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Published in: Journal of Translational Medicine 1/2020

Open Access 01-12-2020 | Artificial Intelligence | Review

Endometriosis: current challenges in modeling a multifactorial disease of unknown etiology

Authors: Helena Malvezzi, Eliana Blini Marengo, Sérgio Podgaec, Carla de Azevedo Piccinato

Published in: Journal of Translational Medicine | Issue 1/2020

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Abstract

Endometriosis is a chronic inflammatory hormone-dependent condition associated with pelvic pain and infertility, characterized by the growth of ectopic endometrium outside the uterus. Given its still unknown etiology, treatments usually aim at diminishing pain and/or achieving pregnancy. Despite some progress in defining mode-of-action for drug development, the lack of reliable animal models indicates that novel approaches are required. The difficulties inherent to modeling endometriosis are related to its multifactorial nature, a condition that hinders the recreation of its pathology and the identification of clinically relevant metrics to assess drug efficacy. In this review, we report and comment endometriosis models and how they have led to new therapies. We envision a roadmap for endometriosis research, integrating Artificial Intelligence, three-dimensional cultures and organ-on-chip models as ways to achieve better understanding of physiopathological features and better tailored effective treatments.
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Metadata
Title
Endometriosis: current challenges in modeling a multifactorial disease of unknown etiology
Authors
Helena Malvezzi
Eliana Blini Marengo
Sérgio Podgaec
Carla de Azevedo Piccinato
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Journal of Translational Medicine / Issue 1/2020
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-020-02471-0

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