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Daptomycin Physiology-Based Pharmacokinetic Modeling to Predict Drug Exposure and Pharmacodynamics in Skin and Bone Tissues

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Abstract

Background and Objective

Daptomycin has been recommended in the treatment of bone and joint infection. Previous work showed that the approved dosage of daptomycin may be insufficient to achieve optimal exposure in patients with bone and joint infection. However, those studies assumed that bone exposure was similar to steady-state daptomycin-free plasma concentrations. We sought to establish a physiologically based pharmacokinetic (PBPK) model of daptomycin to describe the dynamics of daptomycin disposition in bone and skin tissue.

Methods

A PBPK model of daptomycin was built using PK-Sim®. Daptomycin concentrations in plasma and bone were obtained from three previously published studies. Physicochemical drug characteristics, mass balance, anthropometrics, and experimental data were used to build and refine the PBPK model. Internal validation of the PBPK model was performed using the usual diagnostic plots. The final PBPK model was then used to run simulations with doses of 6, 8, 10, and 12 mg/kg/24 h. Pharmacokinetic profiles were simulated in 1000 subjects and the probabilities of target attainment for the area under the concentration–time curve over the bacterial minimum inhibitory concentration were computed in blood, skin, and bone compartments.

Results

The final model showed a good fit of all datasets with an absolute average fold error between 0.5 and 2 for all pharmacokinetic quantities in blood, skin and bone tissues. Results of dosing simulations showed that doses ≥10 mg/kg should be used in the case of bacteremia caused by Staphylococcus aureus with a minimum inhibitory concentration >0.5 mg/L or Enterococcus faecalis with a minimum inhibitory concentration >1 mg/L, while doses ≥12 mg/kg should be used in the case of bone and joint infection or complicated skin infection. When considering a lower minimum inhibitory concentration, doses of 6–8 mg/kg would likely achieve a sufficient success rate. However, in the case of infections caused by E. faecalis with a minimum inhibitory concentration >2 mg/L, a higher dosage and combination therapy would be necessary to maximize efficacy.

Conclusions

We developed the first daptomycin PBPK/pharmacodynamic model for bone and joint infection, which confirmed that a higher daptomycin dosage is needed to optimize exposure in bone tissue. However, such higher dosages raise safety concerns. In this setting, therapeutic drug monitoring and model-informed precision dosing appear necessary to ensure the right exposure on an individual basis.

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Acknowledgements

We gratefully acknowledge Dr. Friederike Traunmüller for sharing daptomycin PK data. Lyon Bone and Joint Study Group (list of collaborators). Coordinator: Tristan Ferry; infectious diseases specialists: Tristan Ferry, Florent Valour, Thomas Perpoint, Patrick Miailhes, Florence Ader, Sandrine Roux, Agathe Becker, Claire Triffault-Fillit, Anne Conrad, Cécile Pouderoux, Nicolas Benech, Pierre Chauvelot, Marielle Perry, Fatiha Daoud, Johanna Lippman, Evelyne Braun, Christian Chidiac; surgeons: Elvire Servien, Cécile Batailler, Stanislas Gunst, Axel Schmidt, Matthieu Malatray, Elliot Sappey-Marinier, Michel-Henry Fessy, Anthony Viste, Jean-Luc Besse, Philippe Chaudier, Lucie Louboutin, Quentin Ode, Adrien Van Haecke, Marcelle Mercier, Vincent Belgaid, Arnaud Walch, Sébastien Martres, Franck Trouillet, Cédric Barrey, Ali Mojallal, Sophie Brosset, Camille Hanriat, Hélène Person, Nicolas Sigaux, Philippe Céruse, Carine Fuchsmann; Anesthesiologists – Frédéric Aubrun, Mikhail Dziadzko, Caroline Macabéo; Microbiologists – Frederic Laurent, Laetitia Beraud, Tiphaine Roussel-Gaillard, Céline Dupieux, Camille Kolenda, Jérôme Josse; Pathology—Marie Brevet, Alexis Trecourt; Imaging—Fabien Craighero, Loic Boussel, Jean-Baptiste Pialat, Isabelle Morelec; PK/PD specialists—Michel Tod, Marie-Claude Gagnieu, Sylvain Goutelle; Clinical research assistant and database manager– Eugénie Mabrut

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Authors and Affiliations

  1. Service Pharmaceutique, Hospices Civils de Lyon, Groupement Hospitalier Nord, Hôpital Pierre Garraud, 136 rue du Commandant Charcot, 69005, Lyon, France

    Romain Garreau, Laurent Bourguignon & Sylvain Goutelle

  2. UMR CNRS 5558, Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, Villeurbanne, France

    Romain Garreau, Laurent Bourguignon & Sylvain Goutelle

  3. Laboratoire de Pharmacologie Clinique et Toxicologie, Plateforme PACE, Centre Hospitalier Universitaire de Besançon, Besançon, France

    Damien Montange

  4. EA 3920, Marqueurs Pronostiques et Facteurs de Régulations des Pathologies Cardiaques et Vasculaires-SFR FED 4234, Université de Franche Comté, Besançon, France

    Damien Montange

  5. Institut de Bactériologie, Hôpitaux Universitaires, Strasbourg, France

    Antoine Grillon & François Jehl

  6. Service des Maladies Infectieuses et Tropicales, Centre Interrégional de Référence Pour la Prise en Charge des Infections Ostéo-Articulaires Complexes (CRIOAc Lyon), Hospices Civils de Lyon, Groupement Hospitalier Nord, Hôpital de la Croix-Rousse, Lyon, France

    Tristan Ferry

  7. ISPB, Facultés de Médecine et de Pharmacie de Lyon, Université Lyon 1, Lyon, France

    Tristan Ferry, Laurent Bourguignon & Sylvain Goutelle

  8. CIRI-Centre International de Recherche en Infectiologie, Inserm, U1111, Université́ Claude Bernard Lyon 1, CNRS, UMR5308, Ecole Normale Supérieure de Lyon, Lyon, France

    Tristan Ferry

Authors
  1. Romain Garreau
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  2. Damien Montange
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  3. Antoine Grillon
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  4. François Jehl
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  5. Tristan Ferry
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  6. Laurent Bourguignon
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  7. Sylvain Goutelle
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Corresponding author

Correspondence to Romain Garreau.

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Funding

This study was carried out as part of our routine work, which is funded by Hospices Civils de Lyon and the University of Lyon.

Conflicts of interest/competing interests

Romain Garreau, Damien Montange, Antoine Grillon, François Jehl, Tristan Ferry, Laurent Bourguignon, and Sylvain Goutelle have no conflicts of interest that are directly relevant to the content of this article.

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All patient gave they consent to participate in the original study.

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All patient gave they consent for publication in the original study.

Availability of data and material

Data analyzed in this study were previously published in different studies. They were shared by Friederick Traunmüller, Damien Montange, François Jehl, and Antoine Grillon. Those authors can be contacted for data availability.

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Author contributions

All authors contributed to the study conception and design. Data collection was performed by RG, DM, and AG. Data preparation and analysis were performed by RG. The first draft of the manuscript was written by RG. and all authors contributed to manuscript revisions with significant intellectual input. All authors read and approved the final manuscript.

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Garreau, R., Montange, D., Grillon, A. et al. Daptomycin Physiology-Based Pharmacokinetic Modeling to Predict Drug Exposure and Pharmacodynamics in Skin and Bone Tissues. Clin Pharmacokinet 61, 1443–1456 (2022). https://doi.org/10.1007/s40262-022-01168-5

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