Acceptable intakes (AIs) for 11 small molecule N-nitrosamines (NAs).

Low levels of N-nitrosamines (NAs) were detected in pharmaceuticals and, as a result, health authorities (HAs) have published acceptable intakes (AIs) in pharmaceuticals to limit potential carcinogenic risk. The rationales behind the AIs have not been provided to understand the process for selecting a TD50 or read-across analog. In this manuscript we evaluated the toxicity data for eleven common NAs in a comprehensive and transparent process consistent with ICH M7. This evaluation included substances which had datasets that were robust, limited but sufficient, and substances with insufficient experimental animal carcinogenicity data. In the case of robust or limited but sufficient carcinogenicity information, AIs were calculated based on published or derived TD50s from the most sensitive organ site. In the case of insufficient carcinogenicity information, available carcinogenicity data and structure activity relationships (SARs) were applied to categorical-based AIs of 1500 ng/day, 150 ng/day or 18 ng/day; however additional data (such as biological or additional computational modelling) could inform an alternative AI. This approach advances the methodology used to derive AIs for NAs.

Management of pharmaceutical ICH M7 (Q)SAR predictions - The impact of model updates.

Pharmaceutical applicants conduct (Q)SAR assessments on identified and theoretical impurities to predict their mutagenic potential. Two complementary models-one rule-based and one statistical-based-are used, followed by expert review. (Q)SAR models are continuously updated to improve predictions, with new versions typically released on a yearly basis. Numerous releases of (Q)SAR models will occur during the typical 6-7 years of drug development until new drug registration. Therefore, it is important to understand the impact of model updates on impurity mutagenicity predictions over time. Compounds representative of pharmaceutical impurities were analyzed with three rule- and three statistical-based models covering a 4-8 year period, with the individual time frame being dependent on when the individual models were initially made available. The largest changes in the combined outcome of two complementary models were from positive or equivocal to negative and from negative to equivocal. Importantly, the cumulative change of negative to positive predictions was small in all models (<5%) and was further reduced when complementary models were combined in a consensus fashion. We conclude that model updates of the type evaluated in this manuscript would not necessarily require re-running a (Q)SAR prediction unless there is a specific need. However, original (Q)SAR predictions should be evaluated when finalizing the commercial route of synthesis for marketing authorization.

Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses.

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.

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.

In Silico Assessment of Biomolecule Reactivity with Leachables.

Leachables in pharmaceutical products may react with biomolecule active pharmaceutical ingredients (APIs), for example, monoclonal antibodies (mAb), peptides, and ribonucleic acids (RNA), potentially compromising product safety and efficacy or impacting quality attributes. This investigation explored a series of in silico models to screen extractables and leachables to assess their possible reactivity with biomolecules. These in silico models were applied to collections of known leachables to identify functional and structural chemical classes likely to be flagged by these in silico approaches. Flagged leachable functional classes included antimicrobials, colorants, and film-forming agents, whereas specific chemical classes included epoxides, acrylates, and quinones. In addition, a dataset of 22 leachables with experimental data indicating their interaction with insulin glargine was used to evaluate whether one or more in silico methods are fit-for-purpose as a preliminary screen for assessing this biomolecule reactivity. Analysis of the data showed that the sensitivity of an in silico screen using multiple methodologies was 80%-90% and the specificity was 58%-92%. A workflow supporting the use of in silico methods in this field is proposed based on both the results from this assessment and best practices in the field of computational modeling and quality risk management.

Use of in silico systems and expert knowledge for structure-based assessment of potentially mutagenic impurities.

