title: A transfer function approach for predicting rare cell capture microdevice performance.
abstract: Rare cells have the potential to improve our understanding of biological systems and the treatment of a variety of diseases; each of those applications requires a different balance of throughput, capture efficiency, and sample purity. Those challenges, coupled with the limited availability of patient samples and the costs of repeated design iterations, motivate the need for a robust set of engineering tools to optimize application-specific geometries. Here, we present a transfer function approach for predicting rare cell capture in microfluidic obstacle arrays. Existing computational fluid dynamics (CFD) tools are limited to simulating a subset of these arrays, owing to computational costs; a transfer function leverages the deterministic nature of cell transport in these arrays, extending limited CFD simulations into larger, more complicated geometries. We show that the transfer function approximation matches a full CFD simulation within 1.34 %, at a 74-fold reduction in computational cost. Taking advantage of these computational savings, we apply the transfer function simulations to simulate reversing array geometries that generate a "notch filter" effect, reducing the collision frequency of cells outside of a specified diameter range. We adapt the transfer function to study the effect of off-design boundary conditions (such as a clogged inlet in a microdevice) on overall performance. Finally, we have validated the transfer function's predictions for lateral displacement within the array using particle tracking and polystyrene beads in a microdevice.
authors.affiliation: Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, 14853, USA.
authors.forename: James P
authors.initials: JP
authors.lastname: Smith
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Kirby
mesh_terms: D000818:Animals; D002468:Cell Physiological Phenomena; D002469:Cell Separation / Q000295:instrumentation*; D003198:Computer Simulation; D017076:Computer-Aided Design; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005434:Flow Cytometry / Q000295:instrumentation*; D006801:Humans; D056656:Lab-On-A-Chip Devices; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity