title: Statistical modeling of single target cell encapsulation.
abstract: High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.
authors.affiliation: Demirci Bio-Acoustic-MEMS in Medicine Laboratory, Center for Bioengineering, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: SangJun
authors.initials: S
authors.lastname: Moon
authors.forename: Elvan
authors.initials: E
authors.lastname: Ceyhan
authors.forename: Umut Atakan
authors.initials: UA
authors.lastname: Gurkan
authors.forename: Utkan
authors.initials: U
authors.lastname: Demirci
mesh_terms: D002468:Cell Physiological Phenomena; D002469:Cell Separation / Q000379:methods*; D002477:Cells / Q000737:chemistry*; D006801:Humans; D044085:Microfluidics; D015233:Models, Statistical