Genotoxicity hazard identification is part of the impurity qualification process for drug substances and products, the first step of which being the prediction of their potential DNA reactivity using in silico (quantitative) structure-activity relationship (Q)SAR models/systems. This white paper provides information relevant to the development of the draft harmonized tripartite guideline ICH M7 on potentially DNA-reactive/mutagenic impurities in pharmaceuticals and their application in practice. It explains relevant (Q)SAR methodologies as well as the added value of expert knowledge. Moreover, the predictive value of the different methodologies analyzed in two surveys conveyed in the US and European pharmaceutical industry is compared: most pharmaceutical companies used a rule-based expert system as their primary methodology, yielding negative predictivity values of ⩾78% in all participating companies. A further increase (>90%) was often achieved by an additional expert review and/or a second QSAR methodology. Also in the latter case, an expert review was mandatory, especially when conflicting results were obtained. Based on the available data, we concluded that a rule-based expert system complemented by either expert knowledge or a second (Q)SAR model is appropriate. A maximal transparency of the assessment process (e.g. methods, results, arguments of weight-of-evidence approach) achieved by e.g. data sharing initiatives and the use of standards for reporting will enable regulators to fully understand the results of the analysis. Overall, the procedures presented here for structure-based assessment are considered appropriate for regulatory submissions in the scope of ICH M7.

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 analysis of pharmaceutical experience with decades of rat carcinogenicity testing: support for a proposal to modify current regulatory guidelines.

Data collected from 182 marketed and nonmarketed pharmaceuticals demonstrate that there is little value gained in conducting a rat two-year carcinogenicity study for compounds that lack: (1) histopathologic risk factors for rat neoplasia in chronic toxicology studies, (2) evidence of hormonal perturbation, and (3) positive genetic toxicology results. Using a single positive result among these three criteria as a test for outcome in the two-year study, fifty-two of sixty-six rat tumorigens were correctly identified, yielding 79% test sensitivity. When all three criteria were negative, sixty-two of seventy-six pharmaceuticals (82%) were correctly predicted to be rat noncarcinogens. The fourteen rat false negatives had two-year study findings of questionable human relevance. Applying these criteria to eighty-six additional chemicals identified by the International Agency for Research on Cancer as likely human carcinogens and to drugs withdrawn from the market for carcinogenicity concerns confirmed their sensitivity for predicting rat carcinogenicity outcome. These analyses support a proposal to refine regulatory criteria for conducting a two-year rat study to be based on assessment of histopathologic findings from a rat six-month study, evidence of hormonal perturbation, genetic toxicology results, and the findings of a six-month transgenic mouse carcinogenicity study. This proposed decision paradigm has the potential to eliminate over 40% of rat two-year testing on new pharmaceuticals without compromise to patient safety.

An industry perspective on the utility of short-term carcinogenicity testing in transgenic mice in pharmaceutical development.

International guidelines allow for use of a short-term cancer bioassay (twenty-six weeks) in transgenic mice as a substitute for one of the two required long-term rodent bioassays in the preclinical safety evaluation of pharmaceuticals. The two models that have gained the widest acceptance by sponsors and regulatory authorities are the CB6F1-RasH2 mouse hemizygous for a human H-ras transgene and the B6.129N5-Trp53 mouse heterozygous for a p53 null allele. The p53(+/-) model is of particular value for compounds with residual concern that genotoxic activity may contribute to tumorigenesis. The rasH2 model is an appropriate alternative without regard to evidence of genotoxic potential. Since results from a short-term bioassay can be obtained relatively early in drug development, there is the potential for more timely assessment of cancer risk for individuals in long-term clinical trials. Use of these models in preclinical safety evaluation also significantly reduces animal use, time, and manpower. Preliminary findings indicate that prediction of two-year rat bioassay outcomes based on data from chronic rat toxicity studies, together with early assessment of carcinogenic potential in short-term transgenic models, may have the potential to increase the timeliness and efficiency of strategies for the identification of human carcinogenic hazards.

Creating context for the use of DNA adduct data in cancer risk assessment: I. Data organization.

