Engineering Advanced In Vitro Models of Systemic Sclerosis for Drug Discovery and Development

Andrea De Pieri1, Benjamin D Korman2, Astrid Jüngel3,4

  • 1Dr. A. De Pieri, Prof. K. Wuertz-Kozak, Department of Biomedical Engineering, Rochester Institute of Technology (RIT), 106 Lomb Memorial Rd., Rochester, NY, 14623, USA.

Advanced Biology
|April 14, 2021
PubMed

Insights

Systemic sclerosis (SSc) treatment needs new antifibrotic therapies. Advanced in vitro models offer promising platforms for developing and validating novel drugs for this complex autoimmune disease.

Area of Science:

  • Rheumatology and Immunology
  • Translational Medicine
  • Biomedical Engineering

Background:

  • Systemic sclerosis (SSc) is a severe autoimmune disease with high mortality and no cure.
  • Current animal models for SSc research are limited in predicting human treatment efficacy.
  • There is a critical need for effective antifibrotic therapies to combat SSc-related fibrosis.

Purpose of the Study:

  • To review advancements in in vitro models for Systemic sclerosis research.
  • To explore biological, biochemical, and biophysical cues used to mimic the SSc microenvironment.
  • To highlight future perspectives for drug discovery and validation in SSc treatment.

Main Methods:

  • Review of recent literature on in vitro models for Systemic sclerosis.
  • Analysis of biological factors (growth factors, cytokines, cocultures) in SSc models.
  • Examination of biochemical (hypoxia, ROS) and biophysical (stiffness, topography) cues.

Main Results:

  • Advanced in vitro models are emerging as valuable tools for SSc research.
  • These models incorporate various cues to better recapitulate the SSc microenvironment.
  • Progress in in vitro modeling aids in investigating novel pharmaceutical therapies for SSc.

Conclusions:

  • In vitro models are crucial for overcoming limitations of traditional animal models in SSc.
  • Utilizing diverse cues enhances the predictive power of in vitro systems for SSc therapies.
  • Future development of these models holds significant promise for SSc drug discovery and validation.