Toward Industrial-Scale Therapeutic Cell Production: Technologies Addressing Purity, Scalability, and Robustness in Regenerative Medicine

Regenerative medicine is an exciting, rapidly moving field that promises to launch an entirely new industry with an entirely new product: human cells. But biology, as it is currently practiced, is not easily adapted to an industrial scale, where cost-effectiveness, throughput, and quality control are the metrics of success. For regenerative medicine to progress, new technologies must be developed to address some key questions: How can we cost-effectively expand stem cells to industrial scale quantities (on the order of 108 - 1010 per therapeutic dose) while maintaining a homogeneous pluripotent cell phenotype? How can we uniformly differentiate these cells into therapeutic phenotypes and mitigate the risk of teratoma formation? By what metric do we assess the functionality of these cells? How do we assemble these cells into functional tissues for therapy? And how can we automate these processes so that they cost-effectively produce repeatable results. What must ultimately arise is a "cell therapy pipeline" populated with a range of new technologies for stem cell expansion, differentiation, purification, and functional tissue assembly. My graduate work has focused on developing new technologies which address two major challenges currently facing the stem cell field: scalability and robustness. In this dissertation, I introduce electrophysiology-activated cell sorting (EPACS), a label-free, non-genetic method of purifying cells based on a functional response to stimulus (namely, electrophysiology). As many of the cell types relevant for regenerative medicine are electrically-excitable (e.g. cardiomyocytes, neurons, smooth muscle cells), EPACS is well-suited for purifying cells from heterogeneous stem cell progeny in clinical applications without the risk and expense associated with labeling molecules. This concept represents an entirely new approach to cell sorting, in which a cell's functionality is assessed rather than its expression profile or physical characteristics. I present the theoretical underpinnings of EPACS in chapter 2. In chapter 3 I present a system which sorts stem cell derived clusters based on their the evoked extracellular field potential signals. In chapter 4, I present an alternative technique for EPACS which achieves single cell resolution using a non-toxic fluorescent calcium indicator dye. I demonstrate that EPACS is capable of distinguishing undifferentiated human induced pluripotent stem cell clusters (iPSC) from iPSC-derived cardiomyocyte (iPSC-CM) clusters, and that individual HL-1 cardiomyocytes can be distinguished from 3T3 fibroblasts. For these cell sorters, I have developed microfluidic devices with integrated electrodes for electrical stimulation and recording of extracellular field potential signals from cells in flow along with the associated electronic instrumentation and automation software. In chapter 5, I present a simple method for controlling stem cell colony geometry using a silicone stencil which leads to an improvement in stem cell pluripotency maintenance and a 3-fold increase in cardiomyocyte differentiation yield. Cell colony geometry plays a significant role in cell fate determination, and factors such as colony shape, spacing, and cell density are impossible to control with conventional cell culture techniques. My technique is easily scalable and provides repeatable results across many colonies, making it well-suited for applications in high-throughput screening and industrial cell production.Finally, I provide detailed protocols for cell culture, EPACS, stencil patterning, and microsystem fabrication in the appendices, and I briefly present two side projects that I have worked on in my graduate career: a point-of-care pathogen genotyping assay for the developing world and a microfabricated cell motility assay which enables controlled studies of 3D cell migration. In the online supplementary accompanying this dissertation, I have uploaded my MATLAB and Labview source code for cell sorting and epifluorescence image analysis