RESUMO
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 (r 2 = 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.
RESUMO
Although formaldehyde is a normal constituent of tissues, lifetime inhalation exposures at 6 h/day, 5 days/week at concentrations ≥6 ppm caused a nonlinear increase in nasal tumors in rats with incidence reaching close to 50% at 15 ppm. Studies with heavy isotope labeled [13CD2]-formaldehyde permit quantification of both the mass-labeled exogenous and endogenous DNA-formaldehyde reaction products. An existing pharmacokinetic model developed initially to describe 14C-DNA-protein crosslinks (DPX) provided a template for describing the time course of mass-labeled adducts. Published datasets included both DPX and N2-HO13CD2-dG adducts measured after a single 6-h exposure to 0.7, 2, 6, 9, 10, or 15 ppm formaldehyde, after multi-day exposures to 2 ppm for 6 h/day, 7 days/week with interim sacrifices up to 28 days, and after 28-day exposures for 6 h/day, 7 days/week to 0.3, 0.03, or 0.001 ppm. The existing kinetic model overpredicted endogenous adducts in the nasal epithelium after 1-day [13CD2]-formaldehyde exposure, requiring adjustment of parameters for rates of tissue metabolism and background formaldehyde. After refining tissue formaldehyde parameters, we fit the model to both forms of adducts by varying key parameters and optimizing against all 3 studies. Fitting to all these studies required 2 nonlinear pathways-one for high-exposure saturation of clearance in the nasal epithelial tissues and another for extracellular clearance that restricts uptake into the epithelial tissue for inhaled concentrations below 0.7 ppm. This refined pharmacokinetic model for endogenous and exogenous formaldehyde acetal adducts can assist in updating biologically based dose-response models for formaldehyde carcinogenicity.