Chapter 10

Computational Engineering for 3D Bioprinting

Models, Methods, and Emerging Technologies

Vidyapati Kumar

Vidyapati Kumar

Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India

Search for more papers by this author
Ankita Mistri

Ankita Mistri

Department of Mechanical Engineering, Indian Institute of Technology, Dhanbad, Jharkhand, India

Search for more papers by this author
Varnit Jain

Varnit Jain

Department of Metallurgy and Materials Engineering, Indian Institute of Engineering Science and Technology, Shibpur, West Bengal, India

Search for more papers by this author
Manojit Ghosh

Manojit Ghosh

Department of Metallurgy and Materials Engineering, Indian Institute of Engineering Science and Technology, Shibpur, West Bengal, India

Search for more papers by this author
First published: 05 July 2024

Summary

Bioprinting is an emerging technology that enables the precise fabrication of complex biological structures by depositing cells, biomaterials, and biomolecules in a layered fashion. Realizing the immense potential of bioprinting requires deep integrative knowledge spanning engineering, materials science, biology, and computing. This chapter provides a comprehensive overview of the computational engineering approaches being developed to understand, optimize, and advance bioprinting methodologies. The fundamental techniques of extrusion, jetting, laser-assisted, and stereolithographic bioprinting are first introduced, along with their respective capabilities and limitations. It then delves into the physics-based modeling methods being employed to simulate key aspects of the bioprinting process, including finite element analysis (FEA), computational fluid dynamics (CFD), agent-based modeling (ABM), lattice Boltzmann techniques, and molecular dynamics (MD) simulations. These computational models enable the design and enhancement of bioprinting systems, materials, and processes by providing insights into factors, such as scaffold mechanics, fluid rheology, cell interactions, and material behavior. The emerging integration of data-driven artificial intelligence methods, like machine learning for design, optimization, and modeling applications is also discussed. This chapter provides a comprehensive guide to the computational engineering approaches and technologies driving innovation in bioprinting. It will be an essential reference for the modeling principles and tools needed to advance bioprinting research and translate findings into impactful clinical and commercial solutions.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.