Defined approaches to classify agrochemical formulations into EPA hazard categories developed using EpiOcularTM reconstructed human corneal epithelium and bovine corneal opacity and permeability assays

Many sectors have seen complete replacement of the in vivo rabbit eye test with reproducible and relevant in vitro and ex vivo methods to assess the eye corrosion/irritation potential of chemicals. However, the in vivo rabbit eye test remains the standard test used for agrochemical formulations in some countries. Therefore, two defined approaches (DAs) for assessing conventional agrochemical formulations were developed, using the EpiOcularTM Eye Irritation Test (EIT) [Organisation for Economic Co-operation and Development (OECD) test guideline (TG) 492] and the Bovine Corneal Opacity and Permeability (OECD TG 437; BCOP) test with histopathology. Presented here are the results from testing 29 agrochemical formulations, which were evaluated against the United States Environmental Protection Agency's (EPA) pesticide classification system, and assessed using orthogonal validation, rather than direct concordance analysis with the historical in vivo rabbit eye data. Scientific confidence was established by evaluating the methods and testing results using an established framework that considers fitness for purpose, human biological relevance, technical characterisation, data integrity and transparency, and independent review. The in vitro and ex vivo methods used in the DAs were demonstrated to be as or more fit for purpose, reliable and relevant than the in vivo rabbit eye test. Overall, there is high scientific confidence in the use of these DAs for assessing the eye corrosion/irritation potential of agrochemical formulations.

Standardizing Extracted Data Using Automated Application of Controlled Vocabularies

BACKGROUND

Extraction of toxicological end points from primary sources is a central component of systematic reviews and human health risk assessments. To ensure optimal use of these data, consistent language should be used for end point descriptions. However, primary source language describing treatment-related end points can vary greatly, resulting in large labor efforts to manually standardize extractions before data are fit for use.

OBJECTIVES

To minimize these labor efforts, we applied an augmented intelligence approach and developed automated tools to support standardization of extracted information via application of preexisting controlled vocabularies.

METHODS

We created and applied a harmonized controlled vocabulary crosswalk, consisting of Unified Medical Language System (UMLS) codes, German Federal Institute for Risk Assessment (BfR) DevTox harmonized terms, and The Organization for Economic Co-operation and Development (OECD) end point vocabularies, to roughly 34,000 extractions from prenatal developmental toxicology studies conducted by the National Toxicology Program (NTP) and 6,400 extractions from European Chemicals Agency (ECHA) prenatal developmental toxicology studies, all recorded based on the original study report language.

RESULTS

We automatically applied standardized controlled vocabulary terms to 75% of the NTP extracted end points and 57% of the ECHA extracted end points. Of all the standardized extracted end points, about half (51%) required manual review for potential extraneous matches or inaccuracies. Extracted end points that were not mapped to standardized terms tended to be too general or required human logic to find a good match. We estimate that this augmented intelligence approach saved > 350 hours of manual effort and yielded valuable resources including a controlled vocabulary crosswalk, organized related terms lists, code for implementing an automated mapping workflow, and a computationally accessible dataset.

DISCUSSION

Augmenting manual efforts with automation tools increased the efficiency of producing a findable, accessible, interoperable, and reusable (FAIR) dataset of regulatory guideline studies. This open-source approach can be readily applied to other legacy developmental toxicology datasets, and the code design is customizable for other study types. https://doi.org/10.1289/EHP13215.

Retrospective evaluation of the eye irritation potential of agrochemical formulations

Multiple in vitro eye irritation methods have been developed and adopted as OECD health effects test guidelines. However, for predicting the ocular irritation/damage potential of agrochemical formulations there is an applicability domain knowledge gap for most of the methods. To overcome this gap, a retrospective evaluation of 192 agrochemical formulations with in vivo (OECD TG 405) and in vitro (OECD TG 437, 438, and/or 492) data was conducted to determine if the in vitro methods could accurately assign United Nations Globally Harmonized System for Classification and Labelling of Chemicals (GHS) eye irritation hazard classifications. In addition, for each formulation the eye irritation classification was derived from the classification of the contained hazardous ingredients and their respective concentration in the product using the GHS concentration threshold (CT) approach. The results herein suggest that the three in vitro methods and the GHS CT approach were highly predictive of formulations that would not require GHS classification for eye irritation. Given most agrochemical formulations fall into this category, methods that accurately identify non-classified agrochemical formulations could significantly reduce the use of animals for this endpoint.

