Generation of realistic virtual adult populations using a model-based copula approach
Incorporating realistic sets of patient-associated covariates, i.e., virtual populations, in pharmacometric simulation workflows is essential to obtain realistic model predictions. Current covariate simulation strategies often omit or simplify dependency structures between covariates. Copula models...
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| Published in | Journal of pharmacokinetics and pharmacodynamics Vol. 51; no. 6; pp. 735 - 746 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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New York
Springer US
01.12.2024
Springer Nature B.V |
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| Abstract | Incorporating realistic sets of patient-associated covariates, i.e., virtual populations, in pharmacometric simulation workflows is essential to obtain realistic model predictions. Current covariate simulation strategies often omit or simplify dependency structures between covariates. Copula models are multivariate distribution functions suitable to capture dependency structures between covariates with improved performance compared to standard approaches. We aimed to develop and evaluate a copula model for generation of adult virtual populations for 12 patient-associated covariates commonly used in pharmacometric simulations, using the publicly available NHANES database, including sex, race-ethnicity, body weight, albumin, and several biochemical variables related to organ function. A multivariate (vine) copula was constructed from bivariate relationships in a stepwise fashion. Covariate distributions were well captured for the overall and subgroup populations. Based on the developed copula model, a web application was developed. The developed copula model and associated web application can be used to generate realistic adult virtual populations, ultimately to support model-based clinical trial design or dose optimization strategies. |
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| AbstractList | Incorporating realistic sets of patient-associated covariates, i.e., virtual populations, in pharmacometric simulation workflows is essential to obtain realistic model predictions. Current covariate simulation strategies often omit or simplify dependency structures between covariates. Copula models are multivariate distribution functions suitable to capture dependency structures between covariates with improved performance compared to standard approaches. We aimed to develop and evaluate a copula model for generation of adult virtual populations for 12 patient-associated covariates commonly used in pharmacometric simulations, using the publicly available NHANES database, including sex, race-ethnicity, body weight, albumin, and several biochemical variables related to organ function. A multivariate (vine) copula was constructed from bivariate relationships in a stepwise fashion. Covariate distributions were well captured for the overall and subgroup populations. Based on the developed copula model, a web application was developed. The developed copula model and associated web application can be used to generate realistic adult virtual populations, ultimately to support model-based clinical trial design or dose optimization strategies.Incorporating realistic sets of patient-associated covariates, i.e., virtual populations, in pharmacometric simulation workflows is essential to obtain realistic model predictions. Current covariate simulation strategies often omit or simplify dependency structures between covariates. Copula models are multivariate distribution functions suitable to capture dependency structures between covariates with improved performance compared to standard approaches. We aimed to develop and evaluate a copula model for generation of adult virtual populations for 12 patient-associated covariates commonly used in pharmacometric simulations, using the publicly available NHANES database, including sex, race-ethnicity, body weight, albumin, and several biochemical variables related to organ function. A multivariate (vine) copula was constructed from bivariate relationships in a stepwise fashion. Covariate distributions were well captured for the overall and subgroup populations. Based on the developed copula model, a web application was developed. The developed copula model and associated web application can be used to generate realistic adult virtual populations, ultimately to support model-based clinical trial design or dose optimization strategies. Incorporating realistic sets of patient-associated covariates, i.e., virtual populations, in pharmacometric simulation workflows is essential to obtain realistic model predictions. Current covariate simulation strategies often omit or simplify dependency structures between covariates. Copula models are multivariate distribution functions suitable to capture dependency structures between covariates with improved performance compared to standard approaches. We aimed to develop and evaluate a copula model for generation of adult virtual populations for 12 patient-associated covariates commonly used in pharmacometric simulations, using the publicly available NHANES database, including sex, race-ethnicity, body weight, albumin, and several biochemical variables related to organ function. A multivariate (vine) copula was constructed from bivariate relationships in a stepwise fashion. Covariate distributions were well captured for the overall and subgroup populations. Based on the developed copula model, a web application was developed. The developed copula model and associated web application can be used to generate realistic adult virtual populations, ultimately to support model-based clinical trial design or dose optimization strategies. |
| Author | Guo, Tingjie Knibbe, Catherijne A. J. van Hasselt, J. G. Coen Guo, Yuchen Zwep, Laura B. |
| Author_xml | – sequence: 1 givenname: Yuchen surname: Guo fullname: Guo, Yuchen organization: Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University – sequence: 2 givenname: Tingjie surname: Guo fullname: Guo, Tingjie organization: Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University – sequence: 3 givenname: Catherijne A. J. surname: Knibbe fullname: Knibbe, Catherijne A. J. organization: Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Department of Clinical Pharmacy, St. Antonius Hospital – sequence: 4 givenname: Laura B. surname: Zwep fullname: Zwep, Laura B. organization: Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University – sequence: 5 givenname: J. G. Coen surname: van Hasselt fullname: van Hasselt, J. G. Coen email: coen.vanhasselt@lacdr.leidenuniv.nl organization: Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38844624$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1515/demo-2020-0022 10.48550/arXiv.1703.05203 10.1029/2019WR025103 10.1002/cpt.1746 10.1016/j.jempfin.2014.11.008 10.1007/s13318-022-00766-9 10.2165/00003088-198409030-00001 10.1007/s10928-022-09838-4 10.1146/annurev.pharmtox.44.101802.121453 10.1002/cpt.3099 10.1007/s10928-021-09786-5 10.1146/annurev-statistics-040220-101153 10.1007/s12561-018-09229-9 10.1111/j.1469-8137.1912.tb05611.x 10.1007/BF01113502 10.1016/j.insmatheco.2013.09.009 10.1007/978-981-13-0872-7_15 10.1208/s12248-012-9320-2 10.3141/2262-20 10.1007/s40261-015-0277-7 10.1007/s11095-015-1699-x 10.1515/demo-2017-0007 10.1177/0049124118799381 10.1007/978-3-642-35407-6_2 10.1016/j.insmatheco.2007.02.001 10.1111/j.1365-2125.2006.02615.x 10.3390/pharmaceutics3010053 10.1111/bcp.12907 10.1002/psp4.12613 10.3390/jrfm15030104 10.2133/dmpk.24.53 10.1080/00036846.2016.1240346 10.1002/jcph.2019 10.1002/psp4.12559 10.5194/npg-15-761-2008 10.1007/978-3-030-13785-4 |
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| Keywords | Copula Covariate modeling Virtual population Pharmacometric simulation |
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| Title | Generation of realistic virtual adult populations using a model-based copula approach |
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