ADMET-AI Enables Interpretable Predictions of Drug-Induced Cardiotoxicity

Circulation. 2025 Jan 21;151(3):285-287. doi: 10.1161/CIRCULATIONAHA.124.070413. Epub 2025 Jan 21.

Authors

Souhrid Mukherjee^#^{1

2}, Kyle Swanson^#^{3

4

2}, Parker Walther², Rabindra V Shivnaraine^{1

2}, Jeremy Leitz², Paul D Pang^{1

2}, James Zou^#^{3

4}, Joseph C Wu^#^{1

5}

Affiliations

¹ Stanford Cardiovascular Institute (S.M., R.V.S., P.D.P., J.C.W.), Stanford University, CA.
² Greenstone Biosciences, Palo Alto, CA (S.M., K.S., P.W., R.V.S., J.L., P.D.P.).
³ Departments of Computer Science (K.S., J.Z.), Stanford University, CA.
⁴ Biomedical Data Science (K.S., J.Z.), Stanford University, CA.
⁵ Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, CA (J.C.W.).

^# Contributed equally.

PMID: 39836754
PMCID: PMC11996029 (available on 2026-01-21)
DOI: 10.1161/CIRCULATIONAHA.124.070413

No abstract available

Keywords: artificial intelligence; cheminformatics; drug discovery; machine learning.

Publication types

Letter

Grants and funding