Tamar Tak

Leiden University Medical Center, Leiden, the Netherlands

Flow cytometry enables the high-throughput analysis of cells at the single cell level and has been an indispensable tool for the biomedical research fields. Shared resource laboratories (SRL) have been indispensable in making expensive instruments available to research labs that would not have had the budget to acquire an instrument by themselves. As SRL housed instruments are shared by many users, they are commonly used for over 12 hours per day. Due to this intensive use, instrument breakdowns are inevitable. The resulting downtime is highly expensive to the SRL due to loss of income and is inconvenient for researchers who have to reschedule their experiments. Therefore, predicting instrument breakdowns and replacing parts before they fail would be desirable.

Most commercial cytometers are equipped with software modules to assure that instruments are performing to specifications using standardized reference beads (QC). Usually, the software allows visualization over time through Levey-Jenning plots. Unfortunately, these software modules are often limited in ease of use and limited to visualization of only a single or a few parameters. Furthermore, these software modules are usually limited to a single instrument, which makes extensive instrument monitoring for a large SRL very time consuming.

To facilitate easier and more advanced monitoring of instrument performance we have developed FlowMonitor, an R-shiny app that allows users without coding experience to analyze QC data in full detail and for multiple instruments. The app is currently compatible with the Cytek Aurora, BD instruments running FACSDiva or FACSSuite and Beckman Coulter CytoFLEX SRT  instruments and adapts to any cytometer configuration. The app allows visualization of all parameters reported during QC, comparisons between detectors, lasers and even different instruments. In addition, lines can be added to indicate thresholds or interventions, allowing more easy determination of the effect of the intervention.

We have tested FlowMonitor with QC data from 5 Cytek Aurora spectral cytometers obtained over a period of 3 years. This has allowed us to compare instrument stability and performance, visualize laser degradation over time and identify issues that were identified during QC. This has led to the software being used on a weekly basis within our SRL. In the future, we plan to expand FlowMonitor by including more instruments from different vendors. In addition, we plan to use machine-learning to find predictive parameters in the QC data. The To allow other SRL reduce their instrument down-time, the app is available for testing and will be made publicly available.