Reliability of the TTC approach: Learning from inclusion of pesticide active substances in the supporting database

Application of the threshold of toxicological concern (TTC) in the evaluation of drinking water contact chemicals

The Threshold of Toxicological Concern (TTC) is an approach for assessing the safety of chemicals with low levels of exposure for which limited toxicology data are available. The original TTC criteria were derived for oral exposures from a distributional analysis of a dataset of 613 chemicals that identified 5th percentile no observed effect level (NOEL) values grouped within three tiers of compounds having specific structural functional groups and/or toxic potencies known as Cramer I, II and III classifications. Subsequent assessments of the TTC approach have established current thresholds to be scientifically robust. While the TTC has gained acknowledgment and acceptance by many regulatory agencies and organizations, use of the TTC approach in evaluating drinking water chemicals has been limited. To apply the TTC concept to drinking water chemicals, an exposure-based approach that incorporates the current weight of evidence for the target chemical is presented. Such an approach provides a comparative point of departure to the 5th percentile TTC NOEL using existing data, while conserving the allocation of toxicological resources for quantitative risk assessment to chemicals with greater exposure or toxicity. This approach will be considered for incorporation into NSF/ANSI/CAN 600, a health effects standard used in the safety evaluation of chemicals present in drinking water from drinking water contact additives and materials certified to NSF/ANSI/CAN 60 and 61, respectively.

Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable chemical substances from medical devices

The Threshold of Toxicological Concern (TTC) is a pragmatic approach used to establish safe thresholds below which there can be no appreciable risk to human health. Here, a large inventory of ~45,000 substances (referred to as the LRI dataset) was profiled through the Kroes TTC decision module within Toxtree v3.1 to assign substances into their respective TTC categories. Four thousand and two substances were found to be not applicable for the TTC approach. However, closer examination of these substances uncovered several implementation issues: substances represented in their salt forms were automatically assigned as not appropriate for TTC when many of these contained essential metals as counter ions which would render them TTC applicable. High Potency Carcinogens and dioxin-like substances were not fully captured based on the rules currently implemented in the software. Phosphorus containing substances were considered exclusions when many of them would be appropriate for TTC. Refinements were proposed to address the limitations in the current software implementation. A second component of the study explored a set of substances representative of those released from medical devices and compared them to the LRI dataset as well as other toxicity datasets to investigate their structural similarity. A third component of the study sought to extend the exclusion rules to address application to substances released from medical devices that lack toxicity data. The refined rules were then applied to this dataset and the TTC assignments were compared. This case study demonstrated the importance of evaluating the software implementation of an established TTC workflow, identified certain limitations and explored potential refinements when applying these concepts to medical devices.

Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods

Current computational technologies hold promise for prioritizing the testing of the thousands of chemicals in commerce. Here, a case study is presented demonstrating comparative risk-prioritization approaches based on the ratio of surrogate hazard and exposure data, called margins of exposure (MoEs). Exposures were estimated using a U.S. EPA’s ExpoCast predictive model (SEEM3) results and estimates of bioactivity were predicted using: 1) Oral equivalent doses (OEDs) derived from U.S. EPA’s ToxCast high-throughput screening program, together with in vitro to in vivo extrapolation and 2) thresholds of toxicological concern (TTCs) determined using a structure-based decision-tree using the Toxtree open source software. To ground-truth these computational approaches, we compared the MoEs based on predicted noncancer TTC and OED values to those derived using the traditional method of deriving points of departure from no-observed adverse effect levels (NOAELs) from in vivo oral exposures in rodents. TTC-based MoEs were lower than NOAEL-based MoEs for 520 out of 522 (99.6%) compounds in this smaller overlapping dataset, but were relatively well correlated with the same (r² = 0.59). TTC-based MoEs were also lower than OED-based MoEs for 590 (83.2%) of the 709 evaluated chemicals, indicating that TTCs may serve as a conservative surrogate in the absence of chemical-specific experimental data. The TTC-based MoE prioritization process was then applied to over 45,000 curated environmental chemical structures as a proof-of-concept for high-throughput prioritization using TTC-based MoEs. This study demonstrates the utility of exploiting existing computational methods at the pre-assessment phase of a tiered risk-based approach to quickly, and conservatively, prioritize thousands of untested chemicals for further study.

