G Time (h) 2 4 10 12 npde 2 1 0 -1 -2 8 6 Normalized prediction distribution error (npde) diagnostic plots for unbound TMO: Population pharmacokinetic modelling of total and unbound temocillin in the plasma of healthy volunteers after intravenous administration Perrin Ngougni Pokem 1 , Peter Matzneller 2 , Beatrix Wulkersdorfer 2 , Arnaud Capron 3 , Laure Elens 4 , Pierre Wallemacq 3 , Paul M Tulkens 1 , Markus Zeitlinger 2 , Françoise Van Bambeke 1 1 Pharmacologie cellulaire et moléculaire, Louvain Drug Research Institute, Université catholique de Louvain, Brussels, Belgium; 2 Department of Clinical Pharmacology, Medical University of Vienna, Austria; 3 Clinical Chemistry Department, Cliniques Universitaires St. Luc, Université catholique de Louvain, Brussels, Belgium ; 4 Integrated PharmacoMetrics, PharmacoGenomics and PhamacoKinetics, Université catholique de Louvain, Brussels, Belgium; Temocillin (TMO) is a β-lactam antibiotic active on Gram (-) bacteria (except most isolates of Pseudomonas aeruginosa [1]), including strains producing extended-spectrum β-lactamases (ESBL) and some carbapenemases [2-3]. It is therefore a useful alternative to carbapenems and is indicated for the treatment of complicated urinary tract infections (including pyelonephritis), low respiratory infections, bacteremia, and wound infections [4]. Temocillin is eliminated unchanged by glomerular filtration. It is highly protein bound (up to 85% [4]) and only the unbound concentration is considered as potentially active. The aim of this phase I study was to develop a joined Population-based (Pop)PK model of total and unbound TMO plasma concentrations in healthy volunteers. Subsequently, this model was used to test different dosing regimens aiming at a 90% probability of target attainment (PTA), i.e. unbound concentrations at least 40% of the dosing interval above the minimal inhibitory concentration (40%ƒT >MIC ) of susceptible organisms [5]. A copy of this poster will be made available after the meeting at http://www.facm.ucl.ac.be/posters.htm Background and Aims Mailing address: Françoise Van Bambeke av. Mounier 73 B1.73.05; 1200 Brussels - Belgium [email protected] Materials & Methods Single-center, open-label, non-randomized study. 8 male healthy volunteers received a single dose of 2 g of TMO as IV infusion over 40 minutes. Plasma samples were collected from 40 min to 12h after the end of infusion. Plasma concentrations were determined by HPLC-MS/MS for total (sample preparation including protein precipitation with methanol) and unbound (sample preparation including ultrafiltration with Amicon filter Ultra-15 device; NMWL 30K; Merck Millipore Ltd) TMO [6]. The PopPK model of total and unbound plasma concentrations were fitted using a non-parametric approach with Pmetrics software version1.4.1 (LAPKB, Los Angeles, CA, USA.). One- and two- compartmental PK models were tested for total TMO plasma concentrations; the model that best described the data was selected to derive the TMO unbound concentrations. Final model selection was based on the Bayesian information criterion (BIC), goodness-of-fit plots, normalized prediction error (npde) distribution and visual predictive check (VPC). 1000 Monte Carlo simulations per subject receiving TMO 2g q12h 1 and 2g q8h 2 were performed using the final PopPK model. The total and unbound concentrations of TMO were estimated and the 5 th , 50 th and 95 th percentiles compared to the observed concentrations. PTA (fT > MIC of 40%) were then computed with 2 different dosing regimens (2g/12h 1 or 2g/8h²) assuming either a mean free fraction of 6.0 ± 1.4% or of 13.0 ± 4.0% being the values observed for total concentrations < 150 mg/L or > 150 mg/L, respectively (see results). 