Utility of In Vitro Bioactivity as a Lower Bound Estimate of In Vivo Adverse Effect Levels and in Risk-Based Prioritization.

Use of high-throughput, in vitro bioactivity data in setting a point-of-departure (POD) has the potential to accelerate the pace of human health safety evaluation by informing screening-level assessments. The primary objective of this work was to compare PODs based on high-throughput predictions of bioactivity, exposure predictions, and traditional hazard information for 448 chemicals. PODs derived from new approach methodologies (NAMs) were obtained for this comparison using the 50th (PODNAM, 50) and the 95th (PODNAM, 95) percentile credible interval estimates for the steady-state plasma concentration used in in vitro to in vivo extrapolation of administered equivalent doses. Of the 448 substances, 89% had a PODNAM, 95 that was less than the traditional POD (PODtraditional) value. For the 48 substances for which PODtraditional < PODNAM, 95, the PODNAM and PODtraditional were typically within a factor of 10 of each other, and there was an enrichment of chemical structural features associated with organophosphate and carbamate insecticides. When PODtraditional < PODNAM, 95, it did not appear to result from an enrichment of PODtraditional based on a particular study type (eg, developmental, reproductive, and chronic studies). Bioactivity:exposure ratios, useful for identification of substances with potential priority, demonstrated that high-throughput exposure predictions were greater than the PODNAM, 95 for 11 substances. When compared with threshold of toxicological concern (TTC) values, the PODNAM, 95 was greater than the corresponding TTC value 90% of the time. This work demonstrates the feasibility, and continuing challenges, of using in vitro bioactivity as a protective estimate of POD in screening-level assessments via a case study.

Finding synergies for the 3Rs - Repeated Dose Toxicity testing: Report from an EPAA Partners' Forum.

The European Partnership for Alternative Approaches to Animal Testing (EPAA) convened a Partners' Forum on repeated dose toxicity (RDT) testing to identify synergies between industrial sectors and stakeholders along with opportunities to progress these in existing research frameworks. Although RTD testing is not performed across all industrial sectors, the OECD accepted tests can provide a rich source of information and play a pivotal role for safety decisions relating to the use of chemicals. Currently there are no validated alternatives to repeated dose testing and a direct one-to-one replacement is not appropriate. However, there are many projects and initiatives at the international level which aim to implement various aspects of replacement, reduction and refinement (the 3Rs) in RDT testing. Improved definition of use, through better problem formulation, aligned to harmonisation of regulations is a key area, as is the more rapid implementation of alternatives into the legislative framework. Existing test designs can be optimised to reduce animal use and increase information content. Greater use of exposure-led decisions and improvements in dose selection will be beneficial. In addition, EPAA facilitates sharing of case studies demonstrating the use of Next Generation Risk Assessment applying various New Approach Methodologies to assess RDT.

The impact on classifications for carcinogenicity, mutagenicity, reproductive and specific target organ toxicity after repeated exposure in the first ten years of the REACH regulation.

The present study primarily aims at informing regulators and policy makers in Europe and examines the evolution of self-classifications and study availability for the endpoints of carcinogenicity, mutagenicity, reproductive toxicity (CMR) and specific target organ toxicity after repeated exposure (STOT RE) for the first ten years of the REACH legislation. Our knowledge on chemical safety keeps increasing due to the registration obligations under REACH, in combination with proactive actions by registrants and regulatory actions by Authorities, which jointly lead to new testing and critical reassessment of existing studies. The improvements become evident by the constant increase in the number of substances that are self-classified by the registrants for human health endpoints. Moreover, there is a slow but steady increase in the number of substances for which there is at least one experimental study available for the human health endpoints in scope of this analysis. However, the increase is slow given the generally limited data availability at the beginning of REACH. Manual examination of about 350 classified substances reveals that the impact of newly generated data and regulatory action by Authorities is greater for reproductive toxicity than for carcinogenicity or mutagenicity, reflecting the strengthening of the information requirements for reproductive toxicity with the introduction of REACH. The results of the study should inform regulators and policy makers at EU and national level in the discussion on potential changes to information requirements or testing strategies under REACH.

