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
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
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 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 determine elimination kinetics of tilmicosin in milk following intramammary administration in lactating dairy cattle.
Design—Prospective pharmacokinetic study.
Animals—6 lactating dairy cows.
Procedures—Following collection of baseline milk samples, 1,200 mg (4 mL) of tilmicosin was infused into the left front and right rear mammary glands of each cow. Approximately 12 hours later, an additional 1,200 mg of tilmicosin was infused into the left front and right rear glands after milking. Milk samples were then collected from each gland at milking time for 40 days. Concentration of tilmicosin was determined by means of ultraperformance liquid chromatography–mass spectrometry, and a milk withdrawal interval for tilmicosin was calculated on the basis of the tolerance limit method.
Results—Although there was considerable variation between glands, concentration of tilmicosin was high in milk from treated glands and had a long half-life in treated and untreated glands. Tilmicosin was detected in all treated glands for the entire 40-day study period and was detected in untreated glands for approximately 30 to 35 days.
Conclusions and Clinical Relevance—Findings indicated that tilmicosin should not be administered by the intramammary route in lactating dairy cows. Milk from all glands of any cows accidentally treated should be discarded for a minimum of 82 days following intramammary administration.
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
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)