1
|
Buddington KK, Pierzynowski SG, Holmes WE, Buddington RK. Selective and Concentrative Enteropancreatic Recirculation of Antibiotics by Pigs. Antibiotics (Basel) 2023; 13:12. [PMID: 38275322 PMCID: PMC10812520 DOI: 10.3390/antibiotics13010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/13/2023] [Accepted: 12/16/2023] [Indexed: 01/27/2024] Open
Abstract
Antibiotics that are efficacious for infectious pancreatitis are present in pancreatic exocrine secretion (PES) after intravenous administration and above minimal inhibitory concentrations. We measured concentrations of four antibiotics by tandem liquid chromatography-mass spectroscopy in plasma and PES after enteral administration to juvenile pigs with jugular catheters and re-entrant pancreatic-duodenal catheters. Nystatin, which is not absorbed by the intestine nor used for infectious pancreatitis (negative control), was not detected in plasma or PES. Concentrations of amoxicillin increased in plasma after administration (p = 0.035), but not in PES (p = 0.51). Metronidazole and enrofloxacin that are used for infectious pancreatitis increased in plasma after enteral administration and even more so in PES, with concentrations in PES averaging 3.1 (±0.5)- and 2.3 (±0.6)-fold higher than in plasma, respectively (p's < 0.001). The increase in enrofloxacin in PES relative to plasma was lower after intramuscular administration (1.8 ± 0.5; p = 0.001). The present results demonstrate the presence of a selective and concentrative enteropancreatic pathway of secretion for some antibiotics. Unlike the regulated secretion of bile, the constitutive secretion of PES and intestinal reabsorption may provide a continuous exposure of pancreas tissue and the small intestine to recirculated antibiotics and potentially other therapeutic molecules. There is a need to better understand the enteropancreatic recirculation of antibiotics and the associated mechanisms.
Collapse
Affiliation(s)
| | - Stefan G. Pierzynowski
- Department of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden;
- Department of Medical Biology, IMW, Jaczewskiego 2, 20-950 Lublin, Poland
| | - William E. Holmes
- Department of Chemical Engineering, University of Louisiana, Lafayette, LA 70503, USA;
| | - Randal K. Buddington
- Department of Health Sciences, University of Memphis, Memphis, TN 38152, USA
- Stonewall Research Facility, LSU Health Sciences, Stonewall, LA 71078, USA
| |
Collapse
|
2
|
Xu B, Yang T, Zhou J, Zheng Y, Wang J, Liu Q, Li D, Zhang Y, Liu M, Wu X. 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. CPT Pharmacometrics Syst Pharmacol 2023; 12:1238-1249. [PMID: 37491812 PMCID: PMC10508574 DOI: 10.1002/psp4.13004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/09/2023] [Accepted: 05/31/2023] [Indexed: 07/27/2023] Open
Abstract
Therapeutic drug monitoring (TDM) of busulfan (BU) is currently performed by plasma sampling in patients undergoing hematopoietic stem cell transplantation (HSCT). Saliva samples are considered a noninvasive TDM matrix. Currently, no salivary population pharmacokinetics (PopPKs) model for BU available. This study aimed to develop a PopPK model that can describe the relationship between plasma and saliva kinetics in patients receiving intravenous BU. The performance of the model in predicting the area under the concentration-time curve at steady state (AUCss ) based on saliva samples is evaluated. Sixty-six patients with HSCT were recruited and administered 0.8 mg/kg BU intravenously. A PopPK model for saliva and plasma was developed using the nonlinear mixed effects model. Bayesian maximum a posteriori (MAP) optimization was used to estimate the model's predictive performance. Plasma and saliva PKs were adequately described with a one-compartment model and a scaled central compartment. Body surface area correlated positively with both clearance and apparent volume of distribution (Vd), whereas alkaline phosphatase correlated negatively with Vd. Simulations demonstrated that the percentage root mean squared prediction error and lower and upper limits of agreements reduced to 10.02% and -16.96% to 22.86% based on five saliva samples. Saliva can be used as an alternative matrix to plasma in TDM of BU. The AUCss can be predicted from saliva concentration by Bayesian MAP optimization, which can be used to design personalized dosing for BU.