1 conventional dose, ² dose registered for severe infections. TMO shows a bi-compartmental pharmacokinetics. TMO protein binding is high but saturable, with unbound concentrations ranging from 3 to 20% of total concentrations within the limits of the total concentrations observed in volunteers. PTA is low for conventional dosage, arguing for the use of more frequent administrations and/or continuous infusion. Current licensed dosage regimen is suboptimal for MICs > 8 mg/L based on PK in healthy volunteers, due to high protein binding in this population. Further studies are needed to evaluate the PK of unbound TMO in target patients’ populations. Discussion and Conclusions References 1. Chalhoub et al; Sci Rep. 2017;7:40208. PMID: 28091521 2. Livermore. J Antimicrob Chemother. 2006;57:1012-4. PMID: 16531428 3. Livermore, Tulkens. J Antimicrob Chemother. 2009; 63:243-5. PMID: 19095679 4. Belgian SmPC, last revision 05/2017; Eumedica ( data on file ) 5. Glupczynski et al. Eur J Clin Microbiol Infect Dis. 2007; 26:777-83. PMID: 17668253 6. Ngougni Pokem et al. Clin Biochem. 2015;48:542-5. PMID: 25712752 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 Simulated total TMO profile Simulated free TMO profile 0.95 0.5 0.05 Observed total concentration Observed free concentration Time (h) Total and free TMO concentrations (mg/L) 0.4 0.6 0.8 1.0 0.2 0.00 0.25 0.5 1 2 4 32 8 16 64 PTA Target concentrations (mg/L) ------- 2g/8h 2g/12h Target concentrations (mg/L) 0.4 0.6 0.8 1.0 0.2 0.00 0.25 0.5 1 2 4 32 8 16 64 PTA ------- 2g/8h 2g/12h Results 0 50 100 150 200 250 300 350 0 50 100 150 200 250 300 350 R 2 = 87.60% (p<0.0001) Slope = 0.98 (95% CI = 0.90 to 1.07) Inter = -10.20 (95% CI = -20.90 to 0.63) Bias = 4.11 Imprecision = 23.9 Total TMO concentrations predicted (mg/L) Total TMO concentrations observed (mg/L) 0 50 100 150 200 250 300 350 0 50 100 150 200 250 300 350 R 2 = 99.30% (p<0.0001) Slope = 1.01 (95% CI = 0.98 to 1.03) Inter = -0.17 (95% CI = -2.45 to 2.11) Bias = 0.02 Imprecision = 1.18 Total TMO concentrations predicted (mg/L) Total TMO concentrations observed (mg/L) A B Linear regression of individual observed versus predicted total TMO concentrations using (A) the median model PK parameter values and (B) the median of the individual Bayesian posterior parameter distributions. The black dashed lines and the open black circles represent the unity lines and the individual total concentrations, respectively. 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 R 2 = 86.50% (p<0.0001) Slope = 0.46 (95% CI = 0.42 to 0.50) Inter = 1.50 (95% CI = 0.43 to 2.57) Bias = 9.48 Imprecision = 59.00 Unbound TMO concentrations predicted (mg/L) Unbound TMO concentrations observed (mg/L) 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 R 2 = 99.% (p<0.0001) Slope = 1.02 (95% CI = 1.00 to 1.04) Inter = -0.10 (95% CI = -0.36 to 0.20) Bias = -0.07 Imprecision = 0.87 Unbound TMO concentrations predicted (mg/L) Unbound TMO concentrations observed (mg/L) Linear regression of Individual observed versus predicted unbound TMO concentrations using (C) the median model PK parameter values and (D) the median of the individual Bayesian posterior parameter distributions. The black dashed lines and the open red circles represent the unity lines and the individual unbound concentrations, respectively. D C Bi-compartmental model with linear elimination best fitted total and unbound TMO concentrations. Equation output of final model: Y(1) = X(1)/V; Y(2) = Y(1)*Km/(Ymax-Y(1)); Y(1) and Y(2) (total and unbound TMO concentrations respectively), X; TMO dose V (apparent volume of distribution) Vc C Rate IV ke=kei*(GFR/135) kes KCP KPC Vp P o IV: Intravenous o C; P: Central; Peripheral compartment o Vc; Vp: Volume of the compartment o KCP; KPC : Transfer rate o Kd: unbound TMO concentration corresponding to half of the maximal binding capacity o Ymax: maximal binding capacity o ke: Elimination constant o kei: typical value of ke; kes: parameter estimated by the model representing the effect of the GFR on the typical kei value. o Glomerular filtration rate (GFR) o 135: mean value of the GFR of study pop. Plasma unbound concentration Kd Ymax Q-Q plot (E), Histogram with expected normal distributions indicated by the dashed lines (mean) and