An update on the genotoxicity and carcinogenicity of marketed pharmaceuticals with reference to in silico predictivity

Characterization and Analytical Method Validation for Potential Impurities of a Merchantability Drug Substance Fluoxetine HCl

A new selective and sensitive high-performance liquid chromatography (HPLC) method was developed for the quantification of potential impurities in fluoxetine hydrochloride. Chromatographic separation was achieved on an end-capped octadecylsilyl silica gel (Gemini-C18 150 mm × 4.6 mm, 3.0 μm) using a gradient program with triethylamine, methanol, and water as the mobile phase at a flow rate of 1.0 mL/min and monitored at 215 nm. The run time was 60 min. The method was validated to fulfill International Conference on Harmonization (ICH Q2(R2)) requirements, and this validation included specificity, precision, linearity, limit of detection (LOD), limit of quantification (LOQ), and accuracy. The calibration curve was linear over the concentration range from LOQ to 120% with respect to sample concentration. The accuracy of the method is within the acceptable limit of 80%-120%. The results obtained for all parameters were within the acceptance criteria. So, this method can be employed for the regular analysis of potential impurities in the fluoxetine hydrochloride API.

Interpreting Neural Network Models for Toxicity Prediction by Extracting Learned Chemical Features

Neural network models have become a popular machine-learning technique for the toxicity prediction of chemicals. However, due to their complex structure, it is difficult to understand predictions made by these models which limits confidence. Current techniques to tackle this problem such as SHAP or integrated gradients provide insights by attributing importance to the input features of individual compounds. While these methods have produced promising results in some cases, they do not shed light on how representations of compounds are transformed in hidden layers, which constitute how neural networks learn. We present a novel technique to interpret neural networks which identifies chemical substructures in training data found to be responsible for the activation of hidden neurons. For individual test compounds, the importance of hidden neurons is determined, and the associated substructures are leveraged to explain the model prediction. Using structural alerts for mutagenicity from the Derek Nexus expert system as ground truth, we demonstrate the validity of the approach and show that model explanations are competitive with and complementary to explanations obtained from an established feature attribution method.

Induction of clastogenesis and gene mutations by carbamazepine (at its therapeutically effective serum levels) in mammalian cells and the dependence on human CYP2B6 enzyme activity

Carbamazepine (CBZ, an antiepileptic) is metabolized by multiple CYP enzymes to its epoxide and hydroxides; however, whether it is genotoxic remains unclear. In this study, molecular docking (CBZ to CYPs) and cytogenotoxic toxicity assays were employed to investigate the activation of CBZ for mutagenic effects, in various mammalian cell models. Docking results indicated that CBZ was valid as a substrate of human CYP2B6 and 2E1, while not for CYP1A1, 1A2, 1B1 or 3A4. In the Chinese hamster (V79) cell line and its derivatives genetically engineered for the expression of human CYP1A1, 1A2, 1B1, 2E1 or 3A4 CBZ (2.5 ~ 40 μM) did not induce micronucleus, while in human CYP2B6-expressing cells CBZ significantly induced micronucleus formation. In a human hepatoma C3A cell line, which endogenously expressed CYP2B6 twofold higher than in HepG2 cells, CBZ induced micronucleus potently, which was blocked by 1-aminobenzotriazole (inhibitor of CYPs) and ticlopidine (specific CYP2B6 inhibitor). In HepG2 cells CBZ did not induce micronucleus; however, pretreatment of the cells with CICTO (CYP2B6 inducer) led to micronucleus formation by CBZ, while rifampicin (CYP3A4 inducer) or PCB126 (CYP1A inducer) did not change the negative results. Immunofluorescent assay showed that CBZ selectively induced centromere-free micronucleus. Moreover, CBZ induced double-strand DNA breaks (γ-H2AX elevation, by Western blot) and PIG-A gene mutations (by flowcytometry) in C3A (threshold being 5 μM, lower than its therapeutic serum concentrations, 17 ~ 51 μM), with no effects in HepG2 cells. Clearly, CBZ may induce clastogenesis and gene mutations at its therapeutic concentrations, human CYP2B6 being a major activating enzyme.

