4.7 Article

Translational in vitro and in vivo PKPD modelling for apramycin against Gram-negative lung pathogens to facilitate prediction of human efficacious dose in pneumonia

Journal

CLINICAL MICROBIOLOGY AND INFECTION
Volume 28, Issue 10, Pages 1367-1374

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.cmi.2022.05.003

Keywords

Apramycin; Modelling; Pharmacodynamics; Pharmacokinetics; Pharmacometrics; Preclinical; Translational

Funding

  1. Innovative Medicines Initiative Joint Undertaking [115583]
  2. European Union
  3. National Institute of Allergy and Infectious Diseases (NIAID) at the National Institutes of Health (NIH) [HHSN272201700020I 75N93020F00159, HHSN272201700020I 75N93019F00131]
  4. National Institute of Allergy and Infectious Diseases (NIAID) at the National Institutes of Health (NIH) (Pharmacology Discovery Services Taiwan, a Eurofins Discovery Partner Lab)
  5. Swedish Research Council [201803296]
  6. European Federation of Pharmaceutical Industries and Associations (EFPIA)
  7. Polish Ministry of Science and Higher Education [W187/IMI/2014]

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This study characterized the preclinical pharmacokinetics (PK) and pharmacodynamics of the drug candidate apramycin in fighting carbapenem-resistant gram-negative pathogens. A mathematical model was developed to predict human efficacy based on in vitro and in vivo data. Apramycin showed good lung penetration and the mathematical model integrated lung PK to drive mouse PK and pharmacodynamics. Apramycin was demonstrated as a candidate for treatment of carbapenem-resistant gram-negative pneumonia.
Objectives: New drugs and methods to efficiently fight carbapenem-resistant gram-negative pathogens are sorely needed. In this study, we characterized the preclinical pharmacokinetics (PK) and pharmacodynamics of the clinical stage drug candidate apramycin in time kill and mouse lung infection models. Based on in vitro and in vivo data, we developed a mathematical model to predict human efficacy. Methods: Three pneumonia-inducing gram-negative species Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae were studied. Bactericidal kinetics were evaluated with time-kill curves; in vivo PK were studied in healthy and infected mice, with sampling in plasma and epithelial lining fluid after subcutaneous administration; in vivo efficacy was measured in a neutropenic mouse pneumonia model. A pharmacokinetic-pharmacodynamic model, integrating all the data, was developed and simulations were performed. Results: Good lung penetration of apramycin in epithelial lining fluid (ELF) was shown (area under the curve (AUC)(ELF)/ALI(Cplasma) = 88%). Plasma clearance was 48% lower in lung infected mice compared to healthy mice. For two out of five strains studied, a delay in growth (similar to 5 h) was observed in vivo but not in vitro. The mathematical model enabled integration of lung PK to drive mouse PK and pharmacodynamics. Simulations predicted that 30 mg/kg of apramycin once daily would result in bacteriostasis in patients. Discussion: Apramycin is a candidate for treatment of carbapenem-resistant gram-negative pneumonia as demonstrated in an integrated modeling framework for three bacterial species. We show that mathematical modelling is a useful tool for simultaneous inclusion of multiple data sources, notably plasma and lung in vivo PK and simulation of expected scenarios in a clinical setting, notably lung infections. (C) 2022 The Author(s). Published by Elsevier Ltd on behalf of European Society of Clinical Microbiology and Infectious Diseases.

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