Sustainable biofabrication: from bioprinting to AI-driven predictive methods

Area of Science:

• Biotechnology and Sustainable Manufacturing

Background:

• Biofabrication offers a sustainable manufacturing approach for bio-hybrid systems.
• Current biofabrication methods are often labor-intensive and energy-inefficient.
• Bio-hybrid systems have potential applications in diverse fields like tissue engineering, robotics, and ecology.

Purpose of the Study:

• To highlight research trends in sustainable material selection for biofabrication.
• To discuss advancements in biofabrication techniques for improved efficiency.
• To explore the role of computational modeling in optimizing biofabrication processes.

Main Methods:

• Review of current research trends in sustainable materials for biofabrication.
• Analysis of emerging biofabrication techniques.
• Discussion of computational modeling approaches for biosystems.
• Exploration of 'bionomic rationality' in biomanufacturing.

Main Results:

• Identification of key research directions in sustainable material sourcing and biofabrication methods.
• Emphasis on the potential of computational prediction to transition biofabrication from trial-and-error to optimized production.
• Highlighting the need for refined production and validation processes.

Conclusions:

• Implementing sustainable material selection and advanced biofabrication techniques is crucial.
• Computational modeling can lead to efficient, target-optimized biofabrication with reduced resource and energy consumption.
• Adopting 'bionomic rationality' in biofabrication can significantly contribute to greening human activities.