Single-Cell Multiomics for In Vivo Gene Therapy Biodistribution

This technical note outlines a single-cell multiomic framework to resolve in vivo biodistribution for a CRISPR-based Duchenne muscular dystrophy gene therapy program. Discover how to precisely map your therapy's true distribution profile, tracking cellular uptake, intracellular localization, and tissue accumulation across eight surveyed organs at single-cell resolution. By coupling genotype and phenotype within the exact same cell, this framework quantifies vehicle tropism, on- and off-target editing, and downstream transcriptional stress responses providing the granular data required to satisfy tightening regulatory safety assessments.

What you will learn

• On-target editing concentrates in skeletal myocytes and cardiomyocytes, with a measurable bystander hepatocyte fraction consistent with hepatic LNP uptake.
• Per-cell genotyping resolves the three-guide strategy (intron 44, exon 51, intron 55) and reports co-occurrence on the single X allele, which a population variant-allele frequency cannot recover.
• DNA-damage and stress pathways transcripts are read in the same cell as the edit, separating tolerated edits from those that perturb cell state.
• Germline editing sits below the detection limit, and persistence and phenotype are tracked from pre-dose to day 180.

Frequently Asked Questions

What does single-cell multiomics add to gene therapy biodistribution?

Single-cell multiomics converts a population-average distribution profile into a high-resolution map of cell-type-specific cellular uptake, tissue accumulation, and intracellular localization. By simultaneously measuring targeted DNA genotyping, targeted RNA transcripts, and cell-surface immunophenotypes within the exact same cell, single-cell multiomics pairs vehicle tropism directly with functional genomic outcomes. It enables developers to definitively resolve delivery efficiency, zygosity, and the co-occurrence of multiplex on- and off-target edits per cell, while concurrently tracking downstream transcriptional stress responses. Instead of diluting rare editing events or masking safety risks in a bulk tissue average, it provides the precise, cell-resolved evidence required for IND-enabling biodistribution packages.

How is germline transmission risk assessed for gene therapy programs?

Because systemic delivery can expose reproductive organs, evaluating germline transmission risk is a critical safety component of an in vivo biodistribution assessment. Rather than relying on whole-tissue assays that inherently dilute rare editing events, this assessment isolates and screens reproductive tissues at single-cell resolution within a unified multiomic workflow. Individual germ cells are directly profiled to measure the per-cell edited-allele fraction against a strictly defined detection threshold. In this technical note, the germline editing frequency sits entirely below the detection limit, indicating no detectable heritable risk. This granular, cell-by-cell analysis ensures that low-frequency events are not averaged away, providing the rigorous germline-tissue assessment required by current regulatory agencies.

How does single-cell multiomics address biodistribution persistence and longitudinal safety monitoring in gene therapy programs?

Evaluating how genomic and phenotypic changes evolve over time is critical for assessing long-term biodistribution persistence and establishing a safety and efficacy trajectory. Single-cell multiomics can track the longitudinal persistence of target multiplex gene edits, bystander tissue accumulation, and low-frequency off-target events over time. This approach directly links editing persistence to phenotypic stability and determines if the therapeutic effect is durable. Monitoring these cellular trajectories over time allows developers to cleanly differentiate well-tolerated tissue localization from late-emerging changes or stress responses in edited cell populations, delivering the definitive evidence required for a robust safety package.