Preclinical safety assessment of JNJ-10450232 (NTM-006), a structural analog of acetaminophen, that does not cause hepatotoxicity at supratherapeutic doses.

JNJ-10450232 (NTM-006) is a new molecular entity that is structurally related to acetaminophen. A comprehensive non-clinical safety program was conducted to support first-in-human and clinical efficacy studies based on preclinical data suggesting that the compound has comparable or enhanced antinociceptive and antipyretic efficacy without causing hepatotoxicity at supratherapeutic doses. No hepatic toxicity was noted in a mouse model sensitive to acetaminophen hepatotoxicity or in rats, dogs, and non-human primates in 28-day repeat dose toxicity studies at and above doses/exposures at which acetaminophen is known to cause hepatotoxicity. In the 28-day toxicity studies, all treatment-related findings were monitorable and reversible. Methemoglobinemia, which was observed in dogs and to a lesser extent in rats, is also observed with acetaminophen. This finding is considered not relevant to humans due to species differences in metabolism. Thyroid hypertrophy and hyperplasia were also observed in dogs and were shown to be a consequence of a species-specific UGT induction also demonstrated with increased thyroid hormone metabolism. Indirect bilirubin elevation was observed in rats as a result of UGT1A1 Inhibition. JNJ-10450232 (NTM-006) had no toxicologically relevant findings in safety pharmacology or genotoxicity studies. Together, these data supported progressing into safety and efficacy studies in humans.

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.

It's difficult, but important, to make negative predictions.

At the confluence of predictive and regulatory toxicologies, negative predictions may be the thin green line that prevents populations from being exposed to harm. Here, two novel approaches to making confident and robust negative in silico predictions for mutagenicity (as defined by the Ames test) have been evaluated. Analyses of 12 data sets containing >13,000 compounds, showed that negative predictivity is high (∼90%) for the best approach and features that either reduce the accuracy or certainty of negative predictions are identified as misclassified or unclassified respectively. However, negative predictivity remains high (and in excess of the prevalence of non-mutagens) even in the presence of these features, indicating that they are not flags for mutagenicity.

Evaluation of a statistics-based Ames mutagenicity QSAR model and interpretation of the results obtained.

The relative wealth of bacterial mutagenicity data available in the public literature means that in silico quantitative/qualitative structure activity relationship (QSAR) systems can readily be built for this endpoint. A good means of evaluating the performance of such systems is to use private unpublished data sets, which generally represent a more distinct chemical space than publicly available test sets and, as a result, provide a greater challenge to the model. However, raw performance metrics should not be the only factor considered when judging this type of software since expert interpretation of the results obtained may allow for further improvements in predictivity. Enough information should be provided by a QSAR to allow the user to make general, scientifically-based arguments in order to assess and overrule predictions when necessary. With all this in mind, we sought to validate the performance of the statistics-based in vitro bacterial mutagenicity prediction system Sarah Nexus (version 1.1) against private test data sets supplied by nine different pharmaceutical companies. The results of these evaluations were then analysed in order to identify findings presented by the model which would be useful for the user to take into consideration when interpreting the results and making their final decision about the mutagenic potential of a given compound.

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 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.

Evaluation of a modified CD71 MicroFlow method for the flow cytometric analysis of micronuclei in rat bone marrow erythrocytes.

The aim of this study was to evaluate a modified flow cytometric method for the quantification of micronuclei in rat bone marrow reticulocytes. The method identified uses the erythrocyte pure fraction from cellulose filtered bone marrow with slight modifications to the widely published MicroFlow(®) method developed by Litron Laboratories, Rochester, NY for the detection of micronuclei in peripheral blood. A number of experiments were conducted to compare the micronucleus induction measured by flow cytometry with traditional microscopic analysis in male rats treated daily for 2 days with appropriate vehicle controls or various doses of cyclophosphamide (CP), mitomycin C (MMC), vinblastine sulfate (VBS), 1,2-dimethylhydrazine (DMH), etoposide (ETO), colchicine (COL), or 4-nitroquinoline-1-oxide (4NQO). In addition, for a subset of chemical we compared the induction of micronuclei in bone marrow and peripheral blood. The results from this study showed a very good correlation of micronucleus frequencies in bone marrow between microscopic analysis and the flow cytometry as well as between blood and bone marrow. In general, micronucleus frequencies of test compound treated animals and inter-animal variability were slightly lower by flow cytometric analysis compared to manual slide analysis. The data presented in this study support the use of the CD71 flow method for the analysis of micronuclei in rat bone marrow and also suggest that peripheral blood may be equally as sensitive as bone marrow in detecting a micronucleus response in short term studies.

