CAR T therapies are complex, heterogeneous cell products, but many standard analytical methods still report only population-level averages. In vector copy number analysis, that means a product can appear acceptable overall while still containing individual cells with higher levels of vector integration which can be dangerous or lower levels that can be not as effective.
In a recent study, Mission Bio and collaborators used the Tapestri single-cell multiomic platform to measure vector copy number, surface protein expression, and vector integrity in individual CAR T cells. The approach showed how single-cell analysis can reveal high-copy outliers and lineage-specific integration patterns that bulk methods may miss.
Here, Mike Molnar, Senior Marketing Manager at Mission Bio, discusses the role of single-cell multiomics in CAR T characterization, manufacturing control, and safety assessment.
What inspired this research into single-cell analysis for CAR-T therapy characterization?
Mission Bio began working with cell therapy companies to first understand transduction assays at single cell level, but knowing how many cells were transduced told only part of the story. The deeper, more impactful cell therapy manufacturing question was how many vector copies had integrated into each individual cell and how this influenced the surface receptors on the final cell therapy product.
Vector Copy Number (VCN) had become one critical quality attribute that the field couldn't adequately measure using legacy methods, making the stakes even higher as regulatory agencies become more critical on the safety of these therapies. Cells harboring VCN >5 carry an elevated risk of insertional oncogenesis and genotoxicity, yet conventional legacy bulk methods like ddPCR and qPCR report only population averages, leaving these dangerous outliers completely invisible.
Furthermore, pairing this single-cell VCN analysis with immunophenotyping within the same assay allows developers to directly correlate specific VCN with the expression of key surface receptors, providing a comprehensive safety and functional profile of the final cell therapy product.
The limitation – of what legacy bulk methods report and what therapy developers need to know to validate the safety of the cell therapy product – is what drove Mission Bio to expand the single-cell platform to include full VCN profiling and immunophenotyping of each cell within the same assay, to help cell therapy companies develop safer therapies.
Why is analytical data so important in the development and manufacture of CAR T therapies?
Because CAR-T therapies are heterogeneous living drugs manufactured to include complex genetic modifications, precise single-cell analytical data is the only way to overcome insufficient population averages and verify the exact composition of the final dose before it reaches a patient. By leveraging Mission Bio’s Tapestri single-cell VCN capabilities, the single-cell analytical data produced informs decision-making across three critical aspects of a cell therapy product development: safety, potency, and process control.
From a safety perspective, legacy bulk assays like ddPCR only provide a population-wide average, but Mission Bio’s Tapestri single-cell VCN profiling can accurately detect rare, individual cells harboring dangerously high vector insertions (e.g., VCN >5) that carry an elevated risk of genotoxicity and insertional oncogenesis.
In terms of potency, rather than guessing at the distribution of vector copies, single-cell VCN analysis accurately quantifies the true ratio of successfully transduced functional cells against un-transduced non-potent cells (VCN = 0), ensuring the final product meets the required clinical efficacy thresholds.
Finally, for process control, knowing the exact dynamics of viral integration at the individual cell level provides the precise feedback developers need to confidently make manufacturing process changes such as tune viral titer dosing, refine transduction protocols, and maintain strict, reproducible batch-to-batch quality.
What are the limitations of looking only at population-level or average measurements in complex cell therapies?
Relying on bulk, population-level averages like standard qPCR or ddPCR fundamentally obscures the cellular heterogeneity inherent in cell therapies. A single mean value may suggest that a product falls within an acceptable range, while hiding rare subpopulations with multiple integration events. For example, a known "safe" average VCN of 1.5 can easily mask individual cells harboring a VCN >5. Since insertional mutagenesis originates at the single-cell level, missing these high-VCN outliers leaves a critical safety risk unmeasured.
In addition, because bulk VCN is calculated across the entire cell population, untransduced cells (VCN = 0) mathematically dilute the average, which can lead to a systemic underestimation of the true vector burden in modified cells.
At the same time, two therapy batches with identical bulk VCNs can possess completely different single-cell genetic makeup. A batch where 100 percent of cells have 1 vector copy is biologically distinct from a batch where 50 percent have 2 copies and 50 percent remain untransduced. Averages cannot resolve these differences, making it impossible to correlate integration dynamics with surface receptor expression or overall functional potency.
How can single-cell multiomics give developers a clearer picture of product quality, consistency, and safety?
Single-cell multiomics provides a clear link between genotype and phenotype. DNA and protein analysis in the same assay at the single-cell level allowsVCN to be assessed within specific cell subsets such as – CD4+ or CD8+ T cells – to directly connect integration data to therapeutic function simultaneously, covering T cell phenotype, exhaustion state, and CAR expression all from a single sample input.
Tapestri's single-cell targeted DNA + RNA assay takes characterization of cell therapy products a step further. For developers working with CRISPR-edited or multiplexed-engineered cell therapies, it is no longer sufficient to confirm just that an edit occurred because regulators and developers need to know what that edit does to the cell. By simultaneously capturing genomic edit status (zygosity, on- and off-target co-occurrence) and functional transcriptional output in the same cell, Tapestri can directly link a specific editing event – say, a biallelic TRAC knockout – to its downstream gene expression consequences. For CAR-T developers, this means being able to confirm not just that cells were transduced or edited, but that the therapeutic modification is functioning as intended at the transcriptional level within each cell, providing a far more rigorous and complete definition of product potency and safety. Our recent presentation at ASGCT 2026 highlighted the impact of single-cell targeted DNA + RNA profiling within key phases of cell therapy production, further validating the need of targeted transcriptional assessments in CRISPR-edited T cells.
What are the potential implications of this work for CAR-T manufacturers, regulators, and ultimately patients?
Cell therapy developers can consolidate separate legacy methods that evaluate genotype and phenotype to assess critical quality attributes (CQA) into a single assay with single-cell resolution. This provides essential data to evaluate CQAs like single-cell VCN and surface receptor expression, reducing analytical turnaround times and generating precise quantitative metrics for process development and lot release.
Agencies, on the other hand, receive exact single-cell VCN distributions instead of population averages. This granular data regarding cellular heterogeneity and vector integration profiles provides the evidence required for rigorous risk assessments for IND and BLA submissions. Mission Bio has already helped clients build FDA briefing packages using Tapestri data.
For patients, individuals receive more thoroughly characterized therapies. Because single-cell analysis identifies high-VCN outlier cells that evade detection in legacy bulk methods, developers can enforce strict, data-driven product release criteria to directly mitigate the risk of insertional oncogenesis and genotoxicity.
Looking ahead, how do you see single-cell approaches shaping the future of cell therapy development and quality control?
I believe single-cell assays will transition from exploratory characterization tools into validated lot release assays. Implementing standardized single-cell multiomic assays directly within GxP environments will enable highly precise, reproducible cell therapy product release criteria based on actual single-cell genotypic and phenotypic profiles rather than reporting by legacy methods, which has proven time and again to be risky for cell therapy programs.
Moreover, as new cell therapies incorporate multiplex gene editing and dual-CAR constructs, single-cell multiomics will be required to verify the co-occurrence of genetic modifications alongside transcription targets and surface proteins. This simultaneous profiling confirms that complex edits are correctly assembled and functionally active within specific cellular subsets and identifies those subsets that pose safety and genotoxicity risk.
Beyond manufacturing, single-cell multiomics has the ability to support long-term patient follow-up. By tracking in vivo cellular biodistribution, clonal expansion dynamics, and specific integration sites over time, developers can accurately monitor therapeutic persistence, identify the early onset of clonal dominance, and detect potential secondary malignancies prior to clinical manifestation.
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