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Faculty/Staff Public Undergraduate students

Rebecca Schneider

BioE PhD Defense Presentation

Date: Tuesday, February 28, 2023

Time: 9:00 AM

Location: 1128 IBB – Suddath Seminar Room

Zoom Link: https://gatech.zoom.us/j/97953677766

 

Advisor: 

Andrés J. García, PhD (Georgia Institute of Technology)

 

Committee Members:

John Blazeck, PhD (Georgia Institute of Technology)

Wilbur A. Lam, MD, PhD (Emory University and Georgia Institute of Technology)

Ankur Singh, PhD (Georgia Institute of Technology)

Ross Marklein, PhD (University of Georgia)

 

High-throughput 3D on-chip potency assay for improved cell therapy product clinical prediction

 

Cell therapies offer promising strategies to treat diverse oncologic, inflammatory, and immune applications. Despite promising early phase clinical data, cell therapy candidates face new translational challenges, in part, due to a poor understanding of the cell therapy product during drug development and scale up. Current potency testing is often overly simplified and strongly biased by traditional 2D culture techniques. By engineering improved, well-defined, physiological-relevant in vitro systems, we aim to provide high-throughput and reproducible potency assays with improved outcome prediction of in vivo and/or clinical response. We have demonstrated proof-of-concept of the on-chip platform by showing improved in vitro immunomodulatory prediction and stronger fidelity to in vivo secretion compared to traditional 2D culture for n=9 mesenchymal stem/stromal cell (MSC) donors. We have further evaluated n=60 MSC and MSC-derivative clinical samples using the on-chip platform and found secretion outcomes with greater correlation and/or variance across donor-matched characteristics compared to 2D culture secretion. Future work will include platform clinical validation by evaluation of on-chip secretion correlation to patient-matched outcomes. The data presented here is in strong support of the value of the on-chip system to deliver scalable and high throughput cell product secretion information more predictive of in vivo and/or clinical settings.