Human genetic risk of treatment with antiviral nucleoside analog drugs that induce lethal mutagenesis: The special case of molnupiravir

This review considers antiviral nucleoside analog drugs, including ribavirin, favipiravir, and molnupiravir, which induce genome error catastrophe in SARS-CoV or SARS-CoV-2 via lethal mutagenesis as a mode of action. In vitro data indicate that molnupiravir may be 100 times more potent as an antiviral agent than ribavirin or favipiravir. Molnupiravir has recently demonstrated efficacy in a phase 3 clinical trial. Because of its anticipated global use, its relative potency, and the reported in vitro "host" cell mutagenicity of its active principle, β-d-N4-hydroxycytidine, we have reviewed the development of molnupiravir and its genotoxicity safety evaluation, as well as the genotoxicity profiles of three congeners, that is, ribavirin, favipiravir, and 5-(2-chloroethyl)-2'-deoxyuridine. We consider the potential genetic risks of molnupiravir on the basis of all available information and focus on the need for additional human genotoxicity data and follow-up in patients treated with molnupiravir and similar drugs. Such human data are especially relevant for antiviral NAs that have the potential of permanently modifying the genomes of treated patients and/or causing human teratogenicity or embryotoxicity. We conclude that the results of preclinical genotoxicity studies and phase 1 human clinical safety, tolerability, and pharmacokinetics are critical components of drug safety assessments and sentinels of unanticipated adverse health effects. We provide our rationale for performing more thorough genotoxicity testing prior to and within phase 1 clinical trials, including human PIG-A and error corrected next generation sequencing (duplex sequencing) studies in DNA and mitochondrial DNA of patients treated with antiviral NAs that induce genome error catastrophe via lethal mutagenesis.

GFP-fused yeast cells as whole-cell biosensors for genotoxicity evaluation of nitrosamines

Nitrosamine compounds, represented by N-nitrosodimethylamine, are regarded as potentially genotoxic impurities (PGIs) due to their hazard warning structure, which has attracted great attention of pharmaceutical companies and regulatory authorities. At present, great research gaps exist in genotoxicity assessment and carcinogenicity comparison of nitrosamine compounds. In this work, a collection of GFP-fused yeast cells representing DNA damage repair pathways were used to evaluate the genotoxicity of eight nitrosamine compounds (10^-6-10⁵ μg/mL). The high-resolution expression profiles of GFP-fused protein revealed the details of the DNA damage repair of nitrosamines. Studies have shown that nitrosamine compounds can cause extensive DNA damage and activate multiple repair pathways. The evaluation criteria based on the total expression level of protein show a good correlation with the mammalian carcinogenicity data TD₅₀, and the yeast cell collection can be used as a potential reliable criterion for evaluating the carcinogenicity of compounds. The assay based on DNA damage pathway integration has high sensitivity and can be used as a supplementary method for the evaluation of trace PGIs in actual production. KEY POINTS: • The genotoxicity mechanism of nitrosamines was systematically studied. • The influence of compound structure on the efficacy of genotoxicity was explored. • GFP-fused yeast cells have the potential to evaluate impurities in production.

Mutation as a Toxicological Endpoint for Regulatory Decision-Making

Mutations induced in somatic cells and germ cells are responsible for a variety of human diseases, and mutation per se has been considered an adverse health concern since the early part of the 20th Century. Although in vitro and in vivo somatic cell mutation data are most commonly used by regulatory agencies for hazard identification, that is, determining whether or not a substance is a potential mutagen and carcinogen, quantitative mutagenicity dose-response data are being used increasingly for risk assessments. Efforts are currently underway to both improve the measurement of mutations and to refine the computational methods used for evaluating mutation data. We recommend continuing the development of these approaches with the objective of establishing consensus regarding the value of including the quantitative analysis of mutation per se as a required endpoint for comprehensive assessments of toxicological risk. Environ. Mol. Mutagen. 61:34-41, 2020. © 2019 Wiley Periodicals, Inc.

Association Between Anti-bacterial Drug Use and Digestive System Neoplasms: A Systematic Review and Meta-analysis

Background: Anti-bacterial drugs are thought to be associated with several malignancies. Objective: We conducted a systematic review and meta-analysis to assess the association between antibacterial drug exposure and the risk of digestive system neoplasms. Methods: Relevant publications reporting a relationship between antibiotic use and the risk of cancer were identified in PubMed, EMBASE, and Cochrane Central Register through June 2018. The random-effects model was selected to pool the risk ratios (RRs) and determine 95% confidence intervals (95% CIs). We performed subgroup analyses by tumor organ site, individual antibacterial drug class, and drug dose accumulation. Results: A total of 17 eligible studies (four randomized trials and 13 observational studies) involving 77,284 cancer patients were included in our analyses. Anti-bacterial drug exposure slightly increased the risk of overall digestive system cancer (RR, 1.12; 95% CI, 1.10-1.14), stomach and small intestine (RR, 1.12; 95% CI, 1.07-1.17), anorectocolonic (RR, 1.08; 95% CI, 1.05-1.12), and hepatobiliary and pancreatic cancers (RR, 1.18; 95% CI, 1.14-1.22). For different anti-bacterial drugs classes, nitroimidazoles (RR, 1.17; 95% CI, 1.09-1.26) and quinolones (RR, 1.18; 95% CI, 1.11-1.26) showed a modest association with the risk of cancers incidence. The risks of digestive system cancers increased with the rise of drug dose accumulation: low (RR, 1.08; 95% CI, 1.05-1.11), intermediate (RR, 1.15; 95% CI, 1.12-1.18), and high (RR, 1.22; 95% CI, 1.18-1.26). Conclusions: Anti-bacterial drug exposure was associated with the risks of digestive system cancer occurrence in our analysis.

