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Real time cell analyzer delivering label-free single cell results in minutes

Real time cell analyzer delivering label-free single cell results in minutes. LumaCyte’s Radiance Laser Force Cytology (LFC) analysis platform instrument is a high-content, label-free microfluidic cell sorter and real time cell analyzer that enables scientists and researchers to characterize and sort individual cells by measuring their optical force.

Key Features

96-well Plate Format

Radiance + Autosampler has a 96-well plate format allowing for unattended, automated processing and analysis.

Flexibility and Power

Radiance + Autosampler is fully programmable via Illuminate™ software suite, giving users maximum flexibility and power for automating sample analyses.

Viable Cells

Cells remain viable for growth and further analysis after sorting with Radiance.

Sensitivity

Sensitive to subtle phenotypic changes including: viral infection, cell differentiation, live/dead, transfection, chemical exposure, etc.

Mid-process Sample Changes

Illuminate software suite provides flexibility allowing for mid-process sample changes and additions show they be required.

Small Benchtop Design

Benchtop design with a footprint (26″L × 20″W x 28″H) small enough to fit on any laboratory bench.

Why Radiance?

Quantify Detectable Differences.

Differences in cell biochemistry, morphology, and deformability (cytoskeletal changes), which are often associated with viral infection, cancer, sepsis, and other diseases, give rise to detectable differences in optical force and deformability which are quantitated by Radiance.

Fits within your current workflow.

Correlates tightly with ddPCR, TCID50, and Plaque Assays.

https://www.youtube.com/watch?v=J4559asAUc0

LumaCyte Force Cytology

1:31 duration

The broad and deep applicability of LFC™, combined with novel univariate & robust multivariate data, enables a host of machine learning strategies and cloud computing capabilities, driving advanced analytics for improved workflow efficiency, enabling a deeper understanding of cell-based biological systems and processes. From real-time cell health monitoring with predictive insights, to rapid and precise viral infectivity measurement, transfection, transduction and stem cell differentiation monitoring, LumaCyte’s LFC™ analytics are transforming key bioprocesses across the growing cell & gene therapy and vaccine sectors.

Radiance® Process Analytics and Production Monitoring

Rapid and Precise Process Analytics

  • Allows for real-time process optimization
  • Increase process knowledge and sources of process variability
  • Mitigates batch failures due to variability
  • Enables real-time contamination monitoring
  • Allows for significant Increases in product yields

Baculovirus Correlation With Plaque Assay

  • Radiance® data correlates with the pfu/mL in supernatant – can replace subsequent infectivity assays
  • Real-Time monitoring using Radiance® enables the development of novel process analytics
  • For in-process cell infection monitoring, Radiance® measurement is 800 to 3,000X faster than traditional methods

Radiance® Infectivity Validation Data

VSV Infectivity Correlation with TCID50

  • Composite Calibration Curve Developed using 5 independent experiments over a ~1-month period
  • Subsequent experiment using curve to predict unknown titers shows an average log10 difference of 0.06
  • Demonstrates a high accuracy of ±15% and precision of ±22%

  • Significant improvement in speed, accuracy, and precision when compared to plaque and TCID50 assay

  • Radiance® tested with 30+ cell types and 35+ viruses to date

Radiance® AAV Transduction Quantification

Optical Force Index Changes

  • Current methods to assess AAV transduction are tedious, variable and may not reflect in vivo performance due to presence of helper virus
  • Radiance® can be used to monitor AAV transduction without the use of a helper virus
  • Radiance® LFC™ analytics illustrate a progressively larger increase in optical force at 48h and 72h post transduction with the addition of higher concentration of AAV

AAV Transduction Correlation

  • Strong correlation developed using data across 3 independent experiments over 6 weeks
  • Accurate and precise unknown prediction within 0.054log10 (12.5%) of the known stock titer with a CV of 17% for 3 unknown samples

Empty/Full Capsid Discrimination During Cellular Transduction

  • Cells treated with an equivalent number of empty or full capsids added at five different total concentrations
  • Progressive decrease in velocity seen with increasing full capsid MOI
  • Minimal response seen to empty capsid samples – highest concentration of empty capsid added shows smaller response than lowest concentration of full capsid

Radiance® Real-time Cell Health Monitoring

  • This example compares Vero cells frozen with di erent methods to the standard protocol and then analyzed immediately post thaw
  • Significant changes are seen in Optical Force Index for samples without DMSO (Sample 3) and rapid (uncontrolled) freezing (Sample 4)
  • Radiance® can rapidly characterize a population of cells to ensure consistent process performance

Measles Live Virus Vaccine Production Monitoring*

Merck, Vaccines McCracken et al. 2022. Vaccines 10(10), 1589

  • Radiance® single cell data was collected from Vero cells on microcarriers producing measles virus sampled from a bioreactor
  • The percentage of cells with an Optical Force Index > 55 s-1 can be defined as the Radiance® Infection Metric and used to correlate with the estimated potency (TCID50/cell)
  • Strong correlation demonstrated between estimated potency measurements and Radiance® data (0.074log10 absolute average difference)
  • Calibration curve can be used to accurately calculate the estimated potency and provide real time feedback to improve the speed of process development and manufacturing consistency

Radiance® Correlation with
Estimated Potency

Rapid Detection of Out-of-Spec (OOS) Batches

In-Process Manufacturing Application

  • Radiance® data can be used to monitor production runs in real time to understand the expected process behavior
  • Batches that deviate from normal operating conditions can be quickly identified in order to provide corrective action as required, saving time and resources 
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