Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Werribee, Australia, 3030.
College of Veterinary Medicine, University of Illinois, Urbana 61802.
J Dairy Sci. 2020 Nov;103(11):10639-10650. doi: 10.3168/jds.2020-18760. Epub 2020 Sep 10.
Predictions of drug residues in milk are critical in food protection and are a major consideration in the economics of treatment of mastitis in dairy cows. Nonlinear mixed-effects modeling (NLME) has been advocated as a suitable pharmaco-statistical method for the study of drug residues in milk. Recent developments in physiologically based pharmacokinetic (PBPK) modeling of intramammary drugs allow the combination of a mechanistic description of milk pharmacokinetics with NLME methods. The PBPK model was applied to NLME analysis of a data set consisting of milk drug concentrations from 78 healthy cows and 117 with clinical mastitis. Pirlimycin milk pharmacokinetics were adequately described by the model across the range of observed concentrations. Mastitis was characterized by increased variance in milk production volume. Udder residual volume was larger in cows with 1, or 2 or greater diseased mammary glands than in the healthy cows. Low-producing cows had a greater risk of prolonged milk residues. With the exclusion of the low-production cows, the model predicted that healthy cows required a milk discard time 12 h longer than that indicated by the label, and the diseased cows 36 h longer than indicated by the label. More pirlimycin was systemically absorbed in the gram-positive infected compared with the gram-negative infected or healthy cows, suggesting a greater risk of violative meat residues in gram-positive infected cows. Using NLME and PBPK models, we identified factors associated with changes in pirlimycin milk residues that may affect food safety. This model extends the verification of a simple physiologically based framework for the study of intramammary drugs.
预测牛奶中的药物残留对于食品保护至关重要，也是奶牛乳腺炎治疗经济学的主要考虑因素。非线性混合效应模型（NLME）已被提倡作为研究牛奶中药物残留的合适药物统计方法。最近，在乳腺内药物的基于生理学的药代动力学（PBPK）建模方面的进展使得可以将奶药代动力学的机制描述与 NLME 方法相结合。该 PBPK 模型被应用于由 78 头健康奶牛和 117 头患有临床乳腺炎的奶牛的牛奶药物浓度数据集的 NLME 分析。该模型在观察到的浓度范围内充分描述了吡利霉素的牛奶药代动力学。乳腺炎的特征是产奶量的方差增加。与健康奶牛相比，1 个或 2 个或更多患病乳腺的奶牛的乳房残留体积更大。低产奶牛有更长时间的牛奶残留的风险。排除低产奶牛后，模型预测健康奶牛需要比标签指示的更长的 12 小时的牛奶弃置时间，患病奶牛需要比标签指示的更长的 36 小时的牛奶弃置时间。与革兰氏阴性感染或健康奶牛相比，革兰氏阳性感染的奶牛系统吸收的吡利霉素更多，这表明革兰氏阳性感染的奶牛存在更高的违规肉残留风险。通过使用 NLME 和 PBPK 模型，我们确定了与吡利霉素牛奶残留变化相关的因素，这些因素可能会影响食品安全。该模型扩展了对简单基于生理学的乳腺内药物研究框架的验证。
