Use of Probabilistic Modeling within a Physiologically BasedPharmacokinetic Model To Predict Sulfamethazine Residue Withdrawal Times in Edible Tissues in Swine

Abstract

The presence of antimicrobial agents in edible tissues of food-producing animals remains a major public health concern. Probabilistic modeling techniques incorporated into a physiologically based pharmacokinetic (PBPK) model were used to predict the amounts of sulfamethazine residues in edible tissues in swine. A PBPK model for sulfamethazine in swine was adapted to include an oral dosing route. The distributions for sensitive parameters were determined and were used in a Monte Carlo analysis to predict tissue residue times. Validation of the distributions was done by comparison of the results of a Monte Carlo analysis to those obtained with an external data set from the literature and an in vivo pilot study. The model was used to predict the upper limit of the 95% confidence interval of the 99th percentile of the population, as recommended by the U.S. Food and Drug Administration (FDA). The external data set was used to calculate the withdrawal time by using the tolerance limit algorithm designed by FDA. The withdrawal times obtained by both methods were compared to the labeled withdrawal time for the same dose. The Monte Carlo method predicted a withdrawal time of 21 days, based on the amounts of residues in the kidneys. The tolerance limit method applied to the time-limited data set predicted a withdrawal time of 12 days. The existing FDA label withdrawal time is 15 days. PBPK models can incorporate probabilistic modeling techniques that make them useful for prediction of tissue residue times. These models can be used to calculate the parameters required by FDA and explore those conditions where the established withdrawal time may not be sufficient.Sulfamethazine is a sulfonamide antibiotic used in the swine industry as a feed or water additive. It is labeled for the treatment of bacterial pneumonia, cervical abscesses, and bacterial swine enteritis, as well as for the prevention of these diseases during times of stress, maintenance of weight gains in the presence of atrophic rhinitis, growth promotion, and increased feed efficiency (14). Research has shown that high concentrations of this drug may cause thyroid tumors in specific strains of rats (35). Also, a wide range of human allergic reactions are related to sulfonamide drugs in general (37, 43). Thus, there is a large public health concern relating to the possible adverse health effects of consuming sulfamethazine residues found in the edible tissues of swine, warranting the development of predictive pharmacokinetic models.Meat withdrawal periods are required by the U.S. Food and Drug Administration (FDA) to ensure the safety of the meat supply and to address this public health concern. A meat withdrawal period is the time between when a chemotherapeutic is administered to a food animal and the time when that animal is sent to slaughter. These periods are designed to guarantee that the amounts of drug residues in edible tissues will be below tolerance levels before animals are sent to slaughter. Currently, withdrawal times are determined by the toleranc...

Interspecies Mixed-Effect Pharmacokinetic Modeling of Penicillin G in Cattle and Swine

“…and drug disposition, which will facilitate the determination of efficacy and safety of drugs. So far, a stochastic pharmacokinetic model was successful in determining effects of variability in systemic pharmacokinetics on tissue depletion of sulfamethazine in swine (21). Wu et al investigated the influence of PK parameters on flunixin tissue residue concentrations in livers using a population pharmacokinetic model (22).…”

Tissue concentrations of sulfamethazine and tetracycline hydrochloride of swine ( Sus scrofa domestica ) as it relates to withdrawal methods for international export

“…AUC inf , C ss and C max match the range that was seen after water medication dosing. The kinetic profiles including calculated half-life for the finisher pigs for SMZ appear to be relatively consistent with previous compartmental and physiologic-based studies (Buur et al, 2006). The withdrawal interval calculations below are based on data that is consistent with previous studies and is similar to the data that was originally used to calculate the FDA withdrawal times.…”

“…From contamination reports by McCauley et al (1990McCauley et al ( , 1991, the withdrawal time for sulfamethazine was expected to be longer than that reported by the FDA in the Green Book (FDA, 2013), especially for export to countries with a lower residue limit than the US (Table 3). Based on our study and one by Buur et al (2006), the current FDA withdrawal time could be re-evaluated and our data suggest a withdrawal time of at least 19 days based on concentrations in the liver using the population PK model in finisher pigs and 20 days in weanling pigs. The TLM using our data predicts a 16-day withdrawal (Fig.…”

“…Sulfamethazine appears to require a longer withdrawal time than the currently acceptable US withdrawal time of 15 days using the US FDA tolerance method (Table 3). Buur et al (2005Buur et al ( , 2006 previously reported that the 15-day WDT was inadequate based upon a physiologic PK model. From contamination reports by McCauley et al (1990McCauley et al ( , 1991, the withdrawal time for sulfamethazine was expected to be longer than that reported by the FDA in the Green Book (FDA, 2013), especially for export to countries with a lower residue limit than the US (Table 3).…”

Use of a Monte Carlo analysis within a physiologically based pharmacokinetic model to predict doxycycline residue withdrawal time in edible tissues in swine

“…In veterinary medicine, the PBPK model has been used to study pharmacokinetics (Gustafson and Thamm 2010) and tissue distribution (Brocklebank et al 1997;Craigmill 2003;Cortright et al 2009). Other reports have used the PBPK model to predict residue withdrawal time (Buur et al 2006(Buur et al , 2008Yuan et al 2011). Compared with the linear regression method, the PBPK model is based on physiological mechanisms and uses mass balance equations to link tissue compartments via blood flow.…”