Recent advances in AI-based toxicity prediction for drug discovery
Toxicity, defined as the potential harm a substance can cause to living organisms, requires the implementation of stringent regulatory standards to ensure public safety. These standards involve comprehensive testing frameworks, including hazard identification, dose-response evaluation, exposure asse...
Saved in:
| Main Authors: | Hyundo Lee, Jisan Kim, Ji-Woon Kim, Yoonji Lee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
|
| Series: | Frontiers in Chemistry |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fchem.2025.1632046/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
NaCTR: Natural product-derived compound-based drug discovery pipeline from traditional oriental medicine by search space reduction
by: Seunghwan Jung, et al.
Published: (2024-12-01) -
Editorial: Multi-target drug discovery and design for complex health disorders
by: Farid A. Badria, et al.
Published: (2025-06-01) -
druglikeFilter 1.0: An AI powered filter for collectively measuring the drug-likeness of compounds
by: Minjie Mou, et al.
Published: (2025-06-01) -
GSFM: A genome-scale functional module transformation to represent drug efficacy for in silico drug discovery
by: Saisai Tian, et al.
Published: (2025-01-01) -
Application of 3D atom pair map in an attention model for enhanced drug virtual screening
by: Gina Ryu, et al.
Published: (2025-05-01)