Weight of evidence for cross-species conservation of androgen receptor-based biological activity

The U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP) is tasked with assessing chemicals for their potential to perturb endocrine pathways, including those controlled by androgen receptor (AR). To address challenges associated with traditional testing strategies, EDSP is considering in vitro high-throughput screening assays to screen and prioritize chemicals more efficiently. The ability of these assays to accurately reflect chemical interactions in nonmammalian species remains uncertain. Therefore, a goal of the EDSP is to evaluate how broadly results can be extrapolated across taxa. To assess the cross-species conservation of AR-modulated pathways, computational analyses and systematic literature review approaches were used to conduct a comprehensive analysis of existing in silico, in vitro, and in vivo data. First, molecular target conservation was assessed across 585 diverse species based on the structural similarity of ARs. These results indicate that ARs are conserved across vertebrates and are predicted to share similarly susceptibility to chemicals that interact with the human AR. Systematic analysis of over 5000 published manuscripts was used to compile in vitro and in vivo cross-species toxicity data. Assessment of in vitro data indicates conservation of responses occurs across vertebrate ARs, with potential differences in sensitivity. Similarly, in vivo data indicate strong conservation of the AR signaling pathways across vertebrate species, although sensitivity may vary. Overall, this study demonstrates a framework for utilizing bioinformatics and existing data to build weight of evidence for cross-species extrapolation and provides a technical basis for extrapolating hAR-based data to prioritize hazard in nonmammalian vertebrate species.

Evaluation of the fish acute toxicity test for pesticide registration

The U.S. Environmental Protection Agency (USEPA) uses the in vivo fish acute toxicity test to assess potential risk of substances to non-target aquatic vertebrates. The test is typically conducted on a cold and a warm freshwater species and a saltwater species for a conventional pesticide registration, potentially requiring upwards of 200 or more fish. A retrospective data evaluation was conducted to explore the potential for using fewer fish species to support conventional pesticide risk assessments. Lethal concentration 50% (LC₅₀) values and experimental details were extracted and curated from 718 studies on fish acute toxicity submitted to USEPA. The LC₅₀ data were analysed to determine, when possible, the relative sensitivity of the tested species to each pesticide. One of the tested freshwater species was most sensitive in 85% of those cases. The tested cold freshwater species was the most sensitive overall among cases with established relative sensitivity and was within 3X of the LC₅₀ value of the most sensitive species tested in 98% of those cases. The results support potentially using fewer than three fish species to conduct ecological risk assessments for the registration of conventional pesticides.

Data curation to support toxicity assessments using the Integrated Chemical Environment

Humans are exposed to large numbers of chemicals during their daily activities. To assess and understand potential health impacts of chemical exposure, investigators and regulators need access to reliable toxicity data. In particular, reliable toxicity data for a wide range of chemistries are needed to support development of new approach methodologies (NAMs) such as computational models, which offer increased throughput relative to traditional approaches and reduce or replace animal use. NAMs development and evaluation require chemically diverse data sets that are typically constructed by incorporating results from multiple studies into a single, integrated view; however, integrating data is not always a straightforward task. Primary study sources often vary in the way data are organized and reported. Metadata and information needed to support interoperability and provide context are often lacking, which necessitates literature research on the assay prior to attempting data integration. The Integrated Chemical Environment (ICE) was developed to support the development, evaluation, and application of NAMs. ICE provides curated toxicity data and computational tools to integrate and explore available information, thus facilitating knowledge discovery and interoperability. This paper describes the data curation workflow for integrating data into ICE. Data destined for ICE undergo rigorous harmonization, standardization, and formatting processes using both automated and manual expert-driven approaches. These processes improve the utility of the data for diverse analyses and facilitate application within ICE or a user's external workflow while preserving data integrity and context. ICE data curation provides the structure, reliability, and accessibility needed for data to support chemical assessments.

Validation of the OptiSafe™ eye irritation test

PURPOSE

OptiSafe is an in chemico test method that identifies potential eye irritants based on macromolecular damage following test chemical exposure. The OptiSafe protocol includes a prescreen assessment that identifies test chemicals that are outside the applicability domain of the test method and thus determines the optimal procedure. We assessed the usefulness and limitations of the OptiSafe test method for identifying chemicals not requiring classification for ocular irritation (i.e. bottom-up testing strategy).

