This study investigated whether, in the absence of chronic noncancer toxicity data, short-term noncancer toxicity data can be used to predict chronic toxicity effect levels by focusing on the dose-response relationship instead of a critical effect. Data from National Toxicology Program (NTP) technical reports have been extracted and modeled using the Environmental Protection Agency's Benchmark Dose Software. Best-fit, minimum benchmark dose (BMD), and benchmark dose lower limits (BMDLs) have been modeled for all NTP pathologist identified significant nonneoplastic lesions, final mean body weight, and mean organ weight of 41 chemicals tested by NTP between 2000 and 2012. Models were then developed at the chemical level using orthogonal regression techniques to predict chronic (two years) noncancer health effect levels using the results of the short-term (three months) toxicity data. The findings indicate that short-term animal studies may reasonably provide a quantitative estimate of a chronic BMD or BMDL. This can allow for faster development of human health toxicity values for risk assessment for chemicals that lack chronic toxicity data.
Keywords: Chemical alternatives assessment; chemical risk assessment; predicative toxicity testing.
© 2017 Society for Risk Analysis.