You are looking at 1 - 10 of 33 items for
- Author or Editor: Jim Riviere x
- Refine by Access: All Content x
Objective—To model the plasma tetracycline concentrations in swine (Sus scrofa domestica) treated with medication administered in water and determine the factors that contribute to the most accurate predictions of measured plasma drug concentrations.
Sample—Plasma tetracycline concentrations measured in blood samples from 3 populations of swine.
Procedures—Data from previous studies provided plasma tetracycline concentrations that were measured in blood samples collected from 1 swine population at 0, 4, 8, 12, 24, 32, 48, 56, 72, 80, 96, and 104 hours and from 2 swine populations at 0, 12, 24, 48, and 72 hours hours during administration of tetracycline hydrochloride dissolved in water. A 1-compartment pharmacostatistical model was used to analyze 5 potential covariate schemes and determine factors most important in predicting the plasma concentrations of tetracycline in swine.
Results—2 models most accurately predicted the tetracycline plasma concentrations in the 3 populations of swine. Factors of importance were body weight or age of pig, ambient temperature, concentration of tetracycline in water, and water use per unit of time.
Conclusions and Clinical Relevance—The factors found to be of importance, combined with knowledge of the individual pharmacokinetic and chemical properties of medications currently approved for administration in water, may be useful in more prudent administration of approved medications administered to swine. Factors found to be important in pharmacostatistical models may allow prediction of plasma concentrations of tetracycline or other commonly used medications administered in water. The ability to predict in vivo concentrations of medication in a population of food animals can be combined with bacterial minimum inhibitory concentrations to decrease the risk of developing antimicrobial resistance.
Objective—To develop a flow-limited, physiologicbased pharmacokinetic model for use in estimating concentrations of sulfamethazine after IV administration to swine.
Sample Population—4 published studies provided physiologic values for organ weights, blood flows, clearance, and tissue-to-blood partition coefficients, and 3 published studies provided data on plasma and other tissue compartments for model validation.
Procedure—For the parent compound, the model included compartments for blood, adipose, muscle, liver, and kidney tissue with an extra compartment representing the remaining carcass. Compartments for the N-acetyl metabolite included the liver and the remaining body. The model was created and optimized by use of computer software. Sensitivity analysis was completed to evaluate the importance of each constant on the whole model. The model was validated and used to estimate a withhold interval after an IV injection at a dose of 50 mg/kg. The withhold interval was compared to the interval estimated by the Food Animal Residue Avoidance Databank (FARAD).
Results—Specific tissue correlations for plasma, adipose, muscle, kidney, and liver tissue compartments were 0.93, 0.86, 0.99, 0.94, and 0.98, respectively. The model typically overpredicted concentrations at early time points but had excellent accuracy at later time points. The withhold interval estimated by use of the model was 120 hours, compared with 100 hours estimated by FARAD.
Conclusions and Clinical Relevance—Use of this model enabled accurate prediction of sulfamethazine pharmacokinetics in swine and has applications for food safety and prediction of drug residues in edible tissues. (Am J Vet Res 2005;66:1686–1693)
Objective—To determine the pharmacokinetics of marbofloxacin after oral administration in juvenile harbor seals (Phoca vitulina) at a dose of 5 mg/kg (2.3 mg/lb) and to compare pharmacokinetic variables after pharmacokinetic analysis by naïve averaged, naïve pooled, and nonlinear mixed-effects modeling.
Animals—33 male and 22 female juvenile seals being treated for various conditions.
Procedures—Blood collection was limited to ≤ 3 samples/seal. Plasma marbofloxacin concentrations were measured via high-pressure liquid chromatography with UV detection.
Results—Mean ± SE dose of marbofloxacin administered was 5.3 ± 0.1 mg/kg (2.4 ± 0.05 mg/lb). The terminal half-life, volume of distribution (per bioavailability), and clearance (per bioavailability) were approximately 5 hours, approximately 1.4 L/kg, and approximately 3 mL/min/kg, respectively (values varied slightly with the method of calculation). Maximum plasma concentration and area under the plasma-time concentration curve were approximately 3 μg/mL and 30 h·μg/mL, respectively. Naïve averaged and naïve pooled analysis appeared to yield a better fit to the population, but nonlinear mixed-effects modeling yielded a better fit for individual seals.
Conclusions and Clinical Relevance—Values of pharmacokinetic variables were similar regardless of the analytic method used. Pharmacokinetic variability can be assessed with nonlinear mixed-effects modeling, but not with naïve averaged or naïve pooled analysis. Visual observation by experienced trainers revealed no adverse effects in treated seals. Plasma concentrations attained with a dosage of 5 mg/kg every 24 hours would be expected to be efficacious for treatment of infections caused by susceptible bacteria (excluding Pseudomonas aeruginosa).
