What Challenges Exist in AI-Driven Catalysis for Drug Design?
Despite its potential, there are several challenges in integrating AI with catalysis for drug design:
Data Quality: High-quality, comprehensive datasets are crucial for training AI models. Incomplete or biased data can lead to inaccurate predictions. Complexity: Catalytic processes are complex and multifaceted, making it difficult to model them accurately. Interdisciplinary Knowledge: Effective application of AI in this field requires expertise in both chemistry and computer science, which can be a barrier. Scalability: Translating AI predictions from small-scale experiments to industrial-scale production remains a significant hurdle.
