Machine learning-driven bioavailability prediction in early-stage drug development: a KNIME-based computational workflow for digital health applications.
Xenobiotica. 2025 May;55(5):339-348. doi: 10.1080/00498254.2025.2508804. Epub 2025 May 28.
Xenobiotica. 2025.
PMID: 40391875
A dataset comprising 475 drug-like compounds characterised by key molecular descriptors was analysed using multiple machine learning models, including Random Forest, Gradient Boosting, Decision Trees, k-Nearest Neighbours, and neural networks. Model performance was assesse …
A dataset comprising 475 drug-like compounds characterised by key molecular descriptors was analysed using multiple machine learning models, …