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

Abstract

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.

High-throughput transcriptomics and benchmark concentration modeling for potency ranking of per- and polyfluoroalkyl substances (PFAS) in exposed human liver cell spheroids

“…2) was used as the transcriptomic PODs for each PFAS depicted in Figure 5. This is consistent with previous approaches to deriving a molecular-based POD (Friedman et al, 2019). Comparing 1-and 10-day exposures, a general trend of increasing potency was observed with decreased gene BMCs at 10 days, primarily with PFSAs.…”

“…The gene BMC, upper (BMCU), and lower (BMCL) bound values were identified from exported best models from BMDExpress. A similar methodology (5th percentile) has been used in previous work to represent a lower bound estimate within the ToxCast database typically to derive values for the bioactivity exposure ratio (BER) (Friedman et al, 2019). Each gene was checked to ensure that none of the BMC values included were fit with a "flagged" Hill model for which no other best-fit model with a p-value < 0.05 could be obtained.…”

“…Although AEDs can be determined for the most prominent PFAS (e.g., PFOS and PFOA) toxicokinetic data are not available for most PFAS. However, other approaches such as benchmark concentration (BMC) modeling (Crump, 1984;Slob et al, 2005) may be used to identify thresholds of molecular change (Paul Friedman et al, 2020). In this approach, a BMC, defined as a change in response from a predetermined threshold (e.g., 1 standard deviation) relative to the background incidence, was determined from continuous concentration-response data Combined with high-throughput transcriptomics, BMC models can be advantageous in providing quantitative toxicogenomic information for various risk assessment applications when adequate toxicokinetic data is not available.…”

High-throughput transcriptomic analysis of human primary hepatocyte spheroids exposed to per- and polyfluoroalkyl substances (PFAS) as a platform for relative potency characterization

“…The BER is the ratio of the administered equivalent dose (AED) for the NAM POD to population exposure for a given chemical. A large BER value is an indication of lower risk, whereas a lower value indicates increased risk to human health (Wetmore et al, 2015b;Paul Friedman et al, 2020). However, the use of transcriptomics in risk assessment is a relatively new concept and there is lack of consistency in how to derive the POD for a given chemical (e.g., selected genes, gene-sets, or pathways), wherein the approach used to determine the AED influences the scale of the BER estimate.…”

“…This was taken into account by comparing two conservative approaches. For Approach 1, a POD that is comparable to previous approaches used for ToxCast data was applied: the 5 th percentile gene BMC (Paul Friedman et al, 2020). Approach 2 was based on data demonstrating a strong correlation between the dose at which apical effects in vivo occur and the lowest (most sensitive) in vivo pathway BMC (Thomas et al, 2013).…”