April 9, 2024

Leveraging Machine Learning and Quantum Mechanics for Blood Brain Barrier Permeability Prediction of Drug Molecules (S27.010)

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Resumen

In this study, we utilize various machine learning, deep learning, and transfer learning methods to predict the blood-brain barrier (BBB) permeability of public drug datasets.

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Cite This Study

Lim et al. (Tue,) studied this question.

synapsesocial.com/papers/68e6fdadb6db643587677cdf https://doi.org/https://doi.org/10.1212/wnl.0000000000206708

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Prediction of blood‐brain barrier permeability using machine learning approaches based on various molecular representation2024 · 7 citations
2Decoding the Blood-Brain Barrier: Innovative and Scalable Open-Source Machine Learning Model for Drug Permeability2026
3Predicting Blood–Brain Barrier Permeability from Experimental Data: An Interpretable and Externally Validated Machine Learning Framework2026
4Manifold Embedding of Quantum Information as Molecule Representation to Predict Blood-Brain Barrier Permeability by Deep Learning2025
5DL_BBBP: blood-brain barrier permeability prediction based on molecular property using deep learning2024

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