CYTOTOXIC EFFECTS OF ARIPIPRAZOLE ON MKN45 AND NIH3T3 CELL LINES AND GENOTOXIC EFFECTS ON HUMAN PERIPHERAL BLOOD LYMPHOCYTES

ABSTRACT BACKGROUND: Gastric cancer is known as the fourth most common cancer. Current treatments for cancer have damaged the sensitive tissues of the healthy body, and in many cases, cancer will be recurrent. Therefore, need for treatments that are more effective is well felt. Researchers have recently shifted their attention towards antipsychotic dopamine antagonists to treat cancer. The anticancer activities of aripiprazole remain unknown. OBJECTIVE: This study aimed to evaluate the efficacy and safety of aripiprazole on gastric cancer and normal cell lines. METHODS: In this regard, the cytotoxicity and genotoxicity of aripiprazole were investigated in MKN45 and NIH3T3 cell lines by methyl tetrazolium assay and on peripheral blood lymphocytes by micronucleus assay. For this purpose, cells were cultured in 96 wells plate. Stock solutions of aripiprazole and cisplatin were prepared. After cell incubation with different concentrations of aripiprazole (1, 10, 25, 50, 100 and 200 μL), methyl tetrazolium solution was added. For micronucleus assay fresh blood was added to RPMI culture medium 1640 supplemented, and different concentrations of aripiprazole (50, 100 and 200 μL) were added. RESULTS: The finding of present study showed that the IC50 of aripiprazole in the cancer cell line (21.36 μg/mL) was lower than that in the normal cell line (54.17 μg/mL). Moreover, the micronucleus assay showed that the frequency of micronuclei of aripiprazole at concentrations below 200 μM was much less than cisplatin. CONCLUSION: Aripiprazole can be a good cytotoxic compound and good candidate for further studies of cancer therapy.

Improvement of quantitative structure-activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project

The International Conference on Harmonization (ICH) M7 guideline allows the use of in silico approaches for predicting Ames mutagenicity for the initial assessment of impurities in pharmaceuticals. This is the first international guideline that addresses the use of quantitative structure–activity relationship (QSAR) models in lieu of actual toxicological studies for human health assessment. Therefore, QSAR models for Ames mutagenicity now require higher predictive power for identifying mutagenic chemicals. To increase the predictive power of QSAR models, larger experimental datasets from reliable sources are required. The Division of Genetics and Mutagenesis, National Institute of Health Sciences (DGM/NIHS) of Japan recently established a unique proprietary Ames mutagenicity database containing 12140 new chemicals that have not been previously used for developing QSAR models. The DGM/NIHS provided this Ames database to QSAR vendors to validate and improve their QSAR tools. The Ames/QSAR International Challenge Project was initiated in 2014 with 12 QSAR vendors testing 17 QSAR tools against these compounds in three phases. We now present the final results. All tools were considerably improved by participation in this project. Most tools achieved >50% sensitivity (positive prediction among all Ames positives) and predictive power (accuracy) was as high as 80%, almost equivalent to the inter-laboratory reproducibility of Ames tests. To further increase the predictive power of QSAR tools, accumulation of additional Ames test data is required as well as re-evaluation of some previous Ames test results. Indeed, some Ames-positive or Ames-negative chemicals may have previously been incorrectly classified because of methodological weakness, resulting in false-positive or false-negative predictions by QSAR tools. These incorrect data hamper prediction and are a source of noise in the development of QSAR models. It is thus essential to establish a large benchmark database consisting only of well-validated Ames test results to build more accurate QSAR models.

Cytogenotoxic effects of venlafaxine hydrochloride on cultured human peripheral blood lymphocytes

The potential genotoxic effect of venlafaxine hydrochloride (venlafaxine), an antidepressant drug-active ingredient, was investigated by using in vitro chromosome aberrations (CAs) and cytokinesis-block micronucleus (CBMN) assays in human peripheral blood lymphocytes (PBLs). Mitotic index (MI) and cytokinesis-block proliferation index (CBPI) were also calculated to determine the cytotoxicity of this active drug. For this aim, the human PBLs were treated with 25, 50, and 100 µg/ml venlafaxine for 24 h and 48 h. The results of this study showed that venlafaxine significantly induced the formation of structural CA and MN for all concentrations (25, 50, and 100 µg/ml) and treatment periods (24 h and 48 h) when compared with the negative and the solvent control (except 25 µg/ml at 48 h for MN). In addition, the increases in the percentage of structural CA and MN were concentration-dependent for both treatment times. With regard to cell cycle kinetics, venlafaxine significantly decreased the MI at all concentrations, and also CBPI at the higher concentrations for both treatment times as compared to the control groups. The present results indicate for the first time that venlafaxine had significant clastogenic and cytotoxic effects at the tested concentrations (25, 50, and 100 µg/ml) in the human PBLs, in vitro; therefore, its excessive and careless use may pose a potential risk to human health.

