Establishing short-term occupational exposure limits (STELs) for sensory irritants using predictive and in silico respiratory rate depression (RD₅₀) models

Abstract

Sensory irritation is a health endpoint that serves as the critical effect basis for many occupational exposure limits (OELs). Schaper 1993 described a significant relationship with high correlation between the measured exposure concentration producing a 50% respiratory rate decrease (RD₅₀) in a standard rodent assay and the American Conference of Governmental Industrial Hygienists (ACGIH®) Threshold Limit Values (TLVs®) as time-weighted averages (TWAs) for airborne chemical irritants. The results demonstrated the potential use of the RD₅₀ values for deriving full-shift TWA OELs protective of irritant responses. However, there remains a need to develop a similar predictive model for deriving workplace short-term exposure limits (STELs) for sensory irritants. The aim of our study was to establish a model capable of correlating the relationship between RD₅₀ values and published STELs to prospectively derive short-term exposure OELs for sensory irritants. A National Toxicology Program (NTP) database that included chemicals with both an RD₅₀ and established STELs was used to fit several linear regression models. A strong correlation between RD₅₀s and STELs was identified, with a predictive equation of ln (STEL) (ppm) = 0.86 * ln (RD₅₀) (ppm) − 2.42 and an R² value of 0.75. This model supports the use of RD₅₀s to derive STELs for chemicals without existing exposure recommendations. Further, for data-poor sensory irritants, predicted RD₅₀ values from in silico quantitative structure activity relationship (QSAR) models can be used to derive STELs. Hence, in silico methods and statistical modeling can present a path forward for establishing reliable OELs and improving worker safety and health.

Keywords:

• Sensory irritants
• STEL
• RD₅₀
• acute exposures
• worker health
• occupational exposure limits

Acknowledgments

The authors would like to thank Dr. Yves Alarie for his comments, input, and direction on initial and subsequent drafts of this manuscript.

Author contributions

Anthony Russell: Methodology, Statistical Analysis, Investigation, Synthesis, Writing - Original Draft, Review and Editing. Amanda Buerger: Investigation, Data Collection, Literature Review, Writing – Original Draft, Review and Editing. Melissa Vincent: Methodology, Scoping, Writing – Review and Editing. Scott Dotson: Conceptualization, Writing – Review and Editing. Jason Lotter: Conceptualization, Writing – Review and Editing, Andrew Maier: Conceptualization, Methodology, Synthesis, Writing – Original Draft, Review and Editing

Disclosure statement

Anthony Russell and Andrew Maier are employed by Stantec ChemRisk, a consulting firm that provides scientific support to the government, corporations, law firms, and various scientific/professional organizations. Scott Dotson and Jason Lotter were previously employed by Stantec ChemRisk and are currently employed by Insight Exposure & Risk Sciences Group, a consulting firm that also provides scientific support to corporations, law firms, and various scientific/professional organizations. Melissa Vincent and Amanda Buerger were previously employed by Stantec ChemRisk and are currently employed by Tox Strategies, a consulting firm specializing in risk assessment. The authors declare no other potential conflicts. The content and the conclusions of the manuscript are exclusively those of the authors.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article or its supplementary materials.

Notes

1 OSHA Annotated Table Z-1: https://www.osha.gov/annotated-pels/table-z-1#notes.

2 https://chem.nlm.nih.gov/chemidplus/.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.