Rebecca Schneider

Thursday, May 27, 2021, 10:00 AM EST 

Link: https://bluejeans.com/326399650

Advisor: 

Andrés J. García, Ph.D.

George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology

Committee Members:  

John Blazeck, Ph.D.

School of Chemical & Biomolecular Engineering, Georgia Institute of Technology

Ankur Singh , Ph.D.

George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology

Wilbur Lam, Ph.D., MD

Division of Hematology/Oncology, Department of Pediatrics, Emory University

Ross Marklein, Ph.D.

School of Chemical, Materials, and Biomedical Engineering, University of Georgia

High-throughput microfluidic potency assay for human mesenchymal stromal cell products with clinical prediction

Human mesenchymal stromal cells (MSC) are a promising source for regenerative cell therapy. However, MSC market access has been stymied by product variability across MSC donors and manufacturing practices resulting in inconsistent clinical outcomes. The inability to predict MSC in vivo performance is a major limitation of MSC market penetration. Standard metrics of MSC potency employ MSC:peripheral blood mononuclear cell (PBMC) co-cultures, however, these assays are challenging to scale due to high PBMC donor variability. To address this challenge, I present a high-throughput, scalable, low-cost microfluidic MSC potency assay with improved MSC secretory correlation to in vivo performance. Traditional planar potency assays have been largely unsuccessful for MSC clinical translation. I demonstrate improved predictive power of the microfluidic platform compared to traditional planar methods by comparison of MSC secretory responses to PBMC co-culture assays. Further, I show analogous MSC secretory performance achieved in the microfluidic platform compared to an in vivo model. Lastly, with early promising results, I am now performing microfluidic potency assay validation by testing clinical samples from the multicenter MILES osteoarthritis clinical study for further system optimization and clinical validation.