April 9, 2024

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

Key Points

Key points are not available for this paper at this time.

Abstract

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

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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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