Computational analysis of high-throughput flow cytometry data

• Published in: Expert opinion on drug discovery Vol. 7; no. 8; p. 679
• Main Authors: Robinson, J Paul, Rajwa, Bartek, Patsekin, Valery, Davisson, Vincent Jo
• Format: Journal Article
• Language: English
• Published: England 01.08.2012
• Subjects: Data Interpretation, Statistical; Drug Evaluation, Preclinical - methods; Flow Cytometry - methods; High-Throughput Screening Assays - methods; Humans; Pharmaceutical Preparations
• ISSN: 1746-045X
• DOI: 10.1517/17460441.2012.693475

Flow cytometry has been around for over 40 years, but only recently has the opportunity arisen to move into the high-throughput domain. The technology is now available and is highly competitive with imaging tools under the right conditions. Flow cytometry has, however, been a technology that has focused on its unique ability to study single cells and appropriate analytical tools are readily available to handle this traditional role of the technology. Expansion of flow cytometry to a high-throughput (HT) and high-content technology requires both advances in hardware and analytical tools. The historical perspective of flow cytometry operation as well as how the field has changed and what the key changes have been discussed. The authors provide a background and compelling arguments for moving toward HT flow, where there are many innovative opportunities. With alternative approaches now available for flow cytometry, there will be a considerable number of new applications. These opportunities show strong capability for drug screening and functional studies with cells in suspension. There is no doubt that HT flow is a rich technology awaiting acceptance by the pharmaceutical community. It can provide a powerful phenotypic analytical toolset that has the capacity to change many current approaches to HT screening. The previous restrictions on the technology, based on its reduced capacity for sample throughput, are no longer a major issue. Overcoming this barrier has transformed a mature technology into one that can focus on systems biology questions not previously considered possible.