title: Interspecies mixed-effect pharmacokinetic modeling of penicillin G in cattle and swine.
abstract: Extralabel drug use of penicillin G in food-producing animals may cause an excess of residues in tissue which will have the potential to damage human health. Of all the antibiotics, penicillin G may have the greatest potential for producing allergic responses to the consumer of food animal products. There are, however, no population pharmacokinetic studies of penicillin G for food animals. The objective of this study was to develop a population pharmacokinetic model to describe the time-concentration data profile of penicillin G across two species. Data were collected from previously published pharmacokinetic studies in which several formulations of penicillin G were administered to diverse populations of cattle and swine. Liver, kidney, and muscle residue data were also used in this study. Compartmental models with first-order absorption and elimination were fit to plasma and tissue concentrations using a nonlinear mixed-effect modeling approach. A 3-compartment model with extra tissue compartments was selected to describe the pharmacokinetics of penicillin G. Typical population parameter estimates (interindividual variability) were central volumes of distribution of 3.45 liters (12%) and 3.05 liters (8.8%) and central clearance of 105 liters/h (32%) and 16.9 liters/h (14%) for cattle and swine, respectively, with peripheral clearance of 24.8 liters/h (13%) and 9.65 liters/h (23%) for cattle and 13.7 liters/h (85%) and 0.52 liters/h (40%) for swine. Body weight and age were the covariates in the final pharmacokinetic models. This study established a robust model of penicillin for a large and diverse population of food-producing animals which could be applied to other antibiotics and species in future analyses.
authors.affiliation: Institute of Computational Comparative Medicine, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, USA.
authors.forename: Mengjie
authors.initials: M
authors.lastname: Li
authors.affiliation: Institute of Computational Comparative Medicine, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, USA.
authors.forename: Ronette
authors.initials: R
authors.lastname: Gehring
authors.affiliation: School of Veterinary Medicine, University of California, Davis, California, USA.
authors.forename: Lisa
authors.initials: L
authors.lastname: Tell
authors.affiliation: College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina, USA.
authors.forename: Ronald
authors.initials: R
authors.lastname: Baynes
authors.affiliation: Institute of Computational Comparative Medicine, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, USA.
authors.forename: Qingbiao
authors.initials: Q
authors.lastname: Huang
authors.affiliation: Institute of Computational Comparative Medicine, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, USA jriviere@ksu.edu.
authors.forename: Jim E
authors.initials: JE
authors.lastname: Riviere
mesh_terms: D000367:Age Factors; D000818:Animals; D000900:Anti-Bacterial Agents / Q000097:blood / Q000493:pharmacokinetics*; D001835:Body Weight; D002417:Cattle; D006801:Humans; D007273:Injections, Intramuscular; D007275:Injections, Intravenous; D007668:Kidney / Q000737:chemistry / Q000378:metabolism; D008099:Liver / Q000737:chemistry / Q000378:metabolism; D008460:Meat / Q000032:analysis*; D015233:Models, Statistical; D018482:Muscle, Skeletal / Q000737:chemistry / Q000378:metabolism; D010400:Penicillin G / Q000097:blood / Q000493:pharmacokinetics*; D013045:Species Specificity; D013552:Swine
chemical_list: D000900:Anti-Bacterial Agents; D010400:Penicillin G