Label-Free Cell Analysis with Laser Force Cytology

Real-time process analytical technology for accelerated biologics development and improved manufacturing consistency

The overall process for developing and manufacturing vaccines and cell and gene therapies (CGTs) is challenging and resource intensive because it involves complex and variable raw materials, demanding bioprocessing procedures, and sensitive final products. The adoption of robust analytical technologies to enable rapid process development and ensure manufacturing quality and consistency is a key component to failure-proofing biologics license applications.

However, many current analytical methods, especially for vaccines and CGTs, face challenges in terms of speed, reproducibility, and resource requirements, driving up costs and development times. Advanced bioanalytics are becoming a vital part of a successful quality by design (QbD) biomanufacturing program, where accurate and precise real-time data enable improved production consistency and product quality.

Implementing process analytical technology (PAT)­—where real-time data, including critical quality attributes (CQAs) and critical process parameters (CPPs), can be comprehensively and proactively monitored and analyzed—allows for advanced process controls and the development of dynamic and robust processes.

A real-time label-free PAT

Laser Force Cytology™ (LFC™), a novel label-free technology, applies optical and hydrodynamic forces to single cells to measure their intrinsic biophysical and biochemical properties without the use of dyes, antibodies, or fluorescent labels.1 These optical force properties, including refractive index, change with a wide variety of biological phenomena, including cell health conditions, activation, transfection, cell differentiation, and viral infection.

LFC measures subtle early indicators of phenotypic changes and differences in a sensitive and rapid manner, enabling both in-process analytics as well as offline release and potency assays to ensure consistent product quality and yields.2-4 For example, LFC can provide a coefficient of variation as low as 14% when measuring adeno-associated virus (AAV) transduction.

In this tutorial, select LFC applications illustrate the benefit of real-time optical force data to monitor stem cell differentiation, AAV production via transfection, and live virus vaccine potency. In contrast to many assays that are laborious, slow, and unreliable and thus not suitable as PAT methods, LFC provides accurate, precise, and sensitive results in minutes, demonstrating its key role within QbD programs.

Label-free stem cell differentiation monitoring

Antibodies have wide applicability as analytical tools, including phenotypic cell characterization, protein detection/quantification, and protein separation. However, antibodies are not without their drawbacks, and in many cases, a label-free approach is advantageous. Upon binding to a cell, antibodies can alter its activation state. Consequently, the expression of surface markers is not always consistent, and the analytical results may be affected.

A label-free approach instead allows the cell to be measured in its native state. Antibody sensitivity and specificity can vary based on the target antigen, population diversity, and manufacturing lot, creating false positives and false negatives as well as difficulties in repeating the results of antibody-based studies.5 Antibodies also require prior knowledge and the availability of a specific cell surface marker, preventing a priori discovery of unknown changes or differences among cells. In contrast, a label-free approach can make unbiased and universal measurements that are unaffected by lot-to-lot variability.

Finally, antibodies typically require significant time, cost, and labor to implement, making them resource intensive and unamendable for use in PAT methods. LFC provides label-free analysis with minimal sample perturbation and rapid time to result (minutes). One example is monitoring the differentiation of stem cells. LFC data illustrating the differentiation of human bone marrow–derived mesenchymal stem cells (hBM-MSCs) into either osteoblasts or adipocytes are shown in Figure 1.

Figure 1. Principal Component Analysis of Cell Populations. Cell samples, either undifferentiated or directed toward osteogenic or adipogenic lineages, were analyzed using LFC at the indicated time points. Performing principal component analysis with the population average and standard deviation of each of the LFC metrics allowed the changes between the time points and lineages to be visualized.

hBM-MSCs were measured using LFC prior to differentiation and then compared to samples harvested at 7, 14, and 21 days post differentiation for both of the pathways using principal component analysis (PCA).

PCA was used to refactor population wide data from multiple LFC parameters into principal components 1 and 2. In Figure 1, changes are shown for both lineages when compared to undifferentiated cells, with the adipogenic samples showing similar results at days 14 and 21, indicating that differentiation has likely stopped, while the osteogenic samples continue to progress through day 21.

