-rule-based model to enhance its predictive accuracy.

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.

2-Hydroxypyridine-N-oxide (HOPO): Equivocal in the ames assay.

2-Hydroxypyridine-N-oxide (HOPO) is a useful coupling reagent for synthesis of active pharmaceutical ingredients. It has been reported to be weakly mutagenic in the Ames assay (Ding W et al. []: J Chromatogr A 1386:47-52). According to the ICH M7 guidance (2014) regarding control of mutagenic impurities to limit potential carcinogenic risk, mutagens require control in drug substances such that exposure not exceeds the threshold of toxicological concern. Given the weak response observed in the Ames assay and the lack of any obvious structural features that could confer DNA reactivity we were interested to determine if the results were reproducible and investigate the role of potentially confounding experimental parameters. Specifically, Ames tests were conducted to assess the influence of compound purity, solvent choice, dose spacing, toxicity, type of S9 (aroclor vs phenobarbital/ß-napthoflavone), and lot variability on the frequency of HOPO induced revertant colonies. Initial extensive testing using one lot of HOPO produced no evidence of mutagenic potential in the Ames assays. Subsequent studies with four additional lots produced conflicting results, with an ∼2.0-fold increase in revertant colonies observed. Given the rigor of the current investigation, lack of reproducibility between lots, and the weak increase in revertants, it is concluded that HOPO is equivocal in the bacterial reverse mutation assay. It is highly unlikely that HOPO poses a mutagenic risk in vivo; therefore, when it is used as a reagent in pharmaceutical synthesis, it should not be regarded as a mutagenic impurity, but rather a normal process related impurity. Environ. Mol. Mutagen. 59:312-321, 2018. © 2018 Wiley Periodicals, Inc.

Resolution of contradiction between in silico predictions and Ames test results for four pharmaceutically relevant impurities.

The ICH M7 Guideline requires low level control of mutagenic impurities in pharmaceutical products to minimize cancer risk in patients (ICHM7, 2014). Bacterial mutagenicity (Ames) data is generally used to determine mutagenic and possible carcinogenic potential of compounds. Recently, a publication on experiences of using two in silico systems to identify potentially mutagenic impurities highlighted the importance of performing a critical review of published Ames data utilized as part of a mutagenicity assessment of impurities (Greene et al., 2015). Four compounds (2-amino-5-hydroxybenzoic acid, 2-amino-3-chlorobenzoic acid, methyl 2-amino-4-chlorobenzoate and 4-morpholinopyridine) reported mutagenic were identified in a two system in silico assessment and expert review of the structuresas non-mutagenic. Likely reasons for mutagenicity could not be identified and the purity of the compounds tested was proposed. In the current investigation, the purest available sample of the four compounds was tested in an OECD-compliant Ames test. The compounds were all found to be non-mutagenic. Possible reasons for the discrepancy between previously reported and current results are discussed. Additionally, important points to consider when conducting an expert review of available Ames data are provided particularly in cases where reported Ames results are discrepant with a two system in silico assessment.

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.

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.

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.

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 SN 1/SN 2 reaction mechanism and the O(6) :N(7) 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.

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.

An evaluation of the sensitivity of the Ames assay to discern low-level mutagenic impurities.

Low level impurities often reside in active pharmaceutical ingredients (API). Some of these impurities are potentially genotoxic since reactive intermediates are used in the synthetic route for the production of API. Routine mutagenicity testing is conducted in support of clinical trials with the intent to identify genotoxic hazards associated with API. Depending on the amount of impurity present in the API tested, the potency of the impurities and the relative sensitivity of the Ames assay, it is possible that mutagenicity associated with the presence of genotoxic impurities could also be detected while testing API. Therefore, we evaluated published data and generated new information to understand the sensitivity of the Ames assay. Based on a literature survey of approximately 450 mutagens, it was estimated that 85% of mutagens are detected at concentrations of 250 microg/plate or less. Based on this estimate, most mutagens should be detected in an Ames assay testing API concentrations up to 5000 microg/plate if present at a 5% or greater concentration. Data from experiments where several direct and indirect-acting mutagens were spiked into representative API further support the literature-based evaluation. Some limitations of this approach, including toxicity of API and competing metabolism are discussed.