Synergizing artificial intelligence and operations research for advancements in biomanufacturing

Area of Science:

• Biotechnology
• Process Engineering
• Data Science

Background:

• Biomanufacturing faces complex operational challenges impacting efficiency and safety.
• Artificial intelligence (AI) provides predictive analytics, while operations research (OR) offers prescriptive solutions.
• Integrating AI and OR can yield structured, interpretable, and verifiable solutions.

Purpose of the Study:

• To explore the synergistic potential of AI and OR in biomanufacturing.
• To highlight successful university-industry collaborations in AI-OR implementation.
• To propose a strategic roadmap for AI-OR integration.

Main Methods:

• Review of current AI and OR methodologies in biomanufacturing.
• Analysis of case studies from university-industry partnerships.
• Development of a conceptual framework for AI-OR integration.

Main Results:

• AI and OR offer complementary strengths for optimizing biomanufacturing processes.
• Successful partnerships demonstrate tangible benefits in efficiency, safety, and innovation.
• A clear need exists for structured integration strategies.

Conclusions:

• The synergy of AI and OR is crucial for advancing biomanufacturing.
• Strategic roadmaps and collaborative efforts are essential for realizing AI-OR potential.
• Future biomanufacturing will likely leverage integrated AI-OR frameworks for enhanced performance.