Bioprinting is a complex process, often approached by a time-consuming experimental trial-and-error approach before reaching the desired result. In silico tools can speed up the optimization of process variables and, at the same time, highlight the interplay between chemistry, biology, and mechanics behind the success or failure of the process. The goal of the present chapter is to review and discuss theoretical models and computer-based simulations in the field. This chapter discusses basic and advanced knowledge, as well as good practices, to perform in silico studies in the field of bioprinting. Moreover, it highlights how essential is to integrate multidisciplinary knowledge to effectively exploit computational modeling in the daily lab activity.

Models and simulations as enabling technologies for bioprinting process design / Conti, M; Santesarti, G; Scocozza, F; Marino, M. - (2022). [10.1016/B978-0-323-85430-6.00009-1].

Models and simulations as enabling technologies for bioprinting process design

Santesarti G;
2022

Abstract

Bioprinting is a complex process, often approached by a time-consuming experimental trial-and-error approach before reaching the desired result. In silico tools can speed up the optimization of process variables and, at the same time, highlight the interplay between chemistry, biology, and mechanics behind the success or failure of the process. The goal of the present chapter is to review and discuss theoretical models and computer-based simulations in the field. This chapter discusses basic and advanced knowledge, as well as good practices, to perform in silico studies in the field of bioprinting. Moreover, it highlights how essential is to integrate multidisciplinary knowledge to effectively exploit computational modeling in the daily lab activity.
2022
Bioprinting: From Multidisciplinary Design to Emerging Opportunities
Computational models; bioprinting
02 Pubblicazione su volume::02a Capitolo o Articolo
Models and simulations as enabling technologies for bioprinting process design / Conti, M; Santesarti, G; Scocozza, F; Marino, M. - (2022). [10.1016/B978-0-323-85430-6.00009-1].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1749639
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