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Seeger J, Guenther S, Schaufler K, Heiden SE, Michelet R, Kloft C. Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure-Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli. Antibiotics (Basel) 2021; 10:antibiotics10060615. [PMID: 34063980 PMCID: PMC8224043 DOI: 10.3390/antibiotics10060615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 05/17/2021] [Accepted: 05/18/2021] [Indexed: 11/30/2022] Open
Abstract
Minimal inhibitory concentration-based pharmacokinetic/pharmacodynamic (PK/PD) indices are commonly applied to antibiotic dosing optimisation, but their informative value is limited, as they do not account for bacterial growth dynamics over time. We aimed to comprehensively characterise the exposure–effect relationship of levofloxacin against Escherichia coli and quantify strain-specific characteristics applying novel PK/PD parameters. In vitro infection model experiments were leveraged to explore the exposure–effect relationship of three clinical Escherichia coli isolates, harbouring different genomic fluoroquinolone resistance mechanisms, under constant levofloxacin concentrations or human concentration–time profiles (≤76 h). As an exposure metric, the ‘cumulative area under the levofloxacin–concentration time curve’ was determined. The antibiotic effect was assessed as the ‘cumulative area between the growth control and the bacterial-killing and -regrowth curve’. PK/PD modelling was applied to characterise the exposure–effect relationship and derive novel PK/PD parameters. A sigmoidal Emax model with an inhibition term best characterised the exposure–effect relationship and allowed for discrimination between two isolates sharing the same MIC value. Strain- and exposure-pattern-dependent differences were captured by the PK/PD parameters and elucidated the contribution of phenotypic adaptation to bacterial regrowth. The novel exposure and effect metrics and derived PK/PD parameters allowed for comprehensive characterisation of the isolates and could be applied to overcome the limitations of the MIC in clinical antibiotic dosing decisions, drug research and preclinical development.
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Affiliation(s)
- Johanna Seeger
- Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Kelchstr. 31, 12169 Berlin, Germany; (J.S.); (R.M.)
| | - Sebastian Guenther
- Department of Pharmaceutical Biology, Institute of Pharmacy, Universitaet Greifswald, Friedrich-Ludwig-Jahn-Straße 17, 17489 Greifswald, Germany;
| | - Katharina Schaufler
- Department of Pharmaceutical Microbiology, Institute of Pharmacy, Universitaet Greifswald, Friedrich-Ludwig-Jahn-Straße 17, 17489 Greifswald, Germany; (K.S.); (S.E.H.)
| | - Stefan E. Heiden
- Department of Pharmaceutical Microbiology, Institute of Pharmacy, Universitaet Greifswald, Friedrich-Ludwig-Jahn-Straße 17, 17489 Greifswald, Germany; (K.S.); (S.E.H.)
| | - Robin Michelet
- Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Kelchstr. 31, 12169 Berlin, Germany; (J.S.); (R.M.)
| | - Charlotte Kloft
- Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Kelchstr. 31, 12169 Berlin, Germany; (J.S.); (R.M.)
