Population pharmacokinetics of enrofloxacin and its active metabolite ciprofloxacin in ill cows

Effect of bovine ABCG2 Y581S polymorphism on concentrations in milk of enrofloxacin and its active metabolite ciprofloxacin

The ATP-binding cassette transporter G2 (ABCG2) is involved in the secretion of several drugs into milk. The bovine Y581S ABCG2 polymorphism increases the secretion into milk of the fluoroquinolone danofloxacin in Holstein cows. Danofloxacin and enrofloxacin are the fluoroquinolones most widely used in veterinary medicine. Both enrofloxacin (ENRO) and its active metabolite ciprofloxacin (CIPRO) reach milk at relatively high concentrations. The aim of this work was to study the effect of the bovine Y581S ABCG2 polymorphism on in vitro transport as well as on concentrations in plasma and in milk of ENRO and CIPRO. Experiments using cells overexpressing bovine ABCG2 showed the effects of ABCG2 on the transport of CIPRO, demonstrating more efficient in vitro transport of this antimicrobial by the S581 variant as compared with the Y581 variant. Animal studies administering 2.5mg/kg of ENRO subcutaneously to Y/Y 581 and Y/S 581 cows revealed that concentrations in plasma of ENRO and CIPRO were significantly lower in Y/S animals. Regardless of the genotype, the antimicrobial profile in milk after the administration of ENRO was predominantly of CIPRO. With respect to the genotype effects on the amounts of drugs present in milk, AUC0-24 values were more than 1.2 times higher in Y/S cows for ENRO and 2.2 times for CIPRO, indicating a greater capacity of Y581S to transfer these drugs into milk. These results emphasize the clinical relevance of this polymorphism as a factor affecting the concentrations in plasma and in milk of drugs of importance in veterinary medicine.

Using robust Bayesian network to estimate the residuals of fluoroquinolone antibiotic in soil

Prediction of antibiotic pollution and its consequences is difficult, due to the uncertainties and complexities associated with multiple related factors. This article employed domain knowledge and spatial data to construct a Bayesian network (BN) model to assess fluoroquinolone antibiotic (FQs) pollution in the soil of an intensive vegetable cultivation area. The results show: (1) The relationships between FQs pollution and contributory factors: Three factors (cultivation methods, crop rotations, and chicken manure types) were consistently identified as predictors in the topological structures of three FQs, indicating their importance in FQs pollution; deduced with domain knowledge, the cultivation methods are determined by the crop rotations, which require different nutrients (derived from the manure) according to different plant biomass. (2) The performance of BN model: The integrative robust Bayesian network model achieved the highest detection probability (pd) of high-risk and receiver operating characteristic (ROC) area, since it incorporates domain knowledge and model uncertainty. Our encouraging findings have implications for the use of BN as a robust approach to assessment of FQs pollution and for informing decisions on appropriate remedial measures.

A framework for meta-analysis of veterinary drug pharmacokinetic data using mixed effect modeling

Combining data from available studies is a useful approach to interpret the overwhelming amount of data generated in medical research from multiple studies. Paradoxically, in veterinary medicine, lack of data requires integrating available data to make meaningful population inferences. Nonlinear mixed-effects modeling is a useful tool to apply meta-analysis to diverse pharmacokinetic (PK) studies of veterinary drugs. This review provides a summary of the characteristics of PK data of veterinary drugs and how integration of these data may differ from human PK studies. The limits of meta-analysis include the sophistication of data mining, and generation of misleading results caused by biased or poor quality data. The overriding strength of meta-analysis applied to this field is that robust statistical analysis of the diverse sparse data sets inherent to veterinary medicine applications can be accomplished, thereby allowing population inferences to be made.

Population pharmacokinetics of cefquinome in pigs

This study was performed in 145 pigs to develop a population pharmacokinetics (PPK) model by i.m. administration of cefquinome (CEQ) at the dose of 2 mg/kg in the neck muscle. Serum physiological and biochemical parameters for each pig were determined before administration. After administration, 2-4 samples were collected at random, with the sampling point evenly distributed in the three periods (<1 h, 1-4 h and >4 h). The plasma concentration of CEQ was determined by high performance liquid chromatography with UV detector. The pharmacostatistical analyses of concentration-time data, weight, age, gender, serum physiological and biochemical parameters were performed with nonlinear mixed effect modeling (NONMEM). A one-compartmental model with first-order absorption and elimination adequately described the data from the study group. The optimal random effect model of pharmacokinetics parameters was of log-normal distribution and the residual errors assumed a mixed-type model (proportional and additive) to best explain intra-individual variability. Covariate analysis showed that body weight is positively correlated with apparent volume of distribution (V/F) and body clearance (CL/F). The typical PPK parameters of Ka , CL, and V were 0.564/h, 5.15 L/h, and 1.36 L, respectively.

Methods for the analysis of fluoroquinolones in biological fluids

Methods for the analysis of ten selected fluoroquinolone antibiotics in biological fluids are reviewed. Approaches for sample preparation, detection methods, limits of detection and quantitation, and recovery information are provided for both single analyte and multi-analyte fluoroquinolone methods.