Guiva Annane 1,2, Benoît Crevier 3, Anis Ouyahia 3, Sabrina Larocque 2, Britanny Bernard 2, Justine Brasseur-Masse 2, Juliette Fournier 2, Amélie Marsot 1,2,4
1 Laboratoire STP2, Faculté de Pharmacie, Université de Montréal (Montreal, Canada), 2 Faculté de Pharmacie, Université de Montréal (Montreal, Canada), 3 CISSS de la Montérégie-Centre, Hôpital Charles-Le Moyne (Greenfield Park, Canada), 4 CHU Sainte-Justine (Montreal, Canada)
Introduction/Objectives: Over the past decades, the prevalence of obesity has risen at an alarming rate worldwide [1]. Obesity is commonly defined as a body mass index (BMI) ≥ 30 kg/m², a measure of excess body fat and the presence of signs and symptoms of organ dysfunction [2]. It is a complex condition that induces profound physiological alterations, including changes in body composition, cardiac output, regional blood flow, protein binding, and renal function [3, 4]. These modifications can significantly affect drug pharmacokinetics (PK) and pharmacodynamics (PD) [5]. In addition to its association with chronic diseases, obesity is linked to an increased risk of infection [6]. The combination of altered immune responses and PK variability makes antimicrobial therapy particularly challenging in this population [5, 6]. Piperacillin-tazobactam is a widely used broad-spectrum β-lactam antibiotic and its efficacy is primarily driven by the time which free concentrations remain above the minimum inhibitory concentration (fT>MIC) [7]. Achieving adequate exposure can be particularly difficult in patients with obesity due to altered PK. This study aims to develop a population pharmacokinetic (popPK) model to characterize the PK of piperacillin-tazobactam and to evaluate the adequacy of current dosing strategies in obese adults.
Methods: An open-label, randomized, controlled feasibility study was conducted from March 2025 to August 2025 in Hospital Charles-Le Moyne (HCLM), Greenfield Park, QC, Canada. Adult patients of body mass index (BMI) ≥ 30 kg/m² treated with piperacillin-tazobactam for 24 hours or more in HCLM were eligible. Exclusion criteria included allergy to penicillins, renal replacement therapy, pregnancy, seizure/epilepsy history or having already had a prolonged or continuous infusion of piperacillin-tazobactam. Eligible patients were randomly assigned to either the standard (30 min) or prolonged (50% of dosing interval) infusion groups. One sample per patient was collected 24 hours after the first dose of the intervention and piperacillin concentrations were assessed by a validated ultra-high performance liquid chromatography with diode array detection method. An external evaluation was initially performed on models developed in obese and critically ill patients, however the models failed to adequately predict the population’s concentrations. PopPK model development and analysis were performed using NONMEM®, Pirana® and RStudio®. Due to limited data, prior information from a previously developed model was used to assist the current model’s development [8].
Results: Forty-five patients (22 women, 23 men) with a mean ± SD BMI and weight of 37.1 ± 7.35 kg/m² and 100.60 ± 18.08 kg, respectively were recruited. Thirty-four through piperacillin concentrations were available with 18 in the standard group and 16 in the prolonged group, the data was best described by a one compartment model with linear elimination, and first order elimination estimation with interaction was used to estimate this model’s parameters. Glomerular filtration rate (GFR) and albumin were the most influential covariates included in the model on clearance (CL). CL and volume of distribution were both estimated at 14 L/h and 31.3 L, respectively.
Conclusions: Considering the high inter-individual variability found in obese patients, dose individualization and therapeutic drug monitoring becomes critical. The use of the PRIOR subroutine represents a valuable strategy when working with sparse datasets. By integrating prior knowledge, model stability can be improved allowing adequate parameter estimation despite limited data.
References:
1. World Health Organization. Obesity and overweight. In: Fact sheets. World Health Organization. 2025. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight. Accessed 17 Feb 2026.
2. Rubino F, Cummings DE, Eckel RH, Cohen RV, Wilding JPH, Brown WA, et al. Definition and diagnostic criteria of clinical obesity. Lancet Diabetes Endocrinol. 2025;13(3):221-62.
3. Janic M, Janez A, El-Tanani M, Rizzo M. Obesity: Recent Advances and Future Perspectives. Biomedicines. 2025;13(2):368.
4. Field AE, Coakley EH, Must A, Spadano JL, Laird N, Dietz WH, et al. Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Intern Med. 2001;161(13):1581-6.
5. Gouju J, Legeay S. Pharmacokinetics of obese adults: Not only an increase in weight. Biomed Pharmacother. 2023;166:115281.
6. van Rhee KP, Knibbe CAJ, van der Linden PD, Bruggemann RJM. Patients with Obesity Should be Recognised as a Special Patient Population During Drug Development of Antibacterial and Antifungal Agents; A Call to Action. Clin Pharmacokinet. 2024;63(1):1-12.
7. Wenker SAM, Alabdulkarim N, Readman JB, Slob EMA, Satta G, Ali S, et al. Defining the pharmacokinetic/pharmacodynamic index of piperacillin/tazobactam within a hollow-fibre infection model to determine target attainment in intensive care patients. JAC Antimicrob Resist. 2024;6(2):dlae036.
8. Chung EK, Cheatham SC, Fleming MR, Healy DP, Shea KM, Kays MB. Population pharmacokinetics and pharmacodynamics of piperacillin and tazobactam administered by prolonged infusion in obese and nonobese patients. J Clin Pharmacol. 2015;55(8):899-908.
Reference: PAGE 34 (2026) Abstr 12233 [www.page-meeting.org/?abstract=12233]
Poster: Drug/Disease Modelling - Infection