UTERIAM
development of three-dimensional (3D) tissue models


The development of three-dimensional (3D) tissue models that enable the study of the physiology and pathology of different biological structures, without the need to use animal models or invasive procedures to obtain samples, represents a major breakthrough in the study of multiple diseases, including cancer. However, prior to the project, there were no artificial intelligence applications specifically designed to optimise the generation of complex endometrial tissue models through 3D bioprinting, enabling the study of diseases such as endometrial cancer and advancing knowledge of these conditions.

The development of three-dimensional (3D) tissue models that enable the study of the physiology and pathology of different biological structures, without the need to use animal models or invasive procedures to obtain samples, represents a major breakthrough in the study of multiple diseases, including cancer. However, prior to the project, there were no artificial intelligence applications specifically designed to optimise the generation of complex endometrial tissue models through 3D bioprinting, enabling the study of diseases such as endometrial cancer and advancing knowledge of these conditions.

Challenges
Obtaining sufficient quantity and quality of data to feed AI systems and train robust models.
Automating the data collection process for AI to ensure uniformity and consistency.
Ensuring the printability of formulated bioinks through proper definition of their viscosity, gelation capacity and mechanical stability.
Guaranteeing the biocompatibility of the bioinks to ensure cell survival and functionality, and to accurately recreate endometrial tissue.
Solution
Integration of artificial intelligence into the process of generating uterine tissue models through the use of advanced biofabrication techniques (specifically 3D bioprinting), enabling the study of pathologies such as endometrial cancer, which are difficult to address through other disciplines.
This represents a significant step towards the creation of a standardised and optimised process for studying various diseases, particularly endometrial cancer, which in the long term will enable the implementation of personalised therapies. This approach will not only improve patient health and wellbeing but also deliver significant savings in time and resources.
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Participating entities
Funding entity
SEKUENS
Collaborator
SERIDA
Subcontractor
IDONIAL