Understanding nanoparticle-cell interactions is critical for engineering effective therapeutic delivery. CBNS researchers have developed a new technique to improve the analysis of nanoparticle association with cells using flow cytometry.
A common limitation when analysing flow cytometry data generated with nanoparticles is the low fluorescent signal emitted from the particles. The low signal means that a large number of nanoparticles must associate with the cell before the interactions are detected.
Using a new deconvolution algorithm, we have been able to improve the sensitivity of flow cytometry assays by an order of magnitude, compared to traditional analysis techniques. The algorithm also enables hidden populations of cells to be revealed from the autofluorescent cell background.