Objective—To determine whether pharmacokinetics and milk elimination of flunixin and 5-hydroxy flunixin differed between healthy and mastitic cows.
Design—Prospective controlled clinical trial.
Animals—20 lactating Holstein cows.
Procedures—Cows with mastitis and matched control cows received flunixin IV, ceftiofur IM, and cephapirin or ceftiofur, intramammary. Blood samples were collected before (time 0) and 0.25, 0.5, 1, 2, 4, 8, 12, 24, and 36 hours after flunixin administration. Composite milk samples were collected at 0, 2, 12, 24, 36, 48, 60, 72, 84, and 96 hours. Plasma and milk samples were analyzed by use of ultra–high-performance liquid chromatography with mass spectrometric detection.
Results—For flunixin in plasma samples, differences in area under the concentration-time curve and clearance were detected between groups. Differences in flunixin and 5-hydroxy flunixin concentrations in milk were detected at various time points. At 36 hours after flunixin administration (milk withdrawal time), 8 cows with mastitis had 5-hydroxy flunixin concentrations higher than the tolerance limit (ie, residues). Flunixin residues persisted in milk up to 60 hours after administration in 3 of 10 mastitic cows.
Conclusions and Clinical Relevance—Pharmacokinetics and elimination of flunixin and 5-hydroxy flunixin in milk differed between mastitic and healthy cows, resulting in violative residues. This may partially explain the high number of flunixin residues reported in beef and dairy cattle. This study also raised questions as to whether healthy animals should be used when determining withdrawal times for meat and milk.
Objective—To determine the tissue depletion profile of tulathromycin and determine an appropriate slaughter withdrawal interval in meat goats after multiple SC injections of the drug.
Animals—16 healthy Boer goats.
Procedures—All goats were administered tulathromycin (2.5 mg/kg, SC) twice, with a 7-day interval between doses. Blood samples were collected throughout the study, and goats were euthanized at 2, 5, 10, and 20 days after the second tulathromycin dose. Lung, liver, kidney, fat, and muscle tissues were collected. Concentrations of tulathromycin in plasma and the hydrolytic tulathromycin fragment CP-60,300 in tissue samples were determined with ultrahigh-pressure liquid chromatography–tandem mass spectrometry.
Results—The plasma profile of tulathromycin was biphasic. Absorption was very rapid, with maximum drug concentrations (1.00 ± 0.42 μg/mL and 2.09 ± 1.77 μg/mL following the first and second doses, respectively) detected within approximately 1 hour after injection. Plasma terminal elimination half-life of tulathromycin was 61.4 ± 14.1 hours after the second dose. Half-lives in tissue ranged from 2.4 days for muscle to 9.0 days for lung tissue; kidney tissue was used to determine the withdrawal interval for tulathromycin in goats because it is considered an edible tissue.
Conclusions and Clinical Relevance—On the basis of the tissue tolerance limit in cattle of 5 ppm (μg/g), the calculated withdrawal interval for tulathromycin would be 19 days following SC administration in goats. On the basis of the more stringent guidelines recommended by the FDA, the calculated meat withdrawal interval following tulathromycin administration in goats was 34 days.
Objective—To investigate the feasibility of using multivariate cluster analysis to meta-analyze pharmacokinetic data obtained from studies of pharmacokinetics of ampicillin trihydrate in cattle and identify factors that could account for variability in pharmacokinetic parameters among studies.
Sample Population—Data from original studies of the pharmacokinetics of ampicillin trihydrate in cattle in the database of the Food Animal Residue Avoidance Databank.
Procedure—Mean plasma or serum ampicillin concentration versus time data and potential factors that may have affected the pharmacokinetics of ampicillin trihydrate were obtained from each study. Noncompartmental pharmacokinetic analyses were performed, and values of pharmacokinetic parameters were clustered by use of multivariate cluster analysis. Practical importance of the clusters was evaluated by comparing the frequency of factors that may have affected the pharmacokinetics of ampicillin trihydrate among clusters.
Results—A single cluster with lower mean values for clearance and volume of distribution of ampicillin trihydrate administered PO, compared with other clusters, was identified. This cluster included studies that used preruminant calves in which feeding was withheld overnight and calves to which probenecid had been administered concurrently.
Conclusions and Clinical Relevance—Meta-analysis was successful in detecting a potential subpopulation of cattle for which factors that explained differences in pharmacokinetic parameters could be identified. Accurate estimates of pharmacokinetic parameters are important for the calculation of dosages and extended withdrawal intervals after extralabel drug administration. (Am J Vet Res 2005;66:108–112)