Update of the Scientific Opinion on opium alkaloids in poppy seeds

Poppy seeds are obtained from the opium poppy (Papaver somniferum L.). They are used as food and to produce edible oil. The opium poppy plant contains narcotic alkaloids such as morphine and codeine. Poppy seeds do not contain the opium alkaloids, but can become contaminated with alkaloids as a result of pest damage and during harvesting. The European Commission asked EFSA to provide an update of the Scientific Opinion on opium alkaloids in poppy seeds. The assessment is based on data on morphine, codeine, thebaine, oripavine, noscapine and papaverine in poppy seed samples. The CONTAM Panel confirms the acute reference dose (ARfD) of 10 μg morphine/kg body weight (bw) and concluded that the concentration of codeine in the poppy seed samples should be taken into account by converting codeine to morphine equivalents, using a factor of 0.2. The ARfD is therefore a group ARfD for morphine and codeine, expressed in morphine equivalents. Mean and high levels of dietary exposure to morphine equivalents from poppy seeds considered to have high levels of opium alkaloids (i.e. poppy seeds from varieties primarily grown for pharmaceutical use) exceed the ARfD in most age groups. For poppy seeds considered to have relatively low concentrations of opium alkaloids (i.e. primarily varieties for food use), some exceedance of the ARfD is also seen at high levels of dietary exposure in most surveys. For noscapine and papaverine, the available data do not allow making a hazard characterisation. However, comparison of the dietary exposure to the recommended therapeutical doses does not suggest a health concern for these alkaloids. For thebaine and oripavine, no risk characterisation was done due to insufficient data. However, for thebaine, limited evidence indicates a higher acute lethality than for morphine and the estimated exposure could present a health risk.

QSAR ligand dataset for modelling mutagenicity, genotoxicity, and rodent carcinogenicity

Five datasets were constructed from ligand and bioassay result data from the literature. These datasets include bioassay results from the Ames mutagenicity assay, Greenscreen GADD-45a-GFP assay, Syrian Hamster Embryo (SHE) assay, and 2 year rat carcinogenicity assay results. These datasets provide information about chemical mutagenicity, genotoxicity and carcinogenicity.

Combining machine learning models of in vitro and in vivo bioassays improves rat carcinogenicity prediction

In vitro genotoxicity bioassays are cost-efficient methods of assessing potential carcinogens. However, many genotoxicity bioassays are inappropriate for detecting chemicals eliciting non-genotoxic mechanisms, such as tumour promotion, this necessitates the use of in vivo rodent carcinogenicity (IVRC) assays. In silico IVRC modelling could potentially address the low throughput and high cost of this assay. We aimed to develop and combine computational QSAR models of novel bioassays for the prediction of IVRC results and compare with existing software. QSAR models were generated from existing Ames (n = 6512), Syrian Hamster Embryonic (SHE, n = 410), ISSCAN rodent carcinogenicity (ISC, n = 834) and GreenScreen GADD45a-GFP (n = 1415) chemical datasets. These models mapped the molecular descriptors of each compound to their respective assay result using machine learning algorithms (adaboost, k-Nearest Neighbours, C.45 Decision Tree, Multilayer Perceptron, Random Forest). The best performing models were combined with k-Nearest Neighbours to create a cascade model for IVRC prediction. High QSAR model performance was observed from ten time 10-fold cross-validation with above 80% accuracy and 0.85 AUC for each assay dataset. The cascade model predicted rat carcinogenicity with 69.3% accuracy and 0.700 AUC. This study demonstrates the novelty of a combined approach for IVRC prediction, with higher performance than existing software.

International regulatory requirements for genotoxicity testing for pharmaceuticals used in human medicine, and their impurities and metabolites

The process of developing international (ICH) guidelines is described, and the main guidelines reviewed are the ICH S2(R1) guideline that includes the genotoxicity test battery for human pharmaceuticals, and the ICH M7 guideline for assessing and limiting potentially mutagenic impurities and degradation products in drugs. Key aspects of the guidelines are reviewed in the context of drug development, for example the incorporation of genotoxicity assessment into non-clinical toxicity studies, and ways to develop and assess weight of evidence. In both guidelines, the existence of "thresholds" or non-linear dose responses for genotoxicity plays a part in the strategies. Differences in ICH S2(R1) protocol recommendations from OECD guidelines are highlighted and rationales explained. The use of genotoxicity data during clinical development and in assessment of carcinogenic potential is also described. There are no international guidelines on assessment of potentially genotoxic metabolites, but some approaches to safety assessment are discussed for these. Environ. Mol. Mutagen. 58:296-324, 2017. © 2017 Wiley Periodicals, Inc.

