Crop Life America seeks review of EPA's Science Advisory Panel

CLA believes the EPA has not had the opportunity to review all the material at the fault of the studies’ authors, who have repeatedly denied EPA access to the full information.
CLA believes the EPA has not had the opportunity to review all the material at the fault of the studies’ authors, who have repeatedly denied EPA access to the full information.

The Environmental Protection Agency is planning a Science Advisory Panel (SAP) in April where it will decide whether or not to use flawed epidemiology studies in pesticide regulation. 

In the past, the EPA has used sound scientific risk assessment and fails to address concerns expressed in previous SAPs.

Crop Life America (CLA) wants the EPA to postpone the panel until the epidemiology study results have been generated and reviewed. CLA also states the EPA’s use of the studies should be subject to public review. 

CLA believes the EPA has not had the opportunity to review all the material at the fault of the studies’ authors, who have repeatedly denied EPA access to the full information.

In the past, pesticides have been studied based on the EPA’s strict health and safety standards where effects on humans are documented and results can be replicated. The EPA has consistently used epidemiology studies as a basis for requiring additional regulatory guideline studies, not for setting regulatory standards.

The EPA’s own guidance says: “When animal and epidemiologic data do not provide a consistent toxicological picture of a particular pesticide, more weight would likely be given to those studies with robust study design and availability of replication or confirmatory data.” – Draft Framework for Incorporating Human Epidemiologic & Incident Data in Health Risk Assessment,” 2010, Office of Pesticide Programs, U.S. Environmental Protection Agency. Washington, D.C., Page 31.

Because of this standard, CLA believes that according to EPA policy when data conflicts, higher quality data is better than lesser quality data.