MATERIALS AND METHODS

Seventeen chemicals were selected by the lead laboratory and tested as an independent study. Ninety-five unique coded chemicals were selected by a validation management team to assess the intra- and interlaboratory reproducibility and accuracy of OptiSafe in a multilaboratory, three-phased validation study. Three laboratories (lead laboratory and two naïve laboratories) evaluated 35 chemicals, with the remaining 60 chemicals evaluated by the lead laboratory only. Test method performance was assessed by comparing classifications based on OptiSafe results to classifications based on available retrospective in vivo data, using both the EPA and GHS eye irritation hazard classification systems. No prospective in vivo testing was conducted.

RESULTS

Phase I testing of five chemicals showed that the method could be transferred to naïve laboratories; within-lab reproducibility ranged from 93% to 100% for both classification systems. Thirty coded chemicals were evaluated in Phase II of the validation study to demonstrate both intra- and interlaboratory reproducibility. Intralaboratory reproducibility for both EPA and GHS classification systems for Phase II of the validation study ranged from 93% to 99%, while interlaboratory reproducibility was 91% for both systems. Test method accuracy for the EPA and GHS classification systems based on results from individual laboratories ranged from 82% to 88% and from 78% to 88%, respectively, among the three laboratories; false negative rates ranged from 0% to 7% (EPA) and 0% to 15% (GHS). When results across all three laboratories were combined based on the majority classification, test method accuracy and false negative rates were 89% and 0%, respectively, for both classification systems, while false positive rates were 25% and 23% for the EPA and GHS classification systems, respectively. Validation study Phase III evaluation of an additional 60 chemicals by the lead laboratory provided a comprehensive assessment of test method accuracy and defined the applicability domain of the method. Based on chemicals tested in Phases II and III by the lead laboratory, test method accuracy was 83% and 79% for the EPA and GHS classification systems, respectively; false negative rates were 4% (EPA) and 0% (GHS); and false positive rates were 40% (EPA) and 42% (GHS). Potential causes of false positives in certain chemical (e.g. ethers and alcohols) or hazard classes are being further investigated.

CONCLUSION

The OptiSafe test method is useful for identifying nonsurfactant substances not requiring classification for ocular irritancy. OptiSafe represents a new tool for the in vitro assessment of ocular toxicity in a tiered-testing strategy where chemicals can be initially tested and identified as not requiring hazard classification.

Evaluation of two in silico programs for predicting mutagenicity and carcinogenicity potential for 4-methylimidazole (4-MeI) and known metabolites

4-Methylimidazole (4-MeI) is a nitrogen-containing heterocyclic compound that is used in the manufacture of chemicals, dyes and pharmaceuticals and may be found in a variety of foods following formation during heating. The purpose of this study was to use two different in silico programs, CASE Ultra and Toxtree, to investigate potential structure-activity relationships in 4-MeI and its metabolites for mutagenicity and carcinogenicity, and combine that information with the available literature to draw conclusions regarding the strength of the predictions observed. Neither CASE Ultra nor Toxtree identified any structural alerts that were associated with mutagenic activity. Data for 4-MeI from a single study were used in the development of the CASE Ultra mouse and rat carcinogenicity models, but no additional similar structures were identified in the carcinogenicity model training set. One metabolite, 5-methylhydantoin, was predicted to be positive in the CASE Ultra carcinogenicity male and female mouse models; positive predictivity percentages of 60.9% and 73.7%, respectively. However, low structural similarity between 5-methylhydantoin and the compounds identified in the training set (<25%) decreases confidence in the positive prediction. Three metabolites were predicted to be positive in the CASE Ultra mouse micronucleus model, but again suffered from low structural similarity. Both limited structural similarity and inconsistent responses among the other clastogenicity models suggest that additional structurally similar compounds are needed to assess the predictive capacity of these alerts for biological activity of these compounds.

In vitro to in vivo extrapolation for high throughput prioritization and decision making

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.

