What Can Be Learnt from Protocols Relating to Non-Pharmaceuticals?
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Abstract
The U.S. EPA administers two statutes that provide authority for requiring toxicity testing, including reproductive and developmental toxicity. These are the Toxic Substances Control Act (TSCA), and the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA). Under these statutes, the EPA has guidelines for reproductive and developmental toxicity testing that include the standard developmental toxicity (Segment Il) test protocol, the two-generation reproduction study protocol, and the developmental neurotoxicity testing protocol. Under TSCA, reproductive and developmental toxicity studies are required on a case-by-case basis depending on whether or not there is reason to suspect that an agent may have reproductive or developmental effects, or if production and/or release of a chemical is likely to be substantial. Under FIFRA, standard developmental toxicity studies in two species and a two-generation reproduction study in rats are required for all food use pesticides and for non-food use pesticides when exposure is likely. evelopmental neurotoxicity studies are required in cases where indications from other data suggest concern.The EPA has also developed guidelines for reproductive and developmental toxicity risk assessment that describe the evaluation of data for extrapolation to humans. These guidelines provide the basic assumptions that are made in the risk assessment process and the procedures used to estimate exposure levels that are not expected to increase the risk for reproductive or developmental effects above background incidence rates. Data from developmental toxicity, developmental neurotoxicity and reproduction studies form the primary data base used in reproductive and developmental toxicity risk assessments, but may be enhanced by data from other studies, including pharmacokinetic and mechanistic studies. The development of risk assessment guidance has been extremely helpful in identifying data needed for reducing uncertainties, eliminating assumptions and improving the qualitative and quantitative extrapolation of data to exposed human populations.