A framework for digital twin integration in biofabrication and a scaffold 3D bioplotting case study

• Published in: Manufacturing letters 2024-10, Vol.41, p.1182-1191
• Main Authors: Ahmed, Nafi, Narayanan, Lokesh Karthik, Shirwaiker, Rohan
• Format: Article
• Language: English
• Subjects: 3D Printing; Biofabrication; Digital twins
• ISSN: 2213-8463; 2213-8463
• DOI: 10.1016/j.mfglet.2024.09.144

Biofabrication, which integrates biological sciences with advanced manufacturing, is vital for innovations in tissue engineering and regenerative medicine. One primary consideration in this domain is ensuring consistent, scalable, and adaptable processes that are amenable to clinical translation. Toward this, this paper introduces a new framework for digital twin integration in biofabrication. Digital twins, which are real-time virtual replicas of physical systems, can facilitate comprehensive monitoring, accurate prediction, and effective optimization to enable robust biofabrication processes and systems. The proposed framework incorporates major building blocks for implementing digital twins for biofabrication, including comprehensive data acquisition and analysis using sophisticated sensors to integrate biological, material, and process data; advanced modeling methods utilizing traditional and machine learning algorithms to refine process parameters; and feedback loop for real-time process adjustments. The first phase of the framework is demonstrated through a case study highlighting process optimization of 3D bioplotting of polycaprolactone (PCL) scaffolds. The digital twin’s insights streamline decisions on bioplotting parameters and post-processing, ensuring that the printed scaffold meets the desired mechanical and biological properties, thereby significantly enhancing cell proliferation and printing resolution. Key benefits of this approach include optimized biofabrication outcomes by integrating physical and biological models, promoting scalability and reproducibility with an accelerated research and development phase. This work underlines the promise of digital convergence in biofabrication, which can accelerate advancements in regenerative medicine and tissue engineering.