Collapse
Affiliation(s)
- Baohua Xu
- Department of PharmacyFujian Medical University Union HospitalFuzhouFujianChina
- School of PharmacyFujian Medical UniversityFuzhouFujianChina
| | - Ting Yang
- Department of HematologyFujian Medical University Union HospitalFuzhouFujianChina
| | - Jianxing Zhou
- Department of PharmacyFujian Medical University Union HospitalFuzhouFujianChina
- School of PharmacyFujian Medical UniversityFuzhouFujianChina
| | - You Zheng
- Department of PharmacyFujian Medical University Union HospitalFuzhouFujianChina
- School of PharmacyFujian Medical UniversityFuzhouFujianChina
| | - Jingting Wang
- College of PharmacyUniversity of MichiganAnn ArborMichiganUSA
| | - Qingxia Liu
- Department of PharmacyFujian Medical University Union HospitalFuzhouFujianChina
- School of PharmacyFujian Medical UniversityFuzhouFujianChina
| | - Dandan Li
- Department of PharmacyFujian Medical University Union HospitalFuzhouFujianChina
- School of PharmacyFujian Medical UniversityFuzhouFujianChina
| | - Yifan Zhang
- Shanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
| | - Maobai Liu
- Department of PharmacyFujian Medical University Union HospitalFuzhouFujianChina
| | - Xuemei Wu
- Department of PharmacyFujian Medical University Union HospitalFuzhouFujianChina
| |
Collapse
|
3
|
Iqbal K, Broeker A, Nowak H, Rahmel T, Nussbaumer-Pröll A, Österreicher Z, Zeitlinger M, Wicha S. 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. Clin Microbiol Infect 2020; 26:1255.e1-1255.e8. [DOI: 10.1016/j.cmi.2020.02.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 01/18/2020] [Accepted: 02/11/2020] [Indexed: 02/07/2023]
|
4
|
Kim HY, Märtson AG, Dreesen E, Spriet I, Wicha SG, McLachlan AJ, Alffenaar JW. Saliva for Precision Dosing of Antifungal Drugs: Saliva Population PK Model for Voriconazole Based on a Systematic Review. Front Pharmacol 2020; 11:894. [PMID: 32595511 PMCID: PMC7304296 DOI: 10.3389/fphar.2020.00894] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 06/01/2020] [Indexed: 12/16/2022] Open
Abstract
Precision dosing for many antifungal drugs is now recommended. Saliva sampling is considered as a non-invasive alternative to plasma sampling for therapeutic drug monitoring (TDM). However, there are currently no clinically validated saliva models available. The aim of this study is firstly, to conduct a systematic review to evaluate the evidence supporting saliva-based TDM for azoles, echinocandins, amphotericin B, and flucytosine. The second aim is to develop a saliva population pharmacokinetic (PK) model for eligible drugs, based on the evidence. Databases were searched up to July 2019 on PubMed® and Embase®, and 14 studies were included in the systematic review for fluconazole, voriconazole, itraconazole, and ketoconazole. No studies were identified for isavuconazole, posaconazole, flucytosine, amphotericin B, caspofungin, micafungin, or anidulafungin. Fluconazole and voriconazole demonstrated a good saliva penetration with an average S/P ratio of 1.21 (± 0.31) for fluconazole and 0.56 (± 0.18) for voriconazole, both with strong correlation (r = 0.89-0.98). Based on the evidence for TDM and available data, population PK analysis was performed on voriconazole using Nonlinear Mixed Effects Modeling (NONMEM 7.4). 137 voriconazole plasma and saliva concentrations from 11 patients (10 adults, 1 child) were obtained from the authors of the included study. Voriconazole pharmacokinetics was best described by one-compartment PK model with first-order absorption, parameterized by clearance of 4.56 L/h (36.9% CV), volume of distribution of 60.7 L, absorption rate constant of 0.858 (fixed), and bioavailability of 0.849. Kinetics of the voriconazole distribution from plasma to saliva was identical to the plasma kinetics, but the extent of distribution was lower, modeled by a scale factor of 0.5 (4% CV). A proportional error model best accounted for the residual variability. The visual and simulation-based model diagnostics confirmed a good predictive performance of the saliva model. The developed saliva model provides a promising framework to facilitate saliva-based precision dosing of voriconazole.
Collapse
Affiliation(s)
- Hannah Yejin Kim
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
- Department of Pharmacy, Westmead Hospital, Westmead, NSW, Australia
- Marie Bashir Institute of Infectious Diseases and Biosecurity, The University of Sydney, Camperdown, NSW, Australia
| | - Anne-Grete Märtson
- University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, Netherlands
| | - Erwin Dreesen
- Department of Pharmaceutical and Pharmacological Sciences, Clinical Pharmacology and Pharmacotherapy, KU Leuven, Leuven, Belgium
| | - Isabel Spriet
- Department of Pharmaceutical and Pharmacological Sciences, Clinical Pharmacology and Pharmacotherapy, KU Leuven, Leuven, Belgium
- Pharmacy Department, University Hospitals Leuven, Leuven, Belgium
| | - Sebastian G. Wicha
- Department of Clinical Pharmacy, Institute of Pharmacy, University of Hamburg, Hamburg, Germany
| | - Andrew J. McLachlan
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Jan-Willem Alffenaar
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
- Department of Pharmacy, Westmead Hospital, Westmead, NSW, Australia
- Marie Bashir Institute of Infectious Diseases and Biosecurity, The University of Sydney, Camperdown, NSW, Australia
| |
Collapse
|