A Quantitative Toxicogenomics Assay for High-throughput and Mechanistic Genotoxicity Assessment and Screening of Environmental Pollutants

The ecological and health concern of mutagenicity and carcinogenicity potentially associated with an overwhelmingly large and ever-increasing number of chemicals demands for cost-effective and feasible method for genotoxicity screening and risk assessment. This study proposed a genotoxicity assay using GFP-tagged yeast reporter strains, covering 38 selected protein biomarkers indicative of all the seven known DNA damage repair pathways. The assay was applied to assess four model genotoxic chemicals, eight environmental pollutants and four negative controls across six concentrations. Quantitative molecular genotoxicity end points were derived based on dose response modeling of a newly developed integrated molecular effect quantifier, Protein Effect Level Index (PELI). The molecular genotoxicity end points were consistent with multiple conventional in vitro genotoxicity assays, as well as with in vivo carcinogenicity assay results. Further more, the proposed genotoxicity end point PELI values quantitatively correlated with both comet assay in human cell and carcinogenicity potency assay in mice, providing promising evidence for linking the molecular disturbance measurements to adverse outcomes at a biological relevant level. In addition, the high-resolution DNA damaging repair pathway alternated protein expression profiles allowed for chemical clustering and classification. This toxicogenomics-based assay presents a promising alternative for fast, efficient and mechanistic genotoxicity screening and assessment of drugs, foods, and environmental contaminants.

Frequent Use of Antibiotics Is Associated with Colorectal Cancer Risk: Results of a Nested Case-Control Study

BACKGROUND

Microbiotical dysbiosis induced by a Western diet seems to be associated with an increased risk of developing colorectal cancer (CRC). Few other factors with an effect on the colonic microbiota and their association with CRC have been evaluated.

AIM

We investigated whether the use of antibiotics is associated with CRC risk.

METHODS

Data on the use of antibiotics and comedication were extracted from a health insurance database for subjects with a diagnostic-related group for CRC between 2006 and 2011 and four age- and sex-matched controls. Antibiotic use was categorized according to the number of prescriptions during a 5-year follow-up period (1-6 years prior to CRC). Multivariable conditional binary logistic regression analysis was used to estimate odds ratios (ORs) and 95 % confidence intervals (95 % CIs) for different levels of use.

RESULTS

A total of 4029 cases (47 % male, mean age at diagnosis 71 ± 11 years) and 15,988 controls were included. Antibiotics had been prescribed to 2630 (65.3 %) cases and 10,234 (64.0 %) controls (p = 0.13). An increasing use of antibiotics was associated with an increasing risk of CRC [multivariable OR for high (≥8 prescriptions) vs. no prescriptions: 1.26, 95 % CI 1.11-1.44, p-trend <0.01]. For each increase of 5 prescriptions, the OR for CRC was 1.05 (95 % CI 1.01-1.09).

CONCLUSION

We found an association between the use of antibiotics, especially when used frequently, and the risk of developing CRC. Further studies are needed to establish under which conditions the use of antibiotics increases the risk of developing CRC.

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.

In vitro genotoxicity and cytotoxicity of a particular combination of pemetrexed and cefixime in human peripheral blood lymphocytes

This study aims to find the genotoxic and cytotoxic effects of a particular combination of pemetrexed (PMX) and cefixime (CFX) in human peripheral blood lymphocytes. Chromosome aberration (CA), sister chromatid exchange (SCE), and micronucleus (MN) tests were used to assess genotoxicity. Whereas, the cytotoxicity was evaluated by using mitotic index (MI), proliferation index (PI), and nuclear division index (NDI). Our tests were proceeded with concentrations of 12.5 + 450, 25 + 800, 37.5 + 1150, and 50 + 1500 μg/mL of a mixture of PMX and CFX separately for 24 hr and 48 hr.

The combination of PMX + CFX did not induce the CA or SCE in human peripheral blood lymphocytes when compared with both the control and the solvent control. MN in human peripheral blood lymphocytes was not significantly increased after treatment with a particular combination of PMX + CFX. However, PMX + CFX significantly decreased the MI, PI and NDI at all concentrations for 24- and 48-hr treatment periods when compared with both controls. Generally, PMX + CFX inhibited cell proliferation more than positive control (MMC) and showed a higher cytotoxic effect than MMC at both treatment periods. These results were compared with individual effects of PMX and CFX. As a result, it was observed that a particular combination of PMX + CFX was not genotoxic. However, the combination synergistically increase cytotoxicity in human peripheral blood lymphocytes.