In Silico Models for Repeated-Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs

Many regulatory contexts require the evaluation of repeated-dose toxicity (RDT) studies conducted in laboratory animals. The main outcome of RDT studies is the identification of the no observed adverse effect level (NOAEL) and the lowest observed adverse effect level (LOAEL) that are normally used as point of departure for the establishment of health-based guidance values. Since in vivo RDT studies are expensive and time-consuming, in silico approaches could offer a valuable alternative. However, NOAEL and LOAEL modeling suffer some limitations since they do not refer to a single end point but to several different effects, and the doses used in experimental studies strongly influence the results. Few attempts to model NOAEL and LOAEL have been reported. The available database and models for the prediction of NOAEL and LOAEL are reviewed here.

Enantioselective Bioaccumulation of the Chiral Insecticide Indoxacarb in Zebrafish (Danio rerio)

Indoxacarb is a typical chiral insecticide widely used in agricultural pest control. In the present study, zebrafish was used as a model animal to explore the enantioselective bioaccumulation behavior of indoxacarb to nontarget species in aquatic environments. Zebrafish were exposed to 0.025 and 0.1 mg/L rac-indoxacarb solution for 12 d under the semistatic method, and the bioconcentration factor (BCF) and enantiomeric fraction of zebrafish were investigated. The results showed that the (-)-R-indoxacarb preferentially accumulated in zebrafish. The BCF values at 0.025 mg/L exposure levels were 1079.8 and 83.4 L/kg for (-)-R-indoxacarb and (+)-S-indoxacarb after 12 d, respectively. The BCF values at 0.1 mg/L exposure levels were 1752.1 and 137.0 L/kg for (-)-R-indoxacarb and (+)-S-indoxacarb after 10 d, respectively. The half-life values of (-)-R-indoxacarb and (+)-S-indoxacarb were 3.47 and 2.05 d for 0.025 mg/L concentration exposure and 4.95 and 2.66 d for 0.1 mg/L concentration exposure, respectively. The enantiomeric fraction values were in the range of 0.48 to 0.55 and 0.89 to 1.00 for water and zebrafish samples, respectively. Studies on the enantioselective bioaccumulation behavior of indoxacarb will provide data for assessing the environmental fate and potential toxic effects of indoxacarb on aquatic organisms. Environ Toxicol Chem 2021;40:1007-1016. © 2020 SETAC.

Do Similar Structures Have Similar No Observed Adverse Effect Level (NOAEL) Values? Exploring Chemoinformatics Approaches for Estimating NOAEL Bounds and Uncertainties

Determination of the no observed adverse effect level (NOAEL) of a substance is an important step in safety and regulatory assessments. Application of conventional in silico strategies, for example, quantitative structure-activity relationship (QSAR) models, to predict NOAEL values is inherently problematic. Whereas QSAR models for well-defined toxicity endpoints such as Ames mutagenicity or skin sensitization can be developed from mechanistic knowledge of molecular initiating events and adverse outcome pathways, QSAR is not appropriate for predicting a NOAEL value, a concentration at which "no effect" is observed. This paper presents a chemoinformatics approach and explores how it can be further refined through the incorporation of toxicity endpoint-specific information to estimate confidence bounds for the NOAEL of a target substance, given experimentally determined NOAEL values for one or more suitable analogues. With a sufficiently large NOAEL database, we analyze how a difference in NOAEL values for pairs of structures depends on their pairwise similarity, where similarity takes both structural features and physicochemical properties into account. The width of the estimate NOAEL confidence interval is proportional to the uncertainty. Using the new threshold of toxicological concern (TTC) database enriched with antimicrobials, examples are presented to illustrate how uncertainty decreases with increasing analogue quality and also how NOAEL bounds estimation can be significantly improved by filtering the full database to include only substances that are in structure categories relevant to the target and analogue.

