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Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling

Moxifloxacin has an important role in the treatment of tuberculosis (TB). Unfortunately, coadministration with the cornerstone TB drug rifampicin results in suboptimal plasma exposure. We aimed to gain insight into the moxifloxacin pharmacokinetics and the interaction with rifampicin. Moreover, we p...

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Autores principales: Litjens, Carlijn H. C., Verscheijden, Laurens F. M., Bolwerk, Celine, Greupink, Rick, Koenderink, Jan B., van den Broek, Petra H. H., van den Heuvel, Jeroen J. M. W., Svensson, Elin M., Boeree, Martin J., Magis‐Escurra, Cecile, Hoefsloot, Wouter, van Crevel, Reinout, van Laarhoven, Arjan, van Ingen, Jakko, Kuipers, Saskia, Ruslami, Rovina, Burger, David M., Russel, Frans G. M., Aarnoutse, Rob E., te Brake, Lindsey H. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297990/
https://www.ncbi.nlm.nih.gov/pubmed/34554580
http://dx.doi.org/10.1002/jcph.1972
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author Litjens, Carlijn H. C.
Verscheijden, Laurens F. M.
Bolwerk, Celine
Greupink, Rick
Koenderink, Jan B.
van den Broek, Petra H. H.
van den Heuvel, Jeroen J. M. W.
Svensson, Elin M.
Boeree, Martin J.
Magis‐Escurra, Cecile
Hoefsloot, Wouter
van Crevel, Reinout
van Laarhoven, Arjan
van Ingen, Jakko
Kuipers, Saskia
Ruslami, Rovina
Burger, David M.
Russel, Frans G. M.
Aarnoutse, Rob E.
te Brake, Lindsey H. M.
author_facet Litjens, Carlijn H. C.
Verscheijden, Laurens F. M.
Bolwerk, Celine
Greupink, Rick
Koenderink, Jan B.
van den Broek, Petra H. H.
van den Heuvel, Jeroen J. M. W.
Svensson, Elin M.
Boeree, Martin J.
Magis‐Escurra, Cecile
Hoefsloot, Wouter
van Crevel, Reinout
van Laarhoven, Arjan
van Ingen, Jakko
Kuipers, Saskia
Ruslami, Rovina
Burger, David M.
Russel, Frans G. M.
Aarnoutse, Rob E.
te Brake, Lindsey H. M.
author_sort Litjens, Carlijn H. C.
collection PubMed
description Moxifloxacin has an important role in the treatment of tuberculosis (TB). Unfortunately, coadministration with the cornerstone TB drug rifampicin results in suboptimal plasma exposure. We aimed to gain insight into the moxifloxacin pharmacokinetics and the interaction with rifampicin. Moreover, we provided a mechanistic framework to understand moxifloxacin pharmacokinetics. We developed a physiologically based pharmacokinetic model in Simcyp version 19, with available and newly generated in vitro and in vivo data, to estimate pharmacokinetic parameters of moxifloxacin alone and when administered with rifampicin. By combining these strategies, we illustrate that the role of P‐glycoprotein in moxifloxacin transport is limited and implicate MRP2 as transporter of moxifloxacin‐glucuronide followed by rapid hydrolysis in the gut. Simulations of multiple dose area under the plasma concentration–time curve (AUC) of moxifloxacin (400 mg once daily) with and without rifampicin (600 mg once daily) were in accordance with clinically observed data (predicted/observed [P/O] ratio of 0.87 and 0.80, respectively). Importantly, increasing the moxifloxacin dose to 600 mg restored the plasma exposure both in actual patients with TB as well as in our simulations. Furthermore, we extrapolated the single dose model to pediatric populations (P/O AUC ratios, 1.04‐1.52) and the multiple dose model to children with TB (P/O AUC ratio, 1.51). In conclusion, our combined approach resulted in new insights into moxifloxacin pharmacokinetics and accurate simulations of moxifloxacin exposure with and without rifampicin. Finally, various knowledge gaps were identified, which may be considered as avenues for further physiologically based pharmacokinetic refinement.
