News for Healthier Living
AI Maps a Clearer Path to Drug-Target Discovery
 Artificial intelligence is reshaping one of drug discovery's most consequential questions: which compounds interact with which biological targets, and how strongly. A new review maps the fast-moving landscape of artificial intelligence (AI)-driven drug-target interaction (DTI) prediction, showing how the field has progressed from hand-crafted molecular features to deep learning, graph-based models, pretraining and multimodal fusion. The authors organize the review around data foundations, model architectures, benchmark resources and evaluation practices that determine whether predictions are trustworthy. They also argue that future progress will depend less on simply building larger models and more on improving data quality, cross-dataset robustness, mechanistic interpretability and links to experimental testing.
August 20, 2026
August 29 2026August 28 2026August 27 2026August 26 2026August 25 2026August 24 2026August 21 2026August 20 2026August 19 2026August 18 2026August 17 2026August 16 2026August 15 2026
|
|
|
|
|