- Correspondence: ; Tel.: +49-30-838-50656
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Michelet R, Ursino M, Boulet S, Franck S, Casilag F, Baldry M, Rolff J, van Dyk M, Wicha SG, Sirard JC, Comets E, Zohar S, Kloft C. The Use of Translational Modelling and Simulation to Develop Immunomodulatory Therapy as an Adjunct to Antibiotic Treatment in the Context of Pneumonia. Pharmaceutics 2021; 13:601. [PMID: 33922017 PMCID: PMC8143524 DOI: 10.3390/pharmaceutics13050601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 04/16/2021] [Accepted: 04/20/2021] [Indexed: 11/16/2022] Open
Abstract
The treatment of respiratory tract infections is threatened by the emergence of bacterial resistance. Immunomodulatory drugs, which enhance airway innate immune defenses, may improve therapeutic outcome. In this concept paper, we aim to highlight the utility of pharmacometrics and Bayesian inference in the development of immunomodulatory therapeutic agents as an adjunct to antibiotics in the context of pneumonia. For this, two case studies of translational modelling and simulation frameworks are introduced for these types of drugs up to clinical use. First, we evaluate the pharmacokinetic/pharmacodynamic relationship of an experimental combination of amoxicillin and a TLR4 agonist, monophosphoryl lipid A, by developing a pharmacometric model accounting for interaction and potential translation to humans. Capitalizing on this knowledge and associating clinical trial extrapolation and statistical modelling approaches, we then investigate the TLR5 agonist flagellin. The resulting workflow combines expert and prior knowledge on the compound with the in vitro and in vivo data generated during exploratory studies in order to construct high-dimensional models considering the pharmacokinetics and pharmacodynamics of the compound. This workflow can be used to refine preclinical experiments, estimate the best doses for human studies, and create an adaptive knowledge-based design for the next phases of clinical development.
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Affiliation(s)
- Robin Michelet
- Department of Clinical Pharmacy & Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, 12169 Berlin, Germany; (S.F.); (C.K.)
| | - Moreno Ursino
- Unit of Clinical Epidemiology, Assistance Publique-Hôpitaux de Paris, CHU Robert Debré, Université de Paris, Sorbonne Paris-Cité, Inserm U1123 and CIC-EC 1426, F-75019 Paris, France;
- INSERM, Centre de Recherche des Cordeliers, Sorbonne Université, Université de Paris, F-75006 Paris, France; (S.B.); (S.Z.)
| | - Sandrine Boulet
- INSERM, Centre de Recherche des Cordeliers, Sorbonne Université, Université de Paris, F-75006 Paris, France; (S.B.); (S.Z.)
- HeKA, Inria, F-75006 Paris, France
| | - Sebastian Franck
- Department of Clinical Pharmacy & Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, 12169 Berlin, Germany; (S.F.); (C.K.)
- Department of Clinical Pharmacy, Institute of Pharmacy, University of Hamburg, 20146 Hamburg, Germany;
| | - Fiordiligie Casilag
- CNRS, Inserm, CHU Lille, Institute Pasteur de Lille, U1019-UMR9017-CIIL-Centre for Infection and Immunity of Lille, Université de Lille, F-59000 Lille, France; (F.C.); (M.B.); (J.-C.S.)
| | - Mara Baldry
- CNRS, Inserm, CHU Lille, Institute Pasteur de Lille, U1019-UMR9017-CIIL-Centre for Infection and Immunity of Lille, Université de Lille, F-59000 Lille, France; (F.C.); (M.B.); (J.-C.S.)
| | - Jens Rolff
- Department of Evolutionary Biology, Institute of Biology, Freie Universitaet Berlin, 14195 Berlin, Germany;
| | - Madelé van Dyk
- Flinders Centre for Innovation in Cancer, College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia;
| | - Sebastian G. Wicha
- Department of Clinical Pharmacy, Institute of Pharmacy, University of Hamburg, 20146 Hamburg, Germany;
| | - Jean-Claude Sirard
- CNRS, Inserm, CHU Lille, Institute Pasteur de Lille, U1019-UMR9017-CIIL-Centre for Infection and Immunity of Lille, Université de Lille, F-59000 Lille, France; (F.C.); (M.B.); (J.-C.S.)
| | - Emmanuelle Comets
- INSERM, University Rennes-1, CIC 1414, F-35000 Rennes, France;
- INSERM, IAME, Université de Paris, F-75006 Paris, France
| | - Sarah Zohar
- INSERM, Centre de Recherche des Cordeliers, Sorbonne Université, Université de Paris, F-75006 Paris, France; (S.B.); (S.Z.)
- HeKA, Inria, F-75006 Paris, France
| | - Charlotte Kloft
- Department of Clinical Pharmacy & Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, 12169 Berlin, Germany; (S.F.); (C.K.)
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