Comparison of threshold of toxicological concern (TTC) values to oral reference dose (RfD) values.

Thousands of chemicals have limited, or no hazard data readily available to characterize human risk. The threshold of toxicological concern (TTC) constitutes a science-based tool for screening level risk-based prioritization of chemicals with low exposure. Herein we compare TTC values to more rigorously derived reference dose (RfD) values for 288 chemicals in the U.S. Environmental Protection Agency's (US EPA) Integrated Risk Information System (IRIS) database. Using the Cramer decision tree and the Kroes tiered decision tree approaches to determine TTC values, the TCC for the majority of these chemicals were determined to be lower than their corresponding RfD values. The ratio of log10(RfD/TCC) was used to measure the differences between these values and the mean ratio for the substances evaluated was ~0.74 and ~0.79 for the Cramer and Kroes approach, respectively, when considering the Cramer Classes only. These data indicate that the RfD values for Cramer Class III compounds were, on average, ~6-fold higher than their TTC value. These analyses indicate that provisional oral toxicity values might be estimated from TTCs in data-poor or emergency situations; moreover, RfD values that are well below TTC values (e.g., 2 standard deviations below the log10(Ratio)) might be overly conservative and targets for re-evaluation.

Profiling 58 compounds including cosmetic-relevant chemicals using ToxRefDB and ToxCast.

Safety assessment for cosmetic-relevant chemicals (CRCs) in the European Union has been reshaped by restrictions on animal testing, and new approach methodologies (NAMs) for predicting toxicity are critical to ensure new cosmetic product safety. To demonstrate NAMs for safety assessment, we surveyed in vitro bioactivity and in vivo systemic toxicity data in the US Environmental Protection Agency's (EPA's) Toxicity Forecaster (ToxCast) and Toxicity Reference databases (ToxRefDB), respectively, for 58 chemicals identified as CRCs, including cosmetic ingredients as well as trace contaminants. CRCs were diverse in use types as suggested by broad chemical use categories. In terms of both target organ effects and study type, the median of the lowest effect level (LEL) doses in ToxRefDB for CRCs tended to be slightly higher than the median for the remaining 928 chemicals with study data in ToxRefDB, though the ranges of LELs were similar. For 17 of the 58 CRCs, high-throughput toxicokinetic data were used to calculate administered equivalent doses (AEDs) in mg/kg/day units for the in vitro bioactivity observed, and these AEDs served as conservative estimators of the systemic LELs observed in vivo. This work suggests that NAMs for bioactivity may inform a conservative point-of-departure estimate for diverse CRCs.

Using the concordance of in vitro and in vivo data to evaluate extrapolation assumptions.

Linking in vitro bioactivity and in vivo toxicity on a dose basis enables the use of high-throughput in vitro assays as an alternative to traditional animal studies. In this study, we evaluated assumptions in the use of a high-throughput, physiologically based toxicokinetic (PBTK) model to relate in vitro bioactivity and rat in vivo toxicity data. The fraction unbound in plasma (fup) and intrinsic hepatic clearance (Clint) were measured for rats (for 67 and 77 chemicals, respectively), combined with fup and Clint literature data for 97 chemicals, and incorporated in the PBTK model. Of these chemicals, 84 had corresponding in vitro ToxCast bioactivity data and in vivo toxicity data. For each possible comparison of in vitro and in vivo endpoint, the concordance between the in vivo and in vitro data was evaluated by a regression analysis. For a base set of assumptions, the PBTK results were more frequently better associated than either the results from a "random" model parameterization or direct comparison of the "untransformed" values of AC50 and dose (performed best in 51%, 28%, and 21% of cases, respectively). We also investigated several assumptions in the application of PBTK for IVIVE, including clearance and internal dose selection. One of the better assumptions sets-restrictive clearance and comparing free in vivo venous plasma concentration with free in vitro concentration-outperformed the random and untransformed results in 71% of the in vitro-in vivo endpoint comparisons. These results demonstrate that applying PBTK improves our ability to observe the association between in vitro bioactivity and in vivo toxicity data in general. This suggests that potency values from in vitro screening should be transformed using in vitro-in vivo extrapolation (IVIVE) to build potentially better machine learning and other statistical models for predicting in vivo toxicity in humans.