The assessment of human cancer risk from chemical exposure requires the integration of diverse types of data. Such data involve effects at the cell and tissue levels. This report focuses on the specific utility of one type of data, namely DNA adducts. Emphasis is placed on the appreciation that such DNA adduct data cannot be used in isolation in the risk assessment process but must be used in an integrated fashion with other information. As emerging technologies provide even more sensitive quantitative measurements of DNA adducts, integration that establishes links between DNA adducts and accepted outcome measures becomes critical for risk assessment. The present report proposes an organizational approach for the assessment of DNA adduct data (e.g., type of adduct, frequency, persistence, type of repair process) in concert with other relevant data, such as dosimetry, toxicity, mutagenicity, genotoxicity, and tumor incidence, to inform characterization of the mode of action. DNA adducts are considered biomarkers of exposure, whereas gene mutations and chromosomal alterations are often biomarkers of early biological effects and also can be bioindicators of the carcinogenic process.

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.

Genotoxicity of naturally occurring indole compounds: correlation between covalent DNA binding and other genotoxicity tests.

3-Methylindole (3MI), melatonin (Mel), serotonin (Ser), and tryptamine (Tryp) were evaluated in vitro for their potential to induce DNA adducts, DNA strand breaks, chromosomal aberrations (Abs), inhibition of DNA synthesis, and mutations. All compounds produced DNA adducts in calf thymus DNA in the presence of rat liver S9. In cultured rat hepatocytes, all produced DNA adducts but none induced DNA strand breaks. In Chinese hamster ovary cells, 3MI and Mel produced DNA adducts, Abs, and inhibition of DNA synthesis with and without S9, except that Mel without S9 did not form adducts. Ser formed DNA adducts, was an equivocal Abs inducer, and suppressed DNA synthesis. Tryp induced neither adducts nor Abs, but did suppress DNA synthesis with S9. Ser and Tryp were less cytotoxic than 3MI and Mel. Mel, Ser, and Tryp failed to induce mutations in Salmonella and E. coli strains with or without S9. 3MI and Mel produced DNA adducts but not mutations in Salmonella TA100 with S9. 3MI and its metabolite indole 3-carbinol also did not induce mutations in a shuttle vector system in human cells. The lack of correlation between DNA adducts and other genotoxicity endpoints for these indole compounds may be due to the higher sensitivity of the (32)P-postlabeling adduct assay or it may indicate that the indole-DNA adducts per se are not mutagenic and are not able to induce strand breaks or alkali-labile lesions. The indole-induced Abs may result from cytotoxicity and suppression of DNA synthesis with minimal if any contribution from DNA adducts.

Genotoxicity of benzene and its metabolites.

The potential role of genotoxicity in human leukemias associated with benzene (BZ) exposures was investigated by a systematic review of over 1400 genotoxicity test results for BZ and its metabolites. Studies of rodents exposed to radiolabeled BZ found a low level of radiolabel in isolated DNA with no preferential binding in target tissues of neoplasia. Adducts were not identified by 32P-postlabeling (equivalent to a covalent binding index <0.002) under the dosage conditions producing neoplasia in the rodent bioassays, and this method would have detected adducts at 1/10,000th the levels reported in the DNA-binding studies. Adducts were detected by 32P-postlabeling in vitro and following high acute BZ doses in vivo, but levels were about 100-fold less than those found by DNA binding. These findings suggest that DNA-adduct formation may not be a significant mechanism for BZ-induced neoplasia in rodents. The evaluation of other genotoxicity test results revealed that BZ and its metabolites did not produce reverse mutations in Salmonella typhimurium but were clastogenic and aneugenic, producing micronuclei, chromosomal aberrations, sister chromatid exchanges and DNA strand breaks. Rodent and human data were compared, and BZ genotoxicity results in both were similar for the available tests. Also, the biotransformation of BZ was qualitatively similar in rodents, humans and non-human primates, further indicating that rodent and human genotoxicity data were compatible. The genotoxicity test results for BZ and its metabolites were the most similar to those of topoisomerase II inhibitors and provided less support for proposed mechanisms involving DNA reactivity, mitotic spindle poisoning or oxidative DNA damage as genotoxic mechanisms; all of which have been demonstrated experimentally for BZ or its metabolites. Studies of the chromosomal translocations found in BZ-exposed persons and secondary human leukemias produced by topoisomerase II inhibitors provide some additional support for this mechanism being potentially operative in BZ-induced leukemia.