A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors

Model‐informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowledge about the individual, in the form of drug level...

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Detalles Bibliográficos
Autores principales: Hughes, Jasmine H., Keizer, Ron J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8520755/
https://www.ncbi.nlm.nih.gov/pubmed/34270885
http://dx.doi.org/10.1002/psp4.12684

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8520755/
https://www.ncbi.nlm.nih.gov/pubmed/34270885
http://dx.doi.org/10.1002/psp4.12684

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