This demonstrates the capability for LFC to monitor differentiation in a label-free manner, providing rapid and sensitive results to inform process development and manufacturing. The ability to quickly obtain nonsubjective results that track differentiation enables real-time process control beyond simple viability and proliferation, without the burden and bias of antibody-based labels.

AAV transfection reagent optimization

The production of viral vectors such as lentivirus and AAV is typically an integral part of the development and manufacturing of advanced therapies such as chimeric antigen receptor T-cell therapies and gene therapies. However, the use of viral vectors faces several challenges related to their development and manufacturing, from characterization, to quantification, to downstream purification.6,7

Manufacturing, in particular, is challenging when it comes to consistently maintaining high purity, potency, and safety while also focusing on cost controls that are acceptable for large-scale manufacturing.8

One of the most common methods of production for both lentivirus and AAV vectors is the use of transient transfection in human (HEK293) cells.9 Current tools to monitor and quantify CQAs such as viral titer during the transfection process are labor intensive and tedious, reducing the speed and efficiency of process development and the ability to monitor in real time.

Shown in Figure 2 are results from a collaboration between Catalent Biologics and LumaCyte to compare AAV vector production using three different transfection reagents, using both LFC and a digital droplet PCR (ddPCR)-based viral genome assay.10 Transfection complexes were prepared with DNA and with each of the reagents, and then they were added to HEK293 cells.

Figure 2. Velocity Histograms Comparing Control HEK293 Cells to Cell Populations Transfected with AAV Production Plasmids Using Three Different Transfection Reagents. Transfection resulted in a clear difference between each population and the control as well as differences between each of the reagents. The percentage of cells in the population with a velocity below 2,400 µm/s is shown numerically and graphically for the control and each reagent. Velocity is proportional to optical force.

At 72 h post transfection, cells were harvested and analyzed using LFC and compared to untransfected cells growing in parallel. Figure 2 shows single-cell histograms for each of the reagents compared to the control. For all reagents, the transfection resulted in a broadening of the velocity distribution, indicating an increased population heterogeneity. In addition, the percentage of low-velocity cells increased in the transfected samples, and by defining a velocity threshold of 2,400 µm/s, it was possible for the performance of the reagents to be compared.

As shown in Figure 2, reagent 3 (TR#3) showed the largest response, followed by reagent 1 and reagent 2, respectively.

When velocity data were used, a strong correlation was generated between the LFC measurements, which are available in near real time, and the ddPCR results, which take significant time and labor, demonstrating the strong utility of LFC for rapid process monitoring to improve speed of process development and optimization and ensure manufacturing consistency.

Additional applications of LFC throughout the AAV vector production process include adventitious agent monitoring to rapidly detect potential contamination as well as cell line characterization during process development and scaleup.

Live-virus vaccine production monitoring

The quantification and characterization of viral-based manufacturing processes is an essential component of the production of numerous classes of products, including viral vector vaccines, oncolytic viruses, and live virus vaccines (LVVs). In the case of LVVs, the potency or infectivity is typically the most critical measurement of efficacy. Therefore, real-time potency information from a PAT is extremely desirable during process development and manufacturing. It can increase process knowledge, improve yields, and ensure consistency.

However, existing methods to measure viral potency include the plaque assay and the endpoint dilution assay (50% tissue culture infectious dose, or TCID50), both of which suffer from high variability and long lead times. Thus, they are not capable of serving as PATs. A recent study by McCracken et al.2 detailed the use of LFC as a real-time PAT platform to measure LVV potency as well as detect the presence of adventitious viruses.
In one aspect of the study, Vero cells were seeded onto microcarriers, incubated to allow the cells to become confluent, and then infected with attenuated measles virus. At each time point post infection across multiple independent experiments, a sample was withdrawn from the bioreactor and separated into two fractions.

