Prediction of the Extent of Blood–Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model
The developed random forest QSPR model for K<sub>p,uu,BBB</sub> prediction was found to have adequate performance, and can support drug discovery and development of novel investigational drugs targeting the CNS in conjunction with CNS PBPK modeling.
Authors
- Elizabeth C. M. de Lange (ORCID: https://orcid.org/0000-0001-8303-1117)
- Berfin Gülave (ORCID: https://orcid.org/0000-0001-8954-882X)
- J. G. Coen van Hasselt (ORCID: https://orcid.org/0000-0002-1664-7314)
- Helle W. van den Maagdenberg (ORCID: https://orcid.org/0000-0002-9718-7806)
- Gerard J. P. van Westen (ORCID: https://orcid.org/0000-0003-0717-1817)
- Luke van Boven
Institutions
- Leiden University (NL)
- Centre for Human Drug Research (NL)
Publication Details
- Journal
- Pharmaceutical Research
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1007/s11095-025-03828-0
- Citations
- 3
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 4.51