Using Monte Carlo Techniques to Estimate Pesticide Residue Levels in Edible Animal Tissues. J. R. Tomerlin, L. M. Barraj, J. Barron, and J. Cappy, Novigen Sciences, 1730 Rhode Island Avenue, NW Washington, DC 20036; and Rhône-Poulenc AG Company, 2 T. W. Alexander Drive, Research Triangle Park, NC 27709
The EPA is charged with protecting the environment and humankind. One aspect of the EPA’s mandate is the assessment of the effect of pesticides on human health. Over the past several years, and more recently following the passage of the Food Quality Protection Act of 1996, the EPA has developed a tiered approach for assessing potential risk to pesticide residues in the diet. An initial assessment uses worst case assumptions to estimate risk. Subsequent analyses using refined information and more sophisticated techniques will be used depending on the outcome of previous, more conservative analyses. The estimation and safety evaluation of residue levels in edible animal tissues (e.g., beef muscle, milk, or eggs), however, has been excluded from some of the advances in the EPA’s thinking regarding dietary risk assessment. Residues in edible animal tissues are a function of the residue concentration on the feeds consumed by the animals and the proportion of the feeds in the animal diets. The analyst may take into account the residue on the raw agricultural commodity, appropriate processing factors, the proportion of the feed item in the animal diet, and, for ruminants, the percent dry matter of the feed item in calculating the amount of pesticide ingested by the animal. This amount is known as the dietary burden. The magnitude of the residue in the edible animal tissues is then calculated as the product of the dietary burden and a transfer coefficient from animal feeding studies. The EPA’s residue chemistry guidelines provide guidance for determining how to construct putative animal diets for the estimation of residues. Historically, point estimates of residues were used and a worst case diet was assumed. The worst case diet combines the animal feed items such that the total dietary burden is maximized, regardless of whether or not such a diet would be followed in practice. Monte Carlo techniques may be used to model some of the realistic mitigating factors that determine residue levels in edible animal tissues. For example, Monte Carlo techniques allow the analyst to incorporate the percent of crop treated, even for dietary analyses of acutely toxic pesticides. Furthermore, actual animal diets are variable, and Monte Carlo techniques can select feed items randomly, or bias the feed items included in the analysis toward more nutritionally sound diets. The use of Monte Carlo techniques may yield a 10-fold decrease in the estimated residue in edible animal tissues, compared to a simple point estimate.