(Q)SARs as Adaptations to REACH Information Requirements.

REACH is a regulation of the European Union adopted to improve the safe use of chemicals with regard to human health and the environment. The safe use of chemicals can be achieved only if the hazard and the exposure of the substances are well characterized. Testing on animals has been traditionally the main tool for hazard assessment. For ethical and economic reasons, alternative ways of testing that do not use laboratory animals have been developed by different parties (regulatory agencies, researchers, industry) over the recent decades, and their proper use in hazard assessment is encouraged under REACH. In this chapter, we describe how (Q)SAR models and predictions are included into REACH and their adequate use promoted by the European Chemicals Agency (ECHA).

Accelerating the Pace of Chemical Risk Assessment.

Changes in chemical regulations worldwide have increased the demand for new data on chemical safety. New approach methodologies (NAMs) are defined broadly here as including in silico approaches and in chemico and in vitro assays, as well as the inclusion of information from the exposure of chemicals in the context of hazard [European Chemicals Agency, " New Approach Methodologies in Regulatory Science ", 2016]. NAMs for toxicity testing, including alternatives to animal testing approaches, have shown promise to provide a large amount of data to fill information gaps in both hazard and exposure. In order to increase experience with the new data and to advance the applications of NAM data to evaluate the safety of data-poor chemicals, demonstration case studies have to be developed to build confidence in their usability. Case studies can be used to explore the domains of applicability of the NAM data and identify areas that would benefit from further research, development, and application. To ensure that this science evolves with direct input from and engagement by risk managers and regulatory decision makers, a workshop was convened among senior leaders from international regulatory agencies to identify common barriers for using NAMs and to propose next steps to address them. Central to the workshop were a series of collaborative case studies designed to explore areas where the benefits of NAM data could be demonstrated. These included use of in vitro bioassays data in combination with exposure estimates to derive a quantitative assessment of risk, use of NAMs for updating chemical categorizations, and use of NAMs to increase understanding of exposure and human health toxicity of various chemicals. The case study approach proved effective in building collaborations and engagement with regulatory decision makers and to promote the importance of data and knowledge sharing among international regulatory agencies. The case studies will be continued to explore new ways of describing hazard (i.e., pathway perturbations as a measure of adversity) and new ways of describing risk (i.e., using NAMs to identify protective levels without necessarily being predictive of a specific hazard). Importantly, the case studies also highlighted the need for increased training and communication across the various communities including the risk assessors, regulators, stakeholders (e.g., industry, non-governmental organizations), and the general public. The development and application of NAMs will play an increasing role in filling important data gaps on the safety of chemicals, but confidence in NAMs will only come with learning by doing and sharing in the experience.

UVCB substances: methodology for structural description and application to fate and hazard assessment.

Substances of unknown or variable composition, complex reaction products, or biological materials (UVCBs) have been conventionally described in generic terms. Commonly used substance identifiers are generic names of chemical classes, generic structural formulas, reaction steps, physical-chemical properties, or spectral data. Lack of well-defined structural information has significantly restricted in silico fate and hazard assessment of UVCB substances. A methodology for the structural description of UVCB substances has been developed that allows use of known identifiers for coding, generation, and selection of representative constituents. The developed formats, Generic Simplified Molecular-Input Line-Entry System (G SMILES) and Generic Graph (G Graph), address the need to code, generate, and select representative UVCB constituents; G SMILES is a SMILES-based single line notation coding fixed and variable structural features of UVCBs, whereas G Graph is based on a workflow paradigm that allows generation of constituents coded in G SMILES and end point-specific or nonspecific selection of representative constituents. Structural description of UVCB substances as afforded by the developed methodology is essential for in silico fate and hazard assessment. Data gap filling approaches such as read-across, trend analysis, or quantitative structure-activity relationship modeling can be applied to the generated constituents, and the results can be used to assess the substance as a whole. The methodology also advances the application of category-based data gap filling approaches to UVCB substances.