Usefulness of monitoring γ-H2AX and cell cycle arrest in HepG2 cells for estimating genotoxicity using a high-content analysis system

Formation of the phosphorylated protein γ-H2AX is a well-established marker of DNA strand breakage induced by DNA-damaging compounds. Many of these genotoxic compounds also inhibit cell division, leading to arrest at specific points in the cell cycle. Detection of γ-H2AX in combination with cell cycle arrest may therefore be useful for estimating the genotoxicity of experimental compounds. In this study, we examined γ-H2AX formation and cell cycle arrest using high-content screening (HCS) as a method for determining genotoxicity. HepG2 cells were treated with a panel of compounds and then stained with Hoechst 33342 and anti-γ-H2AX, anti-phospho-histone H3, and anti-tubulin antibodies. In total, 19 genotoxic and 7 nongenotoxic compounds were tested in this study. γ-H2AX production was observed within 1 h posttreatment for the majority of Ames-positive compounds, topoisomerase inhibitors, and DNA polymerase inhibitors. Cell cycle arrest in either the S or G2 phase was detected for all DNA-damaging compounds 24 h posttreatment, whereas tubulin-targeting compounds were shown to induce cell cycle arrest in the mitotic phase. Together, these results show that HCS is a simple, rapid, and effective tool for estimating the genotoxicity of compounds through detection of γ-H2AX production and cell cycle arrest.

Prediction of noncovalent Drug/DNA interaction using computational docking models: studies with over 1350 launched drugs

Noncovalent chemical/DNA interactions, for example, intercalation and groove-binding, may be more important to genomic integrity than previously appreciated, and there may very well be genotoxic consequences of that binding. It is of importance, then, to develop methods allowing a determination or prediction of such interactions. This would have particular utility in the pharmaceutical industry where genotoxicity is, for the most part, disallowed in new drug entities. We have previously used DNA docking simulations to assess if molecules had structure and charge characteristics which could accommodate noncovalent binding via, for example, electrostatic/hydrogen bonding. We here extend those earlier studies by examining a series of over 1,350 "launched" drugs for ability to noncovalently bind 10 different DNA sequences using two computational programs: Autodock and Surflex. These drugs were also evaluated for binding to the crystallographic ATP-binding site of human topoisomerase II. The results obtained clearly demonstrate multiple series of noncovalent DNA binding structure activity relationships which would not have been predicted based on cursory structural examination. Many drugs within these series are genotoxic although not via any commonly recognized structural covalent alerts. The present studies confirm previously implicated features such as N-dialkyl groups and specific N-aryl ketones as potential genotoxic chemical moieties acting through noncovalent mechanisms. These initial studies provide considerable evidence that DNA intercalation may be an important, largely overlooked, source of drug-induced genotoxicity and further suggest involvement of topoisomerase in that genotoxicity.

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry(SM), a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90% was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84±1% sensitivity, 81±1% specificity, 83±1% concordance and 79±1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity.

Use of buccal micronucleus assay to determine mutagenicity induced by amfepramone in humans and the protective effects of vitamin C

The abusive use of amfepramone in Brazilian population has grown in recent years. Few studies have been conducted on amphetamine with respect to DNA damage, and there have been no apparent investigations examining the influence of amfepramone on humans. The aim of this study was to determine the possible mutagenic actions of amfepramone on humans using the micronucleus (MN) assay with buccal cells and the effects of supplementation with vitamin C as a potential protective agent. The study included 108 females with 52 as control and 56 taking amfepramone at 120 mg/d for at least the whole previous month. All women were intentionally selected to be nonsmokers and nondrinkers. After 30 d of amfepramone women were given amfepramone plus vitamin C use at 1000 mg/d for another month. Results showed a marked increase in the number of MN in amfepramone users in both basal and differentiated cells, indicating a mutagenic action. After vitamin C supplementation, a significant decrease in the frequency of MN and apoptosis was observed. Evidence indicates that the main mechanism of action of amfepramone in inducing DNA damage occurs through formation of reactive oxygen species (ROS), intercalation and topoisomerase binding, attributed to the presence of an N-dialkyl group. In addition, data demonstrated that vitamin C effectively inhibited amfepramone-induced DNA damage.

Predictive computational toxicology to support drug safety assessment

Use of predictive technologies is an important aspect of many efforts in today's research, development, and regulatory landscapes. Computational methods as predictive tools for supporting drug safety assessments is of widespread interest as the field of in silico assessments rapidly changes with emerging technologies and the large amount of existing data available for modeling. There are challenges associated with application of in silico analyses for drug toxicity predictions and need for strategies and harmonization to enable an acceptable in silico evaluation for prediction of specific toxicity assay outcomes. This chapter will provide an overview focused on computational tools using structure-activity relationships and will highlight initiatives for use of computational assessments and realistic applications for predictive modeling in evaluating potential toxicities of drug-related molecules.

