New Confidence: Optimizing Benchmark Dose Modeling to Improve Risk Assessment
نویسنده
چکیده
Benchmark dose (BMD) modeling has been touted as a more accu rate method for conducting chemical risk assessments. In this issue of EHP, a team of researchers applied BMD modeling to hundreds of chemicals whose health effects are already known in an effort to optimize the approach. To calculate the highest safe oral dose of a noncarcinogenic chem ical, regulators must first estimate the pointofdeparture (POD) dose—that is, the dose below which the chemical does not increase disease risk. This POD is then divided by an uncertainty factor to build in extra safety, resulting in a reference dose. In selecting a POD regulators may use the lower confidence limit of the BMD (a value abbreviated BMDL), or they may use the noobservedadverseeffect level (NOAEL) obtained from animal experiments.
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