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A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

PURPOSE: Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human bra...

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Autores principales: Yamamoto, Yumi, Välitalo, Pyry A., van den Berg, Dirk-Jan, Hartman, Robin, van den Brink, Willem, Wong, Yin Cheong, Huntjens, Dymphy R., Proost, Johannes H., Vermeulen, An, Krauwinkel, Walter, Bakshi, Suruchi, Aranzana-Climent, Vincent, Marchand, Sandrine, Dahyot-Fizelier, Claire, Couet, William, Danhof, Meindert, van Hasselt, Johan G. C., de Lange, Elizabeth C. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5236087/
https://www.ncbi.nlm.nih.gov/pubmed/27864744
http://dx.doi.org/10.1007/s11095-016-2065-3
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author Yamamoto, Yumi
Välitalo, Pyry A.
van den Berg, Dirk-Jan
Hartman, Robin
van den Brink, Willem
Wong, Yin Cheong
Huntjens, Dymphy R.
Proost, Johannes H.
Vermeulen, An
Krauwinkel, Walter
Bakshi, Suruchi
Aranzana-Climent, Vincent
Marchand, Sandrine
Dahyot-Fizelier, Claire
Couet, William
Danhof, Meindert
van Hasselt, Johan G. C.
de Lange, Elizabeth C. M.
author_facet Yamamoto, Yumi
Välitalo, Pyry A.
van den Berg, Dirk-Jan
Hartman, Robin
van den Brink, Willem
Wong, Yin Cheong
Huntjens, Dymphy R.
Proost, Johannes H.
Vermeulen, An
Krauwinkel, Walter
Bakshi, Suruchi
Aranzana-Climent, Vincent
Marchand, Sandrine
Dahyot-Fizelier, Claire
Couet, William
Danhof, Meindert
van Hasselt, Johan G. C.
de Lange, Elizabeth C. M.
author_sort Yamamoto, Yumi
collection PubMed
description PURPOSE: Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human brain disposition. METHODS: A mathematical model consisting of several physiological brain compartments in the rat was developed using rich concentration-time profiles from nine structurally diverse drugs in plasma, brain extracellular fluid, and two cerebrospinal fluid compartments. The effect of active drug transporters was also accounted for. Subsequently, the model was translated to predict human concentration-time profiles for acetaminophen and morphine, by scaling or replacing system- and drug-specific parameters in the model. RESULTS: A common model structure was identified that adequately described the rat pharmacokinetic profiles for each of the nine drugs across brain compartments, with good precision of structural model parameters (relative standard error <37.5%). The model predicted the human concentration-time profiles in different brain compartments well (symmetric mean absolute percentage error <90%). CONCLUSIONS: A multi-compartmental brain pharmacokinetic model was developed and its structure could adequately describe data across nine different drugs. The model could be successfully translated to predict human brain concentrations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11095-016-2065-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-52360872017-01-25 A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations Yamamoto, Yumi Välitalo, Pyry A. van den Berg, Dirk-Jan Hartman, Robin van den Brink, Willem Wong, Yin Cheong Huntjens, Dymphy R. Proost, Johannes H. Vermeulen, An Krauwinkel, Walter Bakshi, Suruchi Aranzana-Climent, Vincent Marchand, Sandrine Dahyot-Fizelier, Claire Couet, William Danhof, Meindert van Hasselt, Johan G. C. de Lange, Elizabeth C. M. Pharm Res Research Paper PURPOSE: Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human brain disposition. METHODS: A mathematical model consisting of several physiological brain compartments in the rat was developed using rich concentration-time profiles from nine structurally diverse drugs in plasma, brain extracellular fluid, and two cerebrospinal fluid compartments. The effect of active drug transporters was also accounted for. Subsequently, the model was translated to predict human concentration-time profiles for acetaminophen and morphine, by scaling or replacing system- and drug-specific parameters in the model. RESULTS: A common model structure was identified that adequately described the rat pharmacokinetic profiles for each of the nine drugs across brain compartments, with good precision of structural model parameters (relative standard error <37.5%). The model predicted the human concentration-time profiles in different brain compartments well (symmetric mean absolute percentage error <90%). CONCLUSIONS: A multi-compartmental brain pharmacokinetic model was developed and its structure could adequately describe data across nine different drugs. The model could be successfully translated to predict human brain concentrations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11095-016-2065-3) contains supplementary material, which is available to authorized users. Springer US 2016-11-18 2017 /pmc/articles/PMC5236087/ /pubmed/27864744 http://dx.doi.org/10.1007/s11095-016-2065-3 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research Paper
Yamamoto, Yumi
Välitalo, Pyry A.
van den Berg, Dirk-Jan
Hartman, Robin
van den Brink, Willem
Wong, Yin Cheong
Huntjens, Dymphy R.
Proost, Johannes H.
Vermeulen, An
Krauwinkel, Walter
Bakshi, Suruchi
Aranzana-Climent, Vincent
Marchand, Sandrine
Dahyot-Fizelier, Claire
Couet, William
Danhof, Meindert
van Hasselt, Johan G. C.
de Lange, Elizabeth C. M.
A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations
title A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations
title_full A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations
title_fullStr A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations
title_full_unstemmed A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations
title_short A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations
title_sort generic multi-compartmental cns distribution model structure for 9 drugs allows prediction of human brain target site concentrations
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5236087/
https://www.ncbi.nlm.nih.gov/pubmed/27864744
http://dx.doi.org/10.1007/s11095-016-2065-3
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