light blue boxes (CI 95% ranges) (F), npde with respect to post-intake time (G), and to predicted total TMO concentrations (H) with individual observations (blue dots), observed 5, 50, 95 th percentiles (blue and red lines), predicted percentiles (dashed black lines) and CI 95% (blue and red ribbons). Q-Q plot (I), Histogram with expected normal distributions indicated by the dashed lines (mean) and light blue boxes (CI 95% ranges) (J), npde with respect to post- intake time (K), and predicted unbound TMO concentrations (L) with individual observations (blue dot), observed 5, 50, 95 th percentiles (blue and red lines), predicted percentiles (dashed black lines) and CI 95% (blue and red ribbons). Theoretical quantiles Sample quantiles (npde) Q-Q plot versus N(0,1) for npde -3 3 -2 -1 0 1 2 -3 3 -2 -1 0 1 2 I M N PTA plots for standard dosing (2g/12h) versus higher dosing (2g/8h) considering as target fT > MIC during 40% of the time, based (M) on a mean unbound fraction of 6.0 ± 1.4% (mean of values observed for total concentration < 150mg/L), (N) on a mean unbound fraction of 13.0 ± 4.0% (mean of values observed for total concentration > 150mg/L). The probability of reaching a target of 8 mg/L depends on TMO protein binding for both dosing options. VPC of simulated (5 th , 50 th and 95 th percentiles) of total (solid black lines) and unbound TMO concentrations (solid red lines) represented vs time. The individual values of observed concentrations are shown as black (total) or red (unbound) circles. Less than 5 % of observed concentrations are outside the 5 th and 95 th percentiles of simulated concentrations. Pharmacokinetic parameters of the final model. Parameters Mean SD CV% Median kei (h -1 ) 0.24 0.06 26.68 0.22 kes 0.18 0.13 76.94 0.14 KCP 0.35 0.21 60.93 0.25 KPC 0.57 0.23 41.20 0.54 V (L) 7.70 1.78 23.21 7.61 Ymax (mg/L) 346.55 132.2 38.14 314.94 Kd (mg/L) 14.63 9.60 65.59 12.11 kei (typical value of ke) and kes (parameter estimated by the model representing the effect of the GFR on the typical kei value), KCP and KPC (transfer rate between the compartments), V (apparent volume of distribution), Ymax (maximal binding capacity), Kd (free TMO concentration corresponding to half maximal binding), SD (standard deviation), CV (coefficient of variation). Schematic overview of the mechanism based final PK model for TMO in healthy volunteers Probability of target attainment (PTA) Plasma free fraction vs total TMO concentrations 0 50 100 150 200 250 0 5 10 15 20 25 HV1 HV2 HV3 HV4 HV5 HV6 HV7 HV8 Total TMO concentrations (mg/L) Unbound fraction (%) Mean: 6% Mean: 13% Goodness-of-fit plot for total temocillin (TMO): Goodness-of-fit plot for unbound temocillin (TMO): E Theoretical quantiles Sample quantiles (npde) Q-Q plot versus N(0,1) for npde -3 3 -2 -1 0 1 2 -3 3 -2 -1 0 1 2 F Sample quantiles (npde) 0 5 10 15 20 Frequency -2 -1 0 1 2 H Predicted total concentrations (mg/L) 50 100 150 200 npde 2 1 0 -1 -2 J Sample quantiles (npde) 0 5 10 15 20 Frequency -2 -1 0 1 2 L Predicted unbound concentrations (mg/L) 10 20 30 40 npde 2 1 0 -1 -2 0 K Time (h) 2 4 12 npde 2 1 0 -1 -2 8 6 10 Normalized prediction distribution error (npde) diagnostic plots for total TMO: Visual predictive check (VPC): P 2220 Plasma bound concentration Covariate: GFR was retained as covariate in the final model ( -2LL = 138). Error model: Polynomial error and proportional error (Gamma factor). SD total = 0.19*Y(1) + 1.17*Y(1) 2 SD unbound = 0.0018 + 0.24*Y(2) + 0.11*Y(2) 2 Gamma error factor for the final model was 0.32. SD (standard deviation). Final model converged after 1171 cycles This study was approved by the ethical committee of the Medizinische Universität Wien (Eudra CT 2015-003457-18) Acknowledgments The present work was performed without specific financial support. P.N.P., L.E., P.W. are employees of the Université catholique de Louvain, F.V.B. is Research Director of the Belgian Fonds de la Recherche Scientifique, P.M.T. is emeritus professor and unpaid collaborator.