Is Moxifloxacin a Treatment Option for Pancreatic Infections? A Pharmacometric Analysis of Serum and Pancreatic Juice

Abstract

Postoperative local infection is a major complication after pancreatic surgery. The aim of this prospective clinical trial was to assess the potential of moxifloxacin (MXF) to treat pancreatic infections from a pharmacokinetic (PK)/pharmacodynamic (PD) perspective. The PK of MXF in serum and pancreatic juice, via an inserted tube in the pancreatic duct, was determined in 19 patients up to day 7 after pancreatoduodenectomy. PK data in both specimens was analyzed with NONMEM 7.3. Intraoperative swipes were performed for microbiological examination. PK/PD target attainment was assessed in both matrices using unbound area under the plasma concentration–time curve/minimum inhibitory concentration (MIC) targets of ≥30 and ≥100, for gram‐positive and gram‐negative pathogens, respectively. A 2‐compartment population PK model in which the measurements in pancreatic juice were assigned to a scaled peripheral compartment best described the PK in both specimens simultaneously. Median (10th–90th percentile) area under the plasma concentration–time curve values after the third dose were 28.9 mg · h/L (18.6–42.0) in serum and 55.8 mg · h/L (23.7–81.4) in pancreatic juice. Target attainment rate for the intraoperatively isolated bacterial strains was ≥0.88 after the third MXF dose. For gram‐negatives, high probability of target attainment ≥0.84 was observed in serum for MIC ≤ 0.125 mg/L and in pancreatic juice for MIC ≤ 0.25 mg/L. For gram‐positives, the probability of target attainment was 0.84–1 in serum for MIC ≤ 0.5 mg/L and in pancreatic juice for MIC ≤ 1 mg/L. In conclusion, penetration of MXF into pancreatic juice was substantial. The PK/PD analysis indicated that treatment of pancreatic infections by isolates with MIC ≤ 0.25 mg/L (gram‐negative) and ≤1 mg/L (gram‐positive) should be evaluated in further studies.

A pharmacometric approach to define target site-specific breakpoints for bacterial killing and resistance suppression integrating microdialysis, time–kill curves and heteroresistance data: a case study with moxifloxacin

“…Using a mechanism-based PK modelling approach for microdialysis, it was possible to separate the methodological and clinical variability of MXF PK in the target sites plasma, muscle and skin tissue [11]. Typical MXF PK and variability in plasma identified in the present population of patients with sepsis was similar to those in patients without sepsis [21,22]. Moreover, a minimal PBPK approach [10] was adapted for modelling of microdialysis data and provided additional insight into the distribution pattern of MXF.…”

“…The hybrid PBPK approach outlined herein unifies strategies to model the unbound tissue concentrations using microdialysis data. While commonly the target site PK is assigned to scaled central [26], scaled peripheral [22], or separate empirical compartments [27,28], the PBPK approach not only provides mechanistic insight but is also as flexible as empirical approaches due to the estimation of the bloodflow correction factor and the partition coefficient. Nevertheless, application of the hybrid PBPK approach to further microdialysis studies is warranted to systematically elucidate the distribution pattern to target site tissues.…”

Saliva as a noninvasive sampling matrix for therapeutic drug monitoring of intravenous busulfan in Chinese patients undergoing hematopoietic stem cell transplantation: A prospective population pharmacokinetic and simulation study

“…Different error models (additive, proportional, or additive‐proportional) were tested to account for residual variability. After identifying a suitable model for plasma BU concentration, saliva measurements were added to the model by testing either a separate saliva compartment or a “scale” parameter assigned to the plasma compartment 27 . Separate error models accounted for residual variability of the BU concentrations in saliva.…”

Saliva for Precision Dosing of Antifungal Drugs: Saliva Population PK Model for Voriconazole Based on a Systematic Review.

“…Subsequently, saliva drug concentration-time data were added to the stable plasma model, by testing either a separate saliva compartment or a "scale" parameter assigned to the plasma compartment (Wicha et al, 2019). Separate error models were used to account for residual variability of the saliva drug concentrations.…”