Cargando…

Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example

BACKGROUND AND OBJECTIVES: We propose a strategy for studying ethnopharmacology by conducting sequential physiologically based pharmacokinetic (PBPK) prediction (a ‘bottom-up’ approach) and population pharmacokinetic (popPK) confirmation (a ‘top-down’ approach), or in reverse order, depending on whe...

Descripción completa

Detalles Bibliográficos
Autores principales: Feng, Sheng, Shi, Jun, Parrott, Neil, Hu, Pei, Weber, Cornelia, Martin-Facklam, Meret, Saito, Tomohisa, Peck, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4916198/
https://www.ncbi.nlm.nih.gov/pubmed/26715215
http://dx.doi.org/10.1007/s40262-015-0356-1
_version_ 1782438786928476160
author Feng, Sheng
Shi, Jun
Parrott, Neil
Hu, Pei
Weber, Cornelia
Martin-Facklam, Meret
Saito, Tomohisa
Peck, Richard
author_facet Feng, Sheng
Shi, Jun
Parrott, Neil
Hu, Pei
Weber, Cornelia
Martin-Facklam, Meret
Saito, Tomohisa
Peck, Richard
author_sort Feng, Sheng
collection PubMed
description BACKGROUND AND OBJECTIVES: We propose a strategy for studying ethnopharmacology by conducting sequential physiologically based pharmacokinetic (PBPK) prediction (a ‘bottom-up’ approach) and population pharmacokinetic (popPK) confirmation (a ‘top-down’ approach), or in reverse order, depending on whether the purpose is ethnic effect assessment for a new molecular entity under development or a tool for ethnic sensitivity prediction for a given pathway. The strategy is exemplified with bitopertin. METHODS: A PBPK model was built using Simcyp(®) to simulate the pharmacokinetics of bitopertin and to predict the ethnic sensitivity in clearance, given pharmacokinetic data in just one ethnicity. Subsequently, a popPK model was built using NONMEM(®) to assess the effect of ethnicity on clearance, using human data from multiple ethnic groups. A comparison was made to confirm the PBPK-based ethnic sensitivity prediction, using the results of the popPK analysis. RESULTS: PBPK modelling predicted that the bitopertin geometric mean clearance values after 20 mg oral administration in Caucasians would be 1.32-fold and 1.27-fold higher than the values in Chinese and Japanese, respectively. The ratios of typical clearance in Caucasians to the values in Chinese and Japanese estimated by popPK analysis were 1.20 and 1.17, respectively. The popPK analysis results were similar to the PBPK modelling results. CONCLUSION: As a general framework, we propose that PBPK modelling should be considered to predict ethnic sensitivity of pharmacokinetics prior to any human data and/or with data in only one ethnicity. In some cases, this will be sufficient to guide initial dose selection in different ethnicities. After clinical trials in different ethnicities, popPK analysis can be used to confirm ethnic differences and to support dose justification and labelling. PBPK modelling prediction and popPK analysis confirmation can complement each other to assess ethnic differences in pharmacokinetics at different drug development stages. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40262-015-0356-1) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4916198
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-49161982016-07-06 Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example Feng, Sheng Shi, Jun Parrott, Neil Hu, Pei Weber, Cornelia Martin-Facklam, Meret Saito, Tomohisa Peck, Richard Clin Pharmacokinet Original Research Article BACKGROUND AND OBJECTIVES: We propose a strategy for studying ethnopharmacology by conducting sequential physiologically based pharmacokinetic (PBPK) prediction (a ‘bottom-up’ approach) and population pharmacokinetic (popPK) confirmation (a ‘top-down’ approach), or in reverse order, depending on whether the purpose is ethnic effect assessment for a new molecular entity under development or a tool for ethnic sensitivity prediction for a given pathway. The strategy is exemplified with bitopertin. METHODS: A PBPK model was built using Simcyp(®) to simulate the pharmacokinetics of bitopertin and to predict the ethnic sensitivity in clearance, given pharmacokinetic data in just one ethnicity. Subsequently, a popPK model was built using NONMEM(®) to assess the effect of ethnicity on clearance, using human data from multiple ethnic groups. A comparison was made to confirm the PBPK-based ethnic sensitivity prediction, using the results of the popPK analysis. RESULTS: PBPK modelling predicted that the bitopertin geometric mean clearance values after 20 mg oral administration in Caucasians would be 1.32-fold and 1.27-fold higher than the values in Chinese and Japanese, respectively. The ratios of typical clearance in Caucasians to the values in Chinese and Japanese estimated by popPK analysis were 1.20 and 1.17, respectively. The popPK analysis results were similar to the PBPK modelling results. CONCLUSION: As a general framework, we propose that PBPK modelling should be considered to predict ethnic sensitivity of pharmacokinetics prior to any human data and/or with data in only one ethnicity. In some cases, this will be sufficient to guide initial dose selection in different ethnicities. After clinical trials in different ethnicities, popPK analysis can be used to confirm ethnic differences and to support dose justification and labelling. PBPK modelling prediction and popPK analysis confirmation can complement each other to assess ethnic differences in pharmacokinetics at different drug development stages. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40262-015-0356-1) contains supplementary material, which is available to authorized users. Springer International Publishing 2015-12-29 2016 /pmc/articles/PMC4916198/ /pubmed/26715215 http://dx.doi.org/10.1007/s40262-015-0356-1 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial 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 Original Research Article
Feng, Sheng
Shi, Jun
Parrott, Neil
Hu, Pei
Weber, Cornelia
Martin-Facklam, Meret
Saito, Tomohisa
Peck, Richard
Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example
title Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example
title_full Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example
title_fullStr Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example
title_full_unstemmed Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example
title_short Combining ‘Bottom-Up’ and ‘Top-Down’ Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example
title_sort combining ‘bottom-up’ and ‘top-down’ methods to assess ethnic difference in clearance: bitopertin as an example
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4916198/
https://www.ncbi.nlm.nih.gov/pubmed/26715215
http://dx.doi.org/10.1007/s40262-015-0356-1
work_keys_str_mv AT fengsheng combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample
AT shijun combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample
AT parrottneil combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample
AT hupei combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample
AT webercornelia combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample
AT martinfacklammeret combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample
AT saitotomohisa combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample
AT peckrichard combiningbottomupandtopdownmethodstoassessethnicdifferenceinclearancebitopertinasanexample