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Looking forward, our immediate applications for the next 6 months include expanding to all drug-metabolizing CYPs including CYP1A2, CYP2C9, and CYP2E1, integrating molecular dynamics for conformational flexibility, and developing a real-time drug screening platform for pharmaceutical companies. Our long-term vision for 2-3 years encompasses personalized drug metabolism prediction based on individual genetic variants, AI-guided drug design using structural insights, and regulatory AI tools for FDA and EMA drug approval processes. The scientific contributions of this work are substantial - this is the first structure-aware RAG system for drug metabolism prediction, achieving 35.9% performance improvement over existing methods, providing quantitative structural analysis for medicinal chemistry, and offering a scalable architecture applicable to other enzyme families. The key conference takeaway is that our system bridges the gap between AI language models and structural biology, enabling unprecedented precision in drug metabolism prediction. This represents a new paradigm for AI-driven pharmaceutical research. |
IEEE/ICACT20260263 Slide.23
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