Three-Dimensional Printing of Cell Exclusion Spacers (CES) for Use in Motility Assays

Christen J. Boyer, David H. Ballard, Jungmi W. Yun, Adam Y. Xiao, Jeffery A. Weisman, Mansoureh Barzegar, Jonathan Steven Alexander

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Purpose: Cell migration/invasion assays are widely used in commercial drug discovery screening. 3D printing enables the creation of diverse geometric restrictive barrier designs for use in cell motility studies, permitting on-demand assays. Here, the utility of 3D printed cell exclusion spacers (CES) was validated as a cell motility assay. Methods: A novel CES fit was fabricated using 3D printing and customized to the size and contour of 12 cell culture plates including 6 well plates of basal human brain vascular endothelial (D3) cell migration cells compared with 6 well plates with D3 cells challenged with 1uM cytochalasin D (Cyto-D), an F-actin anti-motility drug. Control and Cyto-D treated cells were monitored over 3 days under optical microscopy. Results: Day 3 cell migration distance for untreated D3 cells was 1515.943μm ± 10.346μm compared to 356.909μm ± 38.562μm for the Cyt-D treated D3 cells (p < 0.0001). By day 3, untreated D3 cells reached confluency and completely filled the original voided spacer regions, while the Cyt-D treated D3 cells remained significantly less motile. Conclusions: Cell migration distances were significantly reduced by Cyto-D, supporting the use of 3D printing for cell exclusion assays. 3D printed CES have great potential for studying cell motility, migration/invasion, and complex multi-cell interactions.

Original languageEnglish
Article number155
JournalPharmaceutical Research
Issue number8
StatePublished - Aug 1 2018


  • 3D printing
  • invasion assays
  • migration assays
  • motility assays
  • personalized medicine
  • three-dimensional printing


Dive into the research topics of 'Three-Dimensional Printing of Cell Exclusion Spacers (CES) for Use in Motility Assays'. Together they form a unique fingerprint.

Cite this