Progress in pre-clinical studies on (predominantly CAR T) cell therapy has introduced some significant challenges for the pharmaceutical industry to reliably manufacture a save product for large numbers of patients. At the center of these challenges lies the question of how a specific therapeutic cell product should be defined and thus the search for product characterization methods that fit manufacturing settings is on. In bulk analysis methods, cells are measured collectively. Single-cell analysis methods perform measurements on individual cells. While bulk analysis provides an average result about the entire cell sample, single-cell analysis reveals heterogeneity.

Innovations in quantitative PCR, protein labeling and data analysis methods have made it possible to perform genomic and transcriptomic assays at the single-cell level (e.g. Multiple Annealing and Looping-Based Amplification Cycles (MALBAC), Fluorescence In Situ Sequencing (FISSEQ), Smart-seq2, seqFISH, sci-RNA-seq, Seq-Well, etc).

Single-cell proteomic (and metabolic) assays are generally performed by means of microscopy and light- or mass-based flow cytometry. Through simultaneous, multi-parameter measurements on individual cells, cell samples are characterized with a mixture of different fluorochrome-conjugated antibodies (antibody panel) known (or assumed) to be specific for proteins present intracellularly and/or on the surface of the cell membrane. Flow cytometry is a single-cell analytical technology that enables measurements on millions of cells in less than a minute. These quick, multi-parameter measurements allow for the identification of cell types that are present in very small (i.e. rare cell populations) as well as in large numbers. A typical rare cell population accounts for 1 % of the sample measured, but high-parameter flow cytometry allows for reliable identification of cell types comprising as little as 0.001% of the sample. In addition to the presence or absence of proteins, flow cytometry can also be used to measure the relative amount of proteins on or in cells (quantitative flow cytometry). Lastly, flow cytometry can be used to physically select specific cell types to obtain cell populations purified for particular cell characteristics (fluorescence activated cell sorting, or FACS). Improvements in the technology have resulted in commercially available light-based flow cytometers that are capable of measuring up to 30 parameters simultaneously for large numbers of cells on individual cells, while mass-based flow cytometers may be able to measure over 200 parameters simultaneously.

A flow cytometric assay is validated using reference material. Because there is no true standard reference material for flow cytometric assays, the type of reference material is determined by the assay. However, in clinical assays, fresh or stabilized ‘normal’ cells from ‘healthy’ donors is commonly used for comparison. The need for more appropriate (standard) reference material is certainly an important topic to discuss in light of product characterization in commercial cell therapy.

Aside from a lack of standard reference material, improper use of controls is adding a significant degree of variability and risk of error to flow cytometric data analysis. A specific example is the use of so called isotype controls (i.e. an antibody with the same isotype as the test antibody but raised against a target that is not present in the test sample). Although the flow cytometry community enjoys an increasing awareness of the limited value isotype controls offer, there is still a widespread misunderstanding about how flow cytometry data obtained with isotype controls should be used to accurately determine the composition of therapeutic cell products. Improper (use of) reference material and controls may result in serious mischaracterization of a therapeutic cell product – in particular with products that may contain rare subpopulations of cell types that harm the patient. While a typical therapeutic cell product consists of millions of cells, it may take only 1 cell to cause an effect. Hence, rare cell analysis by means of single-cell analytics on large numbers of cells plays an important role in product characterization.