From QSAR to QSIIR: searching for enhanced computational toxicology models

Quantitative structure activity relationship (QSAR) is the most frequently used modeling approach to explore the dependency of biological, toxicological, or other types of activities/properties of chemicals on their molecular features. In the past two decades, QSAR modeling has been used extensively in drug discovery process. However, the predictive models resulted from QSAR studies have limited use for chemical risk assessment, especially for animal and human toxicity evaluations, due to the low predictivity of new compounds. To develop enhanced toxicity models with independently validated external prediction power, novel modeling protocols were pursued by computational toxicologists based on rapidly increasing toxicity testing data in recent years. This chapter reviews the recent effort in our laboratory to incorporate the biological testing results as descriptors in the toxicity modeling process. This effort extended the concept of QSAR to quantitative structure in vitro-in vivo relationship (QSIIR). The QSIIR study examples provided in this chapter indicate that the QSIIR models that based on the hybrid (biological and chemical) descriptors are indeed superior to the conventional QSAR models that only based on chemical descriptors for several animal toxicity endpoints. We believe that the applications introduced in this review will be of interest and value to researchers working in the field of computational drug discovery and environmental chemical risk assessment.

Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities

The toxicological assessment of genotoxic impurities is important in the regulatory framework for pharmaceuticals. In this context, the application of promising computational methods (e.g. Quantitative Structure-Activity Relationships (QSARs), Structure-Activity Relationships (SARs) and/or expert systems) for the evaluation of genotoxicity is needed, especially when very limited information on impurities is available. To gain an overview of how computational methods are used internationally in the regulatory assessment of pharmaceutical impurities, the current regulatory documents were reviewed. The software recommended in the guidelines (e.g. MCASE, MC4PC, Derek for Windows) or used practically by various regulatory agencies (e.g. US Food and Drug Administration, US and Danish Environmental Protection Agencies), as well as other existing programs were analysed. Both statistically based and knowledge-based (expert system) tools were analysed. The overall conclusions on the available in silico tools for genotoxicity and carcinogenicity prediction are quite optimistic, and the regulatory application of QSAR methods is constantly growing. For regulatory purposes, it is recommended that predictions of genotoxicity/carcinogenicity should be based on a battery of models, combining high-sensitivity models (low rate of false negatives) with high-specificity ones (low rate of false positives) and in vitro assays in an integrated manner.

Recent trends in statistical QSAR modeling of environmental chemical toxicity

Quantitative cheminformatics approaches such as QSAR modeling find growing applications in chemical risk assessment. Traditional methods rely on the use of calculated chemical descriptors of molecules and relatively small training sets. However, in recent years, there is a trend toward the increased use of in vitro biological testing approaches to reduce both the length of experimental studies and the animal use for chemical risk assessment. Furthermore, there is also much greater emphasis on model validation using external datasets to enable the reliable use of computational models as part of regulatory decision making. In this chapter, recent trends emphasizing the need for both careful curation of experimental data prior to model development and rigorous model validation are investigated. Furthermore, recent approaches to chemical toxicity prediction that employ both chemical descriptors and in vitro screening data for developing novel hybrid chemical/biological models are being reviewed. Examples of respective application studies that employ novel workflows for model developments are described and recent important efforts by several academic, nonprofit, and industrial groups to start placing both data and, especially, models in the public domain are discussed.

Genetic toxicology in the 21st century: reflections and future directions

A symposium at the 40th anniversary of the Environmental Mutagen Society, held from October 24-28, 2009 in St. Louis, MO, surveyed the current status and future directions of genetic toxicology. This article summarizes the presentations and provides a perspective on the future. An abbreviated history is presented, highlighting the current standard battery of genotoxicity assays and persistent challenges. Application of computational toxicology to safety testing within a regulatory setting is discussed as a means for reducing the need for animal testing and human clinical trials, and current approaches and applications of in silico genotoxicity screening approaches across the pharmaceutical industry were surveyed and are reported here. The expanded use of toxicogenomics to illuminate mechanisms and bridge genotoxicity and carcinogenicity, and new public efforts to use high-throughput screening technologies to address lack of toxicity evaluation for the backlog of thousands of industrial chemicals in the environment are detailed. The Tox21 project involves coordinated efforts of four U.S. Government regulatory/research entities to use new and innovative assays to characterize key steps in toxicity pathways, including genotoxic and nongenotoxic mechanisms for carcinogenesis. Progress to date, highlighting preliminary test results from the National Toxicology Program is summarized. Finally, an overview is presented of ToxCast™, a related research program of the U.S. Environmental Protection Agency, using a broad array of high throughput and high content technologies for toxicity profiling of environmental chemicals, and computational toxicology modeling. Progress and challenges, including the pressing need to incorporate metabolic activation capability, are summarized.

