Back to Search Start Over

Computational Models for Diagnosing and Treating Endometriosis

Authors :
Wangui Mbuguiro
Adriana Noemi Gonzalez
Feilim Mac Gabhann
Source :
Frontiers in Reproductive Health, Vol 3 (2021)
Publication Year :
2021
Publisher :
Frontiers Media S.A., 2021.

Abstract

Endometriosis is a common but poorly understood disease. Symptoms can begin early in adolescence, with menarche, and can be debilitating. Despite this, people often suffer several years before being correctly diagnosed and adequately treated. Endometriosis involves the inappropriate growth of endometrial-like tissue (including epithelial cells, stromal fibroblasts, vascular cells, and immune cells) outside of the uterus. Computational models can aid in understanding the mechanisms by which immune, hormone, and vascular disruptions manifest in endometriosis and complicate treatment. In this review, we illustrate how three computational modeling approaches (regression, pharmacokinetics/pharmacodynamics, and quantitative systems pharmacology) have been used to improve the diagnosis and treatment of endometriosis. As we explore these approaches and their differing detail of biological mechanisms, we consider how each approach can answer different questions about endometriosis. We summarize the mathematics involved, and we use published examples of each approach to compare how researchers: (1) shape the scope of each model, (2) incorporate experimental and clinical data, and (3) generate clinically useful predictions and insight. Lastly, we discuss the benefits and limitations of each modeling approach and how we can combine these approaches to further understand, diagnose, and treat endometriosis.

Details

Language :
English
ISSN :
26733153
Volume :
3
Database :
Directory of Open Access Journals
Journal :
Frontiers in Reproductive Health
Publication Type :
Academic Journal
Accession number :
edsdoj.91b4b22fffe74b8ba25a13540589d2e3
Document Type :
article
Full Text :
https://doi.org/10.3389/frph.2021.699133