Alternative toxicological methods for establishing residue definitions applied for dietary risk assessment of pesticides in the European Union

Consumers are constantly exposed to trace levels of residues present in food commodities, arising from the use of pesticides. For this reason, assessing the risk caused by pesticide residues present in food requires not only identification and toxicological properties assessment of the active substance, but also of its metabolites, isomers, and degradates. This requires the use of many laboratory animals. On the other hand, currently there is an emphasis on minimizing the use of animals in toxicological research. This review article presents current activities of the European Food Safety Authority (EFSA) and the European Commission's Joint Research Centre (JRC) aiming to replace at least a part of toxicological tests on substances of unknown toxicity with the alternative methods. Quantitative Structure-Activity Relationship (QSAR) and Threshold of Toxicological Concern (TTC) can be used for this purpose in procedure of establishing residue definitions applied for dietary risk assessment.

Guidance on the use of the Threshold of Toxicological Concern approach in food safety assessment

The Scientific Committee confirms that the Threshold of Toxicological Concern (TTC) is a pragmatic screening and prioritisation tool for use in food safety assessment. This Guidance provides clear step-by-step instructions for use of the TTC approach. The inclusion and exclusion criteria are defined and the use of the TTC decision tree is explained. The approach can be used when the chemical structure of the substance is known, there are limited chemical-specific toxicity data and the exposure can be estimated. The TTC approach should not be used for substances for which EU food/feed legislation requires the submission of toxicity data or when sufficient data are available for a risk assessment or if the substance under consideration falls into one of the exclusion categories. For substances that have the potential to be DNA-reactive mutagens and/or carcinogens based on the weight of evidence, the relevant TTC value is 0.0025 μg/kg body weight (bw) per day. For organophosphates or carbamates, the relevant TTC value is 0.3 μg/kg bw per day. All other substances are grouped according to the Cramer classification. The TTC values for Cramer Classes I, II and III are 30 μg/kg bw per day, 9 μg/kg bw per day and 1.5 μg/kg bw per day, respectively. For substances with exposures below the TTC values, the probability that they would cause adverse health effects is low. If the estimated exposure to a substance is higher than the relevant TTC value, a non-TTC approach is required to reach a conclusion on potential adverse health effects.

Toxicological risk assessment and prioritization of drinking water relevant contaminants of emerging concern

Toxicological risk assessment of contaminants of emerging concern (CEC) in (sources of) drinking water is required to identify potential health risks and prioritize chemicals for abatement or monitoring. In such assessments, concentrations of chemicals in drinking water or sources are compared to either (i) health-based (statutory) drinking water guideline values, (ii) provisional guideline values based on recent toxicity data in absence of drinking water guidelines, or (iii) generic drinking water target values in absence of toxicity data. Here, we performed a toxicological risk assessment for 163 CEC that were selected as relevant for drinking water. This relevance was based on their presence in drinking water and/or groundwater and surface water sources in downstream parts of the Rhine and Meuse, in combination with concentration levels and physicochemical properties. Statutory and provisional drinking water guideline values could be derived from publically available toxicological information for 142 of the CEC. Based on measured concentrations it was concluded that the majority of substances do not occur in concentrations which individually pose an appreciable human health risk. A health concern could however not be excluded for vinylchloride, trichloroethene, bromodichloromethane, aniline, phenol, 2-chlorobenzenamine, mevinphos, 1,4-dioxane, and nitrolotriacetic acid. For part of the selected substances, toxicological risk assessment for drinking water could not be performed since either toxicity data (hazard) or drinking water concentrations (exposure) were lacking. In absence of toxicity data, the Threshold of Toxicological Concern (TTC) approach can be applied for screening level risk assessment. The toxicological information on the selected substances was used to evaluate whether drinking water target values based on existing TTC levels are sufficiently protective for drinking water relevant CEC. Generic drinking water target levels of 37 μg/L for Cramer class I substances and 4 μg/L for Cramer class III substances in drinking water were derived based on these CEC. These levels are in line with previously reported generic drinking water target levels based on original TTC values and are shown to be protective for health effects of the majority of contaminants of emerging concern evaluated in the present study. Since the human health impact of many chemicals appearing in the water cycle has been studied insufficiently, generic drinking water target levels are useful for early warning and prioritization of CEC with unknown toxicity in drinking water and its sources for future monitoring.