title: Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies.
abstract: OBJECTIVE
  To compare the performance of the standard lag time model (LAG model) with the performance of an analytical solution of the transit compartment model (TRANSIT model) in the evaluation of four pharmacokinetic studies with four different compounds.
  
  
  METHODS
  The population pharmacokinetic analyses were performed using NONMEM on concentration-time data of glibenclamide, furosemide, amiloride, and moxonidine. In the TRANSIT model, the optimal number of transit compartments was estimated from the data. This was based on an analytical solution for the change in drug concentration arising from a series of transit compartments with the same first-order transfer rate between each compartment. Goodness-of-fit was assessed by the decrease in objective function value (OFV) and by inspection of diagnostic graphs.
  
  
  RESULTS
  With the TRANSIT model, the OFV was significantly lower and the goodness-of-fit was markedly improved in the absorption phase compared with the LAG model for all drugs. The parameter estimates related to the absorption differed between the two models while the estimates of the pharmacokinetic disposition parameters were similar.
  
  
  CONCLUSIONS
  Based on these results, the TRANSIT model is an attractive alternative for modeling drug absorption delay, especially when a LAG model poorly describes the drug absorption phase or is numerically unstable.
authors.affiliation: Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, Faculty of Pharmacy, Uppsala University, Uppsala 75234, Sweden. Rada.Savic@farmbio.uu.se
authors.forename: Radojka M
authors.initials: RM
authors.lastname: Savic
authors.forename: Daniël M
authors.initials: DM
authors.lastname: Jonker
authors.forename: Thomas
authors.initials: T
authors.lastname: Kerbusch
authors.forename: Mats O
authors.initials: MO
authors.lastname: Karlsson
mesh_terms: D000042:Absorption; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000584:Amiloride / Q000493:pharmacokinetics; D005260:Female; D005665:Furosemide / Q000493:pharmacokinetics; D005905:Glyburide / Q000493:pharmacokinetics; D006801:Humans; D007093:Imidazoles / Q000493:pharmacokinetics; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D017711:Nonlinear Dynamics; D010599:Pharmacokinetics
chemical_list: D007093:Imidazoles; D000584:Amiloride; D005665:Furosemide; C043482:moxonidine; D005905:Glyburide