The first contained the microcarriers with cells attached, whereas the second contained any supernatant cells that had detached from the microcarriers. Cell samples were prepared from both fractions and then analyzed using LFC.

In parallel, supernatant samples were analyzed for viral potency using flow virometry as a surrogate measurement for TCID50. Although flow virometry is a physical measurement rather than infectious titer, it was used as an approximate correlation to the TCID50-based potency assay for measles virus during production.

However, should the ratio of total to infectious particles change due to some undetected process perturbation, a cell-based PAT such as LFC would reflect this change while a physical measurement, such as flow virometry, would not.

As shown in Figure 3, a strong correlation was developed between the potency per viable cell and the Radiance infection metric, defined as the percentage of cells with an optical force index greater than 55 s–1. With this correlation, the absolute average log10 difference between the estimated potency and LFC measurements is 0.074, demonstrating an excellent fit to the data.

Figure 3. Correlation between Radiance® Infection Metric and Estimated Potency. The population-wide correlation between Radiance data and estimated potency was determined on a per viable cell basis as measured by the total virus particles. Radiance data include contributions from both microcarrier and supernatant fractions of bioreactor samples collected during viral production using Vero cells. Each point represents the time point, and each experiment is indicated on the plot.

Once established, this correlation can be then used to calculate the titer of future production samples in minutes using the LFC data.

Using LFC as a rapid PAT for monitoring potency as well as an analytical assay for measuring infectious titer helps pave the way for reducing the research, development, and manufacturing timeline for LVVs as well as other vaccines that rely on viruses during their development and manufacturing process, including protein subunit vaccines produced in Sf9 cells via baculovirus- or adenovirus-based viral vector vaccines.

The capability to make rapid and precise cell-based infectivity measurements has the potential to improve the entire vaccine development life cycle from R&D to clinical trials and manufacturing, reducing the cost and time associated with LVVs and other viral vaccines.


1. Hebert, C.G., et al., Rapid quantification of vesicular stomatitis virus in Vero cells using Laser Force Cytology™. Vaccine, 2018. 36(41): p. 6061-6069.
2. McCracken, R., et al., Rapid In-Process Measurement of Live Virus Vaccine Potency Using Laser Force Cytology™: Paving the Way for Rapid Vaccine Development. Vaccines (Basel), 2022. 10(10).
3. Hebert, C.G., et al., Viral Infectivity Quantification and Neutralization Assays Using Laser Force Cytology™, in Vaccine Delivery Technology: Methods and Protocols, B.A. Pfeifer and A. Hill, Editors. 2021, Springer US: New York, NY. p. 575-585.
4. Bommareddy, P.K., et al., MEK inhibition enhances oncolytic virus immunotherapy through increased tumor cell killing and T cell activation. Sci Transl Med, 2018. 10(471).
5. Baker, M., Reproducibility crisis: Blame it on the antibodies. Nature, 2015. 521(7552): p. 274-276.
6. Clement, N. and J.C. Grieger, Manufacturing of recombinant adeno-associated viral vectors for clinical trials. Mol Ther Methods Clin Dev, 2016. 3: p. 16002.
7. van der Loo, J.C. and J.F. Wright, Progress and challenges in viral vector manufacturing. Hum Mol Genet, 2016. 25(R1): p. R42-R52.
8. Wright, J.F., Transient transfection methods for clinical adeno-associated viral vector production. Hum Gene Ther, 2009. 20(7): p. 698-706.
9. Matsushita, T., et al., Adeno-associated virus vectors can be efficiently produced without helper virus. Gene Ther, 1998. 5(7): p. 938-45.
10. LumaCyte. Radiance® Label-Free Monitoring of AAV Transfection in HEK293 Cells Using Laser Force Cytology™ (LFCTM). June 6th 2023]


All the authors work at LumaCyte. Colin Hebert, PhD, is senior vice president, scientific and business operations. Mina Elahy, PhD, is a senior application scientist. Sean Hart, PhD, is CEO and CSO; Jonathan Turner, PhD, is an application scientist. Renee Hart is president and CBO.