Summary:
- The article discusses the critical role of the "human-in-the-loop" approach in AI-driven drug discovery, emphasizing that computational models must be integrated with laboratory validation to ensure biological accuracy.
- It highlights current challenges in artificial intelligence, such as the "black box" nature of deep learning, and advocates for explainable AI to help researchers better understand how molecular candidates are identified for therapeutic development.