Testing of acetaminophen in support of the international multilaboratory in vivo rat Pig-a assay validation trial.

Acetaminophen, a nonmutagenic compound as previously concluded from bacteria, in vitro mammalian cell, and in vivo transgenic rat assays, presented a good profile as a nonmutagenic reference compound for use in the international multilaboratory Pig-a assay validation. Acetaminophen was administered at 250, 500, 1,000, and 2,000 mg·kg-1 ·day-1 to male Sprague Dawley rats once daily in 3 studies (3 days, 2 weeks, and 1 month with a 1-month recovery group). The 3-Day and 1-Month Studies included assessments of the micronucleus endpoint in peripheral blood erythrocytes and the comet endpoint in liver cells and peripheral blood cells in addition to the Pig-a assay; appropriate positive controls were included for each assay. Within these studies, potential toxicity of acetaminophen was evaluated and confirmed by inclusion of liver damage biomarkers and histopathology. Blood was sampled pre-treatment and at multiple time points up to Day 57. Pig-a mutant frequencies were determined in total red blood cells (RBCs) and reticulocytes (RETs) as CD59-negative RBC and CD59-negative RET frequencies, respectively. No increases in DNA damage as indicated through Pig-a, micronucleus, or comet endpoints were seen in treated rats. All positive controls responded as appropriate. Data from this series of studies demonstrate that acetaminophen is not mutagenic in the rat Pig-a model. These data are consistent with multiple studies in other nonclinical models, which have shown that acetaminophen is not mutagenic. At 1,000 mg·kg-1 ·day-1 , Cmax values of acetaminophen on Day 28 were 153,600 ng/ml and 131,500 ng/ml after single and repeat dosing, respectively, which were multiples over that of clinical therapeutic exposures (2.6-6.1 fold for single doses of 4,000 mg and 1,000 mg, respectively, and 11.5 fold for multiple dose of 4,000 mg) (FDA 2002). Data generated were of high quality and valid for contribution to the international multilaboratory validation of the in vivo Rat Pig-a Mutation Assay.

A comparison of transgenic rodent mutation and in vivo comet assay responses for 91 chemicals.

A database of 91 chemicals with published data from both transgenic rodent mutation (TGR) and rodent comet assays has been compiled. The objective was to compare the sensitivity of the two assays for detecting genotoxicity. Critical aspects of study design and results were tabulated for each dataset. There were fewer datasets from rats than mice, particularly for the TGR assay, and therefore, results from both species were combined for further analysis. TGR and comet responses were compared in liver and bone marrow (the most commonly studied tissues), and in stomach and colon evaluated either separately or in combination with other GI tract segments. Overall positive, negative, or equivocal test results were assessed for each chemical across the tissues examined in the TGR and comet assays using two approaches: 1) overall calls based on weight of evidence (WoE) and expert judgement, and 2) curation of the data based on a priori acceptability criteria prior to deriving final tissue specific calls. Since the database contains a high prevalence of positive results, overall agreement between the assays was determined using statistics adjusted for prevalence (using AC1 and PABAK). These coefficients showed fair or moderate to good agreement for liver and the GI tract (predominantly stomach and colon data) using WoE, reduced agreement for stomach and colon evaluated separately using data curation, and poor or no agreement for bone marrow using both the WoE and data curation approaches. Confidence in these results is higher for liver than for the other tissues, for which there were less data. Our analysis finds that comet and TGR generally identify the same compounds (mainly potent mutagens) as genotoxic in liver, stomach and colon, but not in bone marrow. However, the current database content precluded drawing assay concordance conclusions for weak mutagens and non-DNA reactive chemicals.