Moving forward in human cancer risk assessment

BACKGROUND

The current safety paradigm for assessing carcinogenic properties of drugs, cosmetics, industrial chemicals, and environmental exposures relies mainly on in vitro genotoxicity testing followed by 2-year rodent bioassays. This testing battery is extremely sensitive but has low specificity. Furthermore, rodent bioassays are associated with high costs, high animal burden, and limited predictive value for human risks.

OBJECTIVES

We provide a response to a growing appeal for a paradigm change in human cancer risk assessment.

METHODS

To facilitate development of a road map for this needed paradigm change in carcinogenicity testing, a workshop titled "Genomics in Cancer Risk Assessment" brought together toxicologists from academia and industry and government regulators and risk assessors from the United States and the European Union. Participants discussed the state-of-the-art in developing alternative testing strategies for carcinogenicity, with emphasis on potential contributions from omics technologies.

RESULTS AND CONCLUSIONS

The goal of human risk assessment is to decide whether a given exposure to an agent is acceptable to human health and to provide risk management measures based on evaluating and predicting the effects of exposures on human health. Although exciting progress is being made using genomics approaches, a new paradigm that uses these methods and human material when possible would provide mechanistic insights that may inform new predictive approaches (e.g., in vitro assays) and facilitate the development of genomics-derived biomarkers. Regulators appear to be willing to accept such approaches where use is clearly defined, evidence is strong, and approaches are qualified for regulatory use.

Overall impact of the regulatory requirements for genotoxic impurities on the drug development process

In the last decade a considerable effort has been made both by the regulators and the pharmaceutical industry to assess genotoxic impurities (GTI) in pharmaceutical products. Though the control of impurities in drug substances and products is a well established and consolidated procedure, its extension to GTI has given rise to a number of problems, both in terms of setting the limits and detecting these impurities in pharmaceutical products. Several papers have dealt with this issue, discussing available regulations, providing strategies to evaluate the genotoxic potential of chemical substances, and trying to address the analytical challenge of detecting GTI at trace levels. In this review we would like to discuss the available regulations, the toxicological background for establishing limits, as well as the analytical approaches used for GTI assessment. The final aim is that of providing a complete overview of the topic with updated available information, to address the overall GTI issue during the development of new drug substances.

Potentiation of the mutagenicity and recombinagenicity of bleomycin in yeast by unconventional intercalating agents

Interactions between bleomycin (BLM) and conventional or unconventional intercalating agents were analyzed in an assay for mitotic gene conversion at the trp5 locus and reversion of the ilv1-92 allele in Saccharomyces cerevisiae strain D7. BLM is a potent recombinagen and mutagen in the assay. Various chemicals modulate the genetic activity of BLM, producing either antimutagenic effects or enhanced genotoxicity. Effects of cationic amino compounds include enhancement of BLM activity by aminoacridines and protection against BLM by aliphatic amines. The potentiation of BLM is similar to findings in a micronucleus-based BLM amplification assay in Chinese hamster V79 cells. In this study, the amplification of BLM activity was explored in yeast using known intercalators, compounds structurally related to known intercalators, and unconventional intercalators that were identified on the basis of computer modeling or results in the Chinese hamster BLM amplification assay. As shown in previous studies, the classical intercalator 9-aminoacridine (9AA) caused dose-dependent enhancement of BLM activity. Other compounds found to enhance the induction of mitotic recombination and point mutations in strain D7 were chlorpromazine, chloroquine, mefloquine, tamoxifen, diphenhydramine, benzophenone, and 3-hydroxybenzophenone. The increased activity was detectable by cotreatment of yeast with BLM and the modulator compound in growth medium or by separate interaction of the intercalator with DNA followed by BLM treatment of nongrowing cells in buffer. The data support the interpretation drawn from micronucleus assays in mammalian cells that BLM enhancement results from DNA intercalation and may be useful in detecting noncovalent interactions with DNA. Environ.

In vitro genotoxicity of rocuronium bromide in human peripheral lymphocytes

Rocuronium bromide (RB), an aminosteroid type neuromuscular blocking agent, acts by reducing or inhibiting the depolarising effect of acetylcholine on the terminal disc of the muscle cell. To our knowledge, there is no adequate information on the genotoxic effects of RB, up to now. In the present study, possible genotoxic effects of RB have been determined by means of sister chromatid exchange (SCE), chromosome aberration (CA) and micronucleus (MN) analyses in human peripheral blood lymphocytes. The human peripheral blood lymphocytes were exposed to three different concentrations of RB (60, 80 and 100 μg/mL) for 24- and 48-h. In this study, RB increased the frequency of CAs, however, did not increase the frequency of SCEs. RB did not decrease the proliferation index (PI) and mitotic index (MI). Accordingly, RB increased the frequency of micronucleus (MN) but did not decrease the nuclear division index (NDI). Findings from this study suggest that rocuronium bromide is clastogenic but not cytotoxic to cultured human peripheral blood lymphocytes.