Conformal ADMET Prediction

Uncertainty estimation on molecular ADMET properties with conformal prediction framework.

Datasets

References

1. Liu, W., Luo, C., Wang, H. & Meng, F. A Benchmarking Dataset with 2440 Organic Molecules for Volume Distribution at Steady State. Preprint at https://doi.org/10.48550/arXiv.2211.05661 (2022).
2. Wang, X.; Liu, M.; Zhang, L.; Wang, Y.; Li, Y.; Lu, T. Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach. J. Chem. Inf. Model. 2020, 60 (10), 4603–4613. https://doi.org/10.1021/acs.jcim.0c00568.
3. Fang, C.; Wang, Y.; Grater, R.; Kapadnis, S.; Black, C.; Trapa, P.; Sciabola, S. Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective. J. Chem. Inf. Model. 2023, 63 (11), 3263–3274. https://doi.org/10.1021/acs.jcim.3c00160.
4. Lunghini, F.; Marcou, G.; Azam, P.; Horvath, D.; Patoux, R.; Van Miert, E.; Varnek, A. Consensus Models to Predict Oral Rat Acute Toxicity and Validation on a Dataset Coming from the Industrial Context. SAR and QSAR in Environmental Research 2019, 30 (12), 879–897. https://doi.org/10.1080/1062936X.2019.1672089.
5. Lou, C.; Yang, H.; Wang, J.; Huang, M.; Li, W.; Liu, G.; Lee, P. W.; Tang, Y. IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method. J. Chem. Inf. Model. 2022, 62 (11), 2788–2799. https://doi.org/10.1021/acs.jcim.2c00297.