Multivariate models for prediction of human skin sensitization hazard

One of the Interagency Coordinating Committee on the Validation of Alternative Method's (ICCVAM) top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays - the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens™ assay - six physicochemical properties and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches, logistic regression and support vector machine, to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three logistic regression and three support vector machine) with the highest accuracy (92%) used: (1) DPRA, h-CLAT and read-across; (2) DPRA, h-CLAT, read-across and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens and log P. The models performed better at predicting human skin sensitization hazard than the murine local lymph node assay (accuracy 88%), any of the alternative methods alone (accuracy 63-79%) or test batteries combining data from the individual methods (accuracy 75%). These results suggest that computational methods are promising tools to identify effectively the potential human skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Integrated decision strategies for skin sensitization hazard

One of the top priorities of the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) is the identification and evaluation of non-animal alternatives for skin sensitization testing. Although skin sensitization is a complex process, the key biological events of the process have been well characterized in an adverse outcome pathway (AOP) proposed by the Organisation for Economic Co-operation and Development (OECD). Accordingly, ICCVAM is working to develop integrated decision strategies based on the AOP using in vitro, in chemico and in silico information. Data were compiled for 120 substances tested in the murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens assay. Data for six physicochemical properties, which may affect skin penetration, were also collected, and skin sensitization read-across predictions were performed using OECD QSAR Toolbox. All data were combined into a variety of potential integrated decision strategies to predict LLNA outcomes using a training set of 94 substances and an external test set of 26 substances. Fifty-four models were built using multiple combinations of machine learning approaches and predictor variables. The seven models with the highest accuracy (89-96% for the test set and 96-99% for the training set) for predicting LLNA outcomes used a support vector machine (SVM) approach with different combinations of predictor variables. The performance statistics of the SVM models were higher than any of the non-animal tests alone and higher than simple test battery approaches using these methods. These data suggest that computational approaches are promising tools to effectively integrate data sources to identify potential skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

A prospective, placebo-controlled, randomized trial of intravenous streptokinase and angioplasty versus lone angioplasty therapy of acute myocardial infarction

BACKGROUND

The value of routine administration of intravenous thrombolytic agents during percutaneous transluminal coronary angioplasty (PTCA) therapy of acute myocardial infarction (MI) has not been determined. Therefore, we prospectively randomized 122 patients with evolving MI to PTCA therapy with or without adjunctive intravenous streptokinase therapy.

METHODS AND RESULTS

Patients with ECG ST segment elevation who presented within 4 hours of symptom onset, had no contraindication to thrombolytic therapy, and were not in cardiogenic shock were enrolled. They were treated immediately with intravenous heparin (10,000 units) and oral aspirin (325 mg) and randomized to treatment with placebo or streptokinase (1.5 M units) administered intravenously over 30 minutes. Patients then were taken immediately to the catheterization laboratory, and those with suitable coronary anatomy underwent immediate PTCA. Subsequent clinical course, serial radionuclide ventriculography, and 6-month repeat angiography were analyzed. A total of 106 patients were treated with PTCA. Use of PTCA was similar for placebo (92%) and streptokinase (83%) groups. Angioplasty was successful in 95% of patients, with no difference in placebo (93%) and streptokinase (98%) groups. Serial radionuclide ventriculography demonstrated no difference in 24-hour (52 +/- 12% versus 50 +/- 12%) or 6-week (51 +/- 12% versus 51 +/- 13%) ejection fraction values for placebo and streptokinase groups, respectively. Contrast ventriculography demonstrated improvement in immediate (54 +/- 12%) versus 6-month (60 +/- 15%, p < 0.05) values for the overall group. No differences in 6-month values were present (58 +/- 15% versus 62 +/- 15%, p = NS) for placebo and streptokinase groups, respectively. Coronary angiography was performed in 75% of the 90 patients eligible for restudy. Arterial patency was 87% at 6 months, and coronary restenosis was present in 38% of patients. No differences in chronic patency or restenosis were detected for the two treatment groups. Although adjunctive intravenous streptokinase therapy did not improve outcome, it did complicate the hospital course. Hospitalization was longer (9.3 +/- 5.0 versus 7.7 +/- 4.4 days, p = 0.046) and more costly ($25,191 +/- 15,368 versus $19,643 +/- 7,250, p < 0.02). Transfusion rate was higher (39% versus 8%, p = 0.0001) and need for emergency coronary bypass surgery was greater (10.3% versus 1.6%, p = 0.03) for the streptokinase-treated patients.

CONCLUSIONS

Adjunctive intravenous streptokinase therapy does not enhance early preservation of ventricular function, improve arterial patency rates, or lower restenosis rates after PTCA therapy of acute MI. Hospital course is longer, more expensive, and more complicated. For these reasons, PTCA therapy of acute MI should not be routinely performed with adjunctive intravenous streptokinase therapy.