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October 7, 2025Open Access

Auto-ADMET: An Effective and Interpretable AutoML Method for Chemical ADMET Property Prediction

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Auto-ADMET demonstrates improved predictive performance for ADMET properties in chemical compounds, suggesting a novel use of AutoML.

Auto-ADMET achieves better predictive performance on chemical ADMET properties compared to existing models.
In tests on 12 benchmark datasets, Auto-ADMET outperformed standard GGP, pkCSM, and XGBOOST methods.
The use of a Bayesian Network in the evolutionary process enhances both search efficiency and result interpretation.
This method addresses challenges in model personalization and generalization in the chemical space.

Sá et al. (2025) studied this question.

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