Residue study designs for dietary risk assessment and maximum residue limit (MRL) determination were established in an earlier scientific era with different analytical capabilities, data resolution, and sources of uncertainty. Advances in analytical chemistry, study execution, and statistical science have since transformed how residue data are generated, while MRL calculations have remained static.

The OECD MRL Calculator provides a harmonized and protective framework for translating residue trial data into regulatory limits using conservative upper bound estimates which is a function of the mean, standard deviation, and underlying distribution as shown in the OECD Calculator. As the scientific context of residue data generation evolves, an important question emerges: how can modern residue study designs be evaluated using contemporary statistical understanding so that MRL calculations remain both conservative and scientifically fit for purpose?

This work uses statistical sampling principles and OECD framework to align residue study design with current scientific capability while preserving regulatory intent and consumer protection. Three approaches are highlighted: 1) Dissipation time curve data are evaluated to estimate residues at the target preharvest interval and to improve the harvest-relevant estimates for both mean and standard deviation; 2) observed residue distributions are examined to understand how distributional form and variability contribute to conservative upper bound estimates as the sample size changes, while retaining protective defaults when warranted; and 3) hierarchical variability is assessed within trials, between sites, and across regions to identify where uncertainty arises and to support fit for purpose sampling strategies.

Together, these considerations represent well established statistical sampling problems rather than predictive or mechanistic modeling approaches. Applying these principles within the OECD MRL Calculator framework enhances transparency and scientific rigor while fully preserving the conservative role of MRLs.

Pamela Jensen Ph.D.

Principal Scientist, Bayer CropScience LLC

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