3D Bioprinting Models for Glioblastoma: From Scaffold Design to Therapeutic Application

F Francisco Branco (Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal) J Joana Cunha (Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal) M Maria Mendes (Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal) J João J. Sousa (Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal) C Carla Vitorino (Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal)

Abstract

AbstractConventional in vitro models fail to accurately mimic the tumor in vivo characteristics, being appointed as one of the causes of clinical attrition rate. Recent advances in 3D culture techniques, replicating essential physical and biochemical cues such as cell–cell and cell–extracellular matrix interactions, have led to the development of more realistic tumor models. Bioprinting has emerged to advance the creation of 3D in vitro models, providing enhanced flexibility, scalability, and reproducibility. This is crucial for the development of more effective drug treatments, and glioblastoma (GBM) is no exception. GBM, the most common and deadly brain cancer, remains a major challenge, with a median survival of only 15 months post‐diagnosis. This review highlights the key components needed for 3D bioprinted GBM models. It encompasses an analysis of natural and synthetic biomaterials, along with crosslinking methods to improve structural integrity. Also, it critically evaluates current 3D bioprinted GBM models and their integration into GBM‐on‐a‐chip platforms, which hold noteworthy potential for drug screening and personalized therapies. A versatile development framework grounded on Quality‐by‐Design principles is proposed to guide the design of bioprinting models. Future perspectives, including 4D bioprinting and machine learning approaches, are discussed, along with the current gaps to advance the field further.

Article Details

Volume / Issue Vol. 37, Issue 18
Published May 01, 2025
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (5)

F

Francisco Branco

Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal

J

Joana Cunha

Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal

M

Maria Mendes

Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal

J

João J. Sousa

Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal

C

Carla Vitorino

Faculty of Pharmacy University of Coimbra Pólo das Ciências da Saúde Azinhaga de Santa Comba Coimbra 3000‐548 Portugal