Derivation of internal dose-based thresholds of toxicological concern for occupational inhalation exposure to systemically acting organic chemicals.

This study aimed at deriving occupational thresholds of toxicological concern for inhalation exposure to systemically-acting organic chemicals using predicted internal doses. The latter were also used to evaluate the quantitative relationship between occupational exposure limit and internal dose. Three internal dose measures were identified for investigation: (i) the daily area under the venous blood concentration vs. time curve, (ii) the daily rate of the amount of parent chemical metabolized, and (iii) the maximum venous blood concentration at the end of an 8-hr work shift. A dataset of 276 organic chemicals with 8-hr threshold limit values-time-weighted average was compiled along with their molecular structure and Cramer classes (Class I: low toxicity, Class II: intermediate toxicity, Class III: suggestive of significant toxicity). Using a human physiologically-based pharmacokinetic model, the three identified dose metrics were predicted for an 8-hr occupational inhalation exposure to the threshold limit value for each chemical. Distributional analyses of the predicted dose metrics were performed to identify the percentile values corresponding to the occupational thresholds of toxicological concern. Also, simple linear regression analyses were performed to evaluate the relationship between the 8-hr threshold limit value and each of the predicted dose metrics, respectively. No threshold of toxicological concern could be derived for class II due to few chemicals. Based on the daily rate of the amount of parent chemical metabolized, the proposed internal dose-based occupational thresholds of toxicological concern were 5.61 × 10-2 and 9 × 10-4 mmol/d at the 10th percentile level for classes I and III, respectively, while they were 4.55 × 10-1 and 8.5 × 10-3 mmol/d at the 25th percentile level. Even though high and significant correlations were observed between the 8-hr threshold limit values and the predicted dose metrics, the one with the rate of the amount of chemical metabolized was remarkable regardless of the Cramer class (r2 = 0.81; n = 276). The proposed internal dose-based occupational thresholds of toxicological concern are potentially useful for screening-level assessments as well as prioritization within an integrated occupational risk assessment framework.

A framework for application of quantitative property-property relationships (QPPRs) in physiologically based pharmacokinetic (PBPK) models for high-throughput prediction of internal dose of inhaled organic chemicals.

New generation of toxicological tests and assessment strategies require validated toxicokinetic data or models that are lacking for most chemicals. This study aimed at developing a quantitative property-property relationship (QPPR)-based human physiologically based pharmacokinetic (PBPK) modeling framework for high-throughput predictions of inhalation toxicokinetics of organic chemicals. A PBPK model was parameterized with QPPR-derived values for hepatic clearance (CLh) and partition coefficients (P) [blood:air (Pba) and tissue:air (Pta) and tissue:blood (Ptb)]. The model was initially applied to an evaluation dataset of 40 organic chemicals in the applicability domain, and then to an expanded dataset of 249 organic chemicals from diverse chemical classes. 'Batch' analyses were performed for rapid assessments of hundreds of chemicals. The simulations of inhalation toxicokinetics following an 8-h exposure to 1 ppm of each chemical were successful. The mean ratios of their predicted-to-experimental values were within a factor of 1.36-2.36 for Ptb and 1.18 for CLh, for 80% of the chemicals in the evaluation dataset. The predicted 24-h area under the venous blood concentration-time curve (AUC24) values were within the predicted envelopes obtained while using experimental values of Pba and considering either no or maximal hepatic extraction. The reliability analysis (based on combined sensitivity and uncertainty analyses) indicated that AUC24 predictions for 55% of the expanded dataset were moderately to highly reliable, with 46% exhibiting highly reliable values. Overall, the modeling framework suggests that molecular structure and chemical properties can together be effectively used to obtain first-cut estimates of the toxicokinetics of data-poor organic chemicals for screening and prioritization purposes.

Derivation of Occupational Thresholds of Toxicological Concern for Systemically Acting Noncarcinogenic Organic Chemicals.

Many substances in workplace do not have occupational exposure limits. The threshold of toxicological concern (TTC) principle is part of the hierarchy of approaches useful in occupational health risk assessment. The aim of this study was to derive occupational TTCs (OTTCs) reflecting the airborne concentrations below which no significant risk to workers would be anticipated. A reference dataset consisting of the 8-h threshold limit values-Time-Weighted Average for 280 organic substances was compiled. Each substance was classified into low (class I), intermediate (class II), or high (class III) hazard categories as per Cramer rules. For each chemical, n-octanol:water partition coefficient and vapor pressure along with the molecular weight were used to predict the blood:air partition coefficient. The blood:air partition coefficient along with data on water solubility and ventilation rate allowed the prediction of pulmonary retention factor and absorbed dose in workers. For each Cramer class, the distribution of the predicted doses was analyzed to identify the various percentile values corresponding to the OTTC. Accordingly, for Cramer classes I-III, the OTTCs derived in this study correspond to 0.15, 0.0085, and 0.006 mmol/d, respectively, at the 10th percentile level, while these values were 1.5, 0.09 and 0.03 mmol/d at the 25th percentile level. The proposed OTTCs are not meant to replace the traditional occupational exposure limits, but can be used in data-poor situations along with exposure estimates to support screening level risk assessment and prioritization.