Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/262879 |
Resumo: | Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill. |
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Hanafin, Patrick O.Nation, Roger L.Scheetz, Marc H.Zavascki, Alexandre PrehnSandri, Ana MariaKwa, Andrea L.Cherng, Benjamin P. Z.Kubin, Christine J.Yin, Michael T.Wang, JipingLi, JianKaye, Keith S.Rao, Gauri G.2023-08-01T03:32:59Z20212163-8306http://hdl.handle.net/10183/262879001171536Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill.application/pdfengCPT: pharmacometrics & systems pharmacology. New York. Vol. 10 (2021), p. 1525–1537PrognósticoFarmacocinéticaCuidados críticosPolimixina BAssessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patientsEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001171536.pdf.txt001171536.pdf.txtExtracted Texttext/plain59198http://www.lume.ufrgs.br/bitstream/10183/262879/2/001171536.pdf.txtd05c8136e2a64203a363020b29dc0da6MD52ORIGINAL001171536.pdfTexto completo (inglês)application/pdf596130http://www.lume.ufrgs.br/bitstream/10183/262879/1/001171536.pdf9270f0642b4fbece928ba46cec06fdabMD5110183/2628792023-08-02 03:31:35.103498oai:www.lume.ufrgs.br:10183/262879Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-08-02T06:31:35Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients |
title |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients |
spellingShingle |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients Hanafin, Patrick O. Prognóstico Farmacocinética Cuidados críticos Polimixina B |
title_short |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients |
title_full |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients |
title_fullStr |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients |
title_full_unstemmed |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients |
title_sort |
Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients |
author |
Hanafin, Patrick O. |
author_facet |
Hanafin, Patrick O. Nation, Roger L. Scheetz, Marc H. Zavascki, Alexandre Prehn Sandri, Ana Maria Kwa, Andrea L. Cherng, Benjamin P. Z. Kubin, Christine J. Yin, Michael T. Wang, Jiping Li, Jian Kaye, Keith S. Rao, Gauri G. |
author_role |
author |
author2 |
Nation, Roger L. Scheetz, Marc H. Zavascki, Alexandre Prehn Sandri, Ana Maria Kwa, Andrea L. Cherng, Benjamin P. Z. Kubin, Christine J. Yin, Michael T. Wang, Jiping Li, Jian Kaye, Keith S. Rao, Gauri G. |
author2_role |
author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Hanafin, Patrick O. Nation, Roger L. Scheetz, Marc H. Zavascki, Alexandre Prehn Sandri, Ana Maria Kwa, Andrea L. Cherng, Benjamin P. Z. Kubin, Christine J. Yin, Michael T. Wang, Jiping Li, Jian Kaye, Keith S. Rao, Gauri G. |
dc.subject.por.fl_str_mv |
Prognóstico Farmacocinética Cuidados críticos Polimixina B |
topic |
Prognóstico Farmacocinética Cuidados críticos Polimixina B |
description |
Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021 |
dc.date.accessioned.fl_str_mv |
2023-08-01T03:32:59Z |
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Estrangeiro info:eu-repo/semantics/article |
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001171536 |
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eng |
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dc.relation.ispartof.pt_BR.fl_str_mv |
CPT: pharmacometrics & systems pharmacology. New York. Vol. 10 (2021), p. 1525–1537 |
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