Predictive Model of Rat Reproductive Toxicity from ToxCast High Throughput Screening
ABSTRACT The U.S. Environmental Protection Agency's ToxCast research program uses high throughput screening (HTS) for profiling bioactivity and predicting the toxicity of large numbers of chemicals. ToxCast Phase I tested 309 well-characterized chemicals in more than 500 assays for a wide range of molecular targets and cellular responses. Of the 309 environmental chemicals in Phase I, 256 were linked to high-quality rat multigeneration reproductive toxicity studies in the relational Toxicity Reference Database. Reproductive toxicants were defined here as having achieved a reproductive lowest-observed-adverse-effect level of less than 500 mg kg(-1) day(-1). Eight-six chemicals were identified as reproductive toxicants in the rat, and 68 of those had sufficient in vitro bioactivity to model. Each assay was assessed for univariate association with the identified reproductive toxicants. Significantly associated assays were linked to gene sets and used for the subsequent predictive modeling. Using linear discriminant analysis and fivefold cross-validation, a robust and stable predictive model was produced capable of identifying rodent reproductive toxicants with 77% ± 2% and 74% ± 5% (mean ± SEM) training and test cross-validation balanced accuracies, respectively. With a 21-chemical external validation set, the model was 76% accurate, further indicating the model's potential for prioritizing the many thousands of environmental chemicals with little to no hazard information. The biological features of the model include steroidal and nonsteroidal nuclear receptors, cytochrome P450 enzyme inhibition, G protein-coupled receptors, and cell signaling pathway readouts-mechanistic information suggesting additional targeted, integrated testing strategies and potential applications of in vitro HTS to risk assessment.
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ABSTRACT: A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling.Archive für Toxikologie 01/2015; 89(2). DOI:10.1007/s00204-015-1464-2
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ABSTRACT: The two-generation study (OECD TG 416) is the standard requirement within REACH to test reproductive toxicity effects of chemicals with production volumes >100 tonnes. This test is criticized in terms of scientific relevance and animal welfare. The Extended One Generation Reproductive Toxicity Study (EOGRTS), incorporated into the OECD test guidelines in 2011 (OECD TG 443) has the potential to replace TG 416, while using only one generation of rats and being more informative. However, its regulatory acceptance proved challenging. This article reconstructs the process of regulatory acceptance and use of the EOGRTS and describes drivers and barriers influencing the process. The findings derive from literature research and expert interviews. A distinction is made between three sub-stages; The stage of Formal Incorporation of the EOGRTS into OECD test guidelines was stimulated by retrospective analyses on the value of the second generation (F2), strong EOGRTS advocates, animal welfare concern and changing US and EU chemicals legislation; the stage of Actual Regulatory Acceptance within REACH was challenged by legal factors and ongoing scientific disputes, while the stage of Use by Industry is influenced by uncertainty of registrants about regulatory acceptance, high costs, the risk of false positives and the manageability of the EOGRTS.Regulatory Toxicology and Pharmacology 10/2014; 71(1). DOI:10.1016/j.yrtph.2014.10.012
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ABSTRACT: High throughput (HTS) and high content (HCS) screening methods show great promise in changing how hazard and risk assessments are undertaken, but scientific confidence in such methods and associated prediction models needs to be established prior to regulatory use. Using a case study of HTS-derived models for predicting in vivo androgen (A), estrogen (E), thyroid (T) and steroidogenesis (S) endpoints in endocrine screening assays, we compare classification (fitting) models to cross validation (prediction) models. The more robust cross validation models (based on a set of endocrine ToxCastTM assays and guideline in vivo endocrine screening studies) have balanced accuracies from 79% to 85% for A and E, but only 23% to 50% for S and T. Thus, for E and A, HTS results appear promising for initial use in setting priorities for endocrine screening. However, continued research is needed to expand the domain of applicability and to develop more robust HTS/HCS-based prediction models prior to their use in other regulatory applications. Based on the lessons learned, we propose a framework for documenting scientific confidence in HTS assays and the prediction models derived therefrom. The documentation, transparency and the scientific rigor involved in addressing the elements in the proposed Scientific Confidence Framework could aid in discussions and decisions about the prediction accuracy needed for different applications.Regulatory Toxicology and Pharmacology 01/2014;