Miranda Bastos AC (1,2,3) , Vandecasteele SJ (4), Capron A (5), Tulkens PM (1,3), Spinewine A (2,3), Van Bambeke F (1,3)
(1) Pharmacologie cellulaire et moléculaire, Louvain Drug Research Institute, Université catholique de Louvain, Brussels, Belgium (2) Clinical Pharmacy Research Group, Louvain Drug Research Institute, Université catholique de Louvain, Brussels, Belgium (3) Center for Clinical Pharmacy, Université catholique de Louvain, Brussels, Belgium (4) Department Nephrology and Infectious Diseases, AZ Sint-Jan Brugge-Oostende AV, Bruges, Belgium (5) Department of Clinical Chemistry, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium.
Objectives: TMO is a narrow-spectrum anti-Gram-negative beta-lactam marketed since the ’80s witnessessing renewed interest as a carbapenem-sparing drug, due to resistance to degradation by most β‑lactamases.[1] TMO pharmacokinetics in hemodialysis patients has not been investigated yet. The purpose of this study was to develop a population pharmacokinetic model of TMO in patients with end stage renal disease (ESRD) undergoing haemodialysis, and to evaluate by simulation, the clinical performance of current dosing regimens.
Methods: 12 patients were administered a single dose of 1, 2, or 3g of TMO followed by a interdialytic period (off-dialysis) of 20, 44, or 68h, respectively, and a dialysis period of 4h (total of 39 administrations). 351 serum samples were collected to measure unbound concentrations using a HPLC-MS/MS assay. A population PK model was constructed and evaluated by a bootstrap analysis (internal evaluation, 1000 runs) and by comparison to an external dataset. A 1000-subject Monte Carlo simulation was conducted to determine 95% probability of target attainment (PTA95) versus MIC (based on 40% time above MIC (ƒT > MIC) for measured unbound drug). Data analyses were performed using NONMEM, Pirana, PsN and R.
Results: TMO serum unbound concentrations were best described by a two-compartment model. The apparent total body TMO clearance (off-dialysis), was estimated at 1.35 L/h (bootstrap CI95% 1.084-1.966) (published value for healthy volunteers: 2.4 L/h [2]). An apparent dialysis clearance was implemented in parallel to body clearance to describe the accelerated drug clearance caused by haemodialysis (> 0 during haemodialysis; 0 during the interdialytic period). The relationship between blood flow rate and apparent TMO dialysis clearance was described using the Michaels equation [3]. TMO clearance during dialysis was 8 fold higher than off-dialysis, resulting in significant reduction of TMO serum concentration. The final model successfully predicted the serum TMO concentrations described in an haemodialysis patient unknown to the model. PTA95 was obtained for a MIC < 8mg/L, for a 2g dose (44h interdialytic period).
Conclusions: A two-compartment PK model for TMO in ESRD patients undergoing haemodialysis was developed and demonstrated to be predictive, including during the dialysis period. This model might serve as a useful tool to provide guidance in the optimization of TMO dosing regimens in haemodialysis patients.
References:
[1] Livermore DM, Tulkens PM. Temocillin revived. J Antimicrob Chemother (2009) 63: 243-5.
[2] Overbosch D,van Gulpen C, Mattie H. Renal clearance of temocillin in volunteers. Drugs (1985) 29(Suppl 5): 128-34.
[3] Michaels AS. Operating parameters and performance criteria for hemodialyzers and other membrane-separation devices. Trans Am Soc Artif Intern Organs (1966) 12:387-92.
Reference: PAGE 23 (2014) Abstr 3184 [www.page-meeting.org/?abstract=3184]
Poster: Drug/Disease modeling - Infection