The Impact of Pesticides - Academy Publish

faecal metabolites (e.g. F x (t), F y (t), …). Other excretion compartments may be alsoadded to describe the excretion of the non-monitored metabolites (N(t)).Once the model is functionally represented by compartments and systems ofdifferential equations, equations are solved to yield the mathematical functions ofthe time courses of the pesticide and each of its relevant metabolites in the differentcompartments. Initial conditions for every compartment are set in the experiment tobe zero at starting time of the kinetic modeling. The next step therefore consists indetermining the analytical solutions of the various linear first-order differentialequations for oral, respiratory, dermal exposure, and any other relevant route-ofentryin the body.Subsequently, model parameters are determined and adjusted to available literaturedata on the human kinetic time course following controlled exposure doses, alongwith in vitro studies and in vivo animal kinetics to complete human data whennecessary. More specifically, the model parameters are computed by best-fitadjustments of the explicit solutions of differential equations to these time coursedata using a mathematical software. To best-fit general analytical functions to datasets, several procedures exist, but the least-square algorithm is a method often used(Weisstein, 2010).Model Simulations, Sensitivity Analysis and ValidationOnce parameters are estimated, simulations of the time course of the pesticide andits metabolites in the body and in excreta are performed by solving numerically thedifferential equation system using a mathematical software (e.g. the Runge-Kuttamethod incorporated in MathCad). Hence, by introducing time varying inputs andusing the same set of parameter values, the model predicts amounts absorbed underdifferent exposure scenarios (single or repeated, intermittent or continuousinhalation, dermal or oral exposures) starting from measurements of urinaryamounts of biomarkers accumulated over specific time periods. This approach hasthe advantage of estimating the body burden of a chemical and its internal evolutionregardless the route-of-entry and without reference to ambient concentrations.The sensitivity of each of the model parameter values is then tested to determinetheir capacity to influence the predicted urinary excretion at different cumulativetimes (e.g. 12-h or 24-h urinary excretion). This mathematical procedure allowsdetermining how much the value of a dependent function is modified when aparticular independent degree of freedom is changed, while keeping all theremaining parameters unaffected. Lastly, the developed model is validated usingdifferent sets of experimental data available in the literature and for different routesof-exposurein humans.Derivation of BRV Using ModelingOnce validated, toxicokinetic models may be used to assess health risks related topesticide exposures. Indeed, as models can be used to reconstruct the absorbeddoses from measurements of cumulative urinary biomarkers, it is thus possible toestablish the average daily absorbed dose corresponding, for each chemical studied,to a safe exposure level preventing early biological effects. The selected safeexposure level is based on a conservative reference dose, such as a human noobserved-(adverse)-effectlevel (NO(A)EL) dose, below which individuals shouldAcademyPublish.org - The Impact of Pesticides109