A machine learning approach to population pharmacokinetic modelling automation
Abstract Background Population pharmacokinetic (PopPK) models are crucial for understanding drug behaviour across populations, yet traditional development is often labour-intensive and slow. This study demonstrates an automated, out-of-the-box approach for popPK model development, leveraging optimis...
Saved in:
| Main Authors: | Sam Richardson, Itziar Irurzun Arana, Andrzej Nowojewski, Diansong Zhou, Jacob Leander, Weifeng Tang, Richard Dearden, Megan Gibbs |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-025-01054-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Population pharmacokinetics
by: Milovanović Jasmina R., et al.
Published: (2005-01-01) -
Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations
by: Diego Valderrama, et al.
Published: (2025-04-01) -
An automated classification pipeline for tables in pharmacokinetic literature
by: Victoria C. Smith, et al.
Published: (2025-03-01) -
Machine learning and population pharmacokinetics: a hybrid approach for optimizing vancomycin therapy in sepsis patients
by: Keyu Chen, et al.
Published: (2025-05-01) -
Influential predictors of azithromycin pharmacokinetics: a systematic review of population pharmacokinetics
by: Janthima Methaneethorn, et al.
Published: (2025-12-01)