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spelling pubmed-92979902022-07-21 Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling Litjens, Carlijn H. C. Verscheijden, Laurens F. M. Bolwerk, Celine Greupink, Rick Koenderink, Jan B. van den Broek, Petra H. H. van den Heuvel, Jeroen J. M. W. Svensson, Elin M. Boeree, Martin J. Magis‐Escurra, Cecile Hoefsloot, Wouter van Crevel, Reinout van Laarhoven, Arjan van Ingen, Jakko Kuipers, Saskia Ruslami, Rovina Burger, David M. Russel, Frans G. M. Aarnoutse, Rob E. te Brake, Lindsey H. M. J Clin Pharmacol Physiologically Based Pharmacokinetic Modeling Moxifloxacin has an important role in the treatment of tuberculosis (TB). Unfortunately, coadministration with the cornerstone TB drug rifampicin results in suboptimal plasma exposure. We aimed to gain insight into the moxifloxacin pharmacokinetics and the interaction with rifampicin. Moreover, we provided a mechanistic framework to understand moxifloxacin pharmacokinetics. We developed a physiologically based pharmacokinetic model in Simcyp version 19, with available and newly generated in vitro and in vivo data, to estimate pharmacokinetic parameters of moxifloxacin alone and when administered with rifampicin. By combining these strategies, we illustrate that the role of P‐glycoprotein in moxifloxacin transport is limited and implicate MRP2 as transporter of moxifloxacin‐glucuronide followed by rapid hydrolysis in the gut. Simulations of multiple dose area under the plasma concentration–time curve (AUC) of moxifloxacin (400 mg once daily) with and without rifampicin (600 mg once daily) were in accordance with clinically observed data (predicted/observed [P/O] ratio of 0.87 and 0.80, respectively). Importantly, increasing the moxifloxacin dose to 600 mg restored the plasma exposure both in actual patients with TB as well as in our simulations. Furthermore, we extrapolated the single dose model to pediatric populations (P/O AUC ratios, 1.04‐1.52) and the multiple dose model to children with TB (P/O AUC ratio, 1.51). In conclusion, our combined approach resulted in new insights into moxifloxacin pharmacokinetics and accurate simulations of moxifloxacin exposure with and without rifampicin. Finally, various knowledge gaps were identified, which may be considered as avenues for further physiologically based pharmacokinetic refinement. John Wiley and Sons Inc. 2021-10-25 2022-03 /pmc/articles/PMC9297990/ /pubmed/34554580 http://dx.doi.org/10.1002/jcph.1972 Text en © 2021 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Physiologically Based Pharmacokinetic Modeling
Litjens, Carlijn H. C.
Verscheijden, Laurens F. M.
Bolwerk, Celine
Greupink, Rick
Koenderink, Jan B.
van den Broek, Petra H. H.
van den Heuvel, Jeroen J. M. W.
Svensson, Elin M.
Boeree, Martin J.
Magis‐Escurra, Cecile
Hoefsloot, Wouter
van Crevel, Reinout
van Laarhoven, Arjan
van Ingen, Jakko
Kuipers, Saskia
Ruslami, Rovina
Burger, David M.
Russel, Frans G. M.
Aarnoutse, Rob E.
te Brake, Lindsey H. M.
Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling
title Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling
title_full Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling
title_fullStr Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling
title_full_unstemmed Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling
title_short Prediction of Moxifloxacin Concentrations in Tuberculosis Patient Populations by Physiologically Based Pharmacokinetic Modeling
title_sort prediction of moxifloxacin concentrations in tuberculosis patient populations by physiologically based pharmacokinetic modeling
topic Physiologically Based Pharmacokinetic Modeling
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297990/
https://www.ncbi.nlm.nih.gov/pubmed/34554580
http://dx.doi.org/10.1002/jcph.1972
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