Photo of a single-cell analysis.
Roughly 40 percent of all clinical holds last year happened in trials for cell and gene therapies.
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Safety Issues Plague Cell and Gene Therapy Trials. Single-Cell Analysis Can Help

Single-cell DNA and omic characterization can help avoid costly clinical holds and potential harm to patients

Brittany Enzmann, PhD

Brittany Enzmann, PhD, is a product manager at Mission Bio, which is pioneering high-throughput single-cell DNA and multi-omics analysis for cell and gene therapies and beyond.

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Published:Jul 18, 2022
|Updated:Jul 19, 2022
|4 min read
Photo portrait of Brittany Enzmann
Brittany Enzmann, PhD, is a product manager at Mission Bio, which is pioneering high-throughput single-cell DNA and multi-omics analysis for cell and gene therapies and beyond.

Cell and gene therapies are some of the most promising treatments in development, but clinical holds are stalling their progress. That’s because safety concerns are often identified after treatments reach the clinic. Characterizing therapies at the single-cell level before entering clinical trials—and as early as preclinical studies—could help developers avoid costly clinical holds and get treatments in the hands of patients quickly and safely.

Why safety concerns are pervasive with cell and gene therapies

A recent uptick in clinical holds on cell and gene therapy trials underscores the danger and time-consuming challenges of identifying risks after therapies are being tested in patients.

According to Jefferies analyst Michael Yee, cell and gene therapies experience safety issues leading to clinical holds at a higher rate than other therapies. Roughly 40 percent of all clinical holds last year happened in trials for cell and gene therapies; and those holds lasted, on average, 145 days.

Part of the problem may be the expedited development of many of these therapies without adequate characterization. Often considered “living drugs,” cell and gene therapies are intrinsically more complex than small molecule drugs. Cells that are engineered to provide a therapeutic benefit, for instance, comprise myriad interacting molecules and can change as a function of their environment. Furthermore, the genetic modification of these cells only increases their heterogeneity.

Failure to adequately understand this heterogeneity can have ramifications for patient safety. For example, therapies that involve the integration of a transgene into the genome (e.g., by lentivirus) have the potential to cause cancer if not assessed properly. The more vector copies that integrate into the genome of host cells, the higher the risk of insertional mutagenesis. Other vectors, like recombinant adeno-associated virus (rAAV)—commonly used for in vivo gene therapies—are considered relatively safe because they rarely integrate into the genome. But animal studies have shown cancer and liver toxicities occur alongside rAAV integration, raising red flags for the FDA.

Additionally, if a therapy is engineered with gene editing tools like CRISPR, off-target edits can disrupt important genes, and unintended translocations can dysregulate normal gene function—even leading to the expression of oncogenic fusion genes.

Because the cell and gene therapy field is relatively young and rapidly evolving, there is no standard technology or level of resolution in regards to best practices for safety assessments. The FDA released draft recommendations for gene therapies that incorporate genome editing, as well as for CAR T-cell development in March, which was a step in the right direction. The agency has called for companies to optimize their genome editing components to reduce the potential for off-target modifications and called for patients treated with gene-edited therapies to be followed for at least 15 years.

Conventional methodologies used for cell and gene therapy characterization include bulk technologies that report population averages. This broad-view analysis, however, can allow a small number of potentially dangerous cells to slip through the cracks. For example, if cells with high vector copy number are rare in a population of cells, bulk analysis methods might not identify a problem—but those few cells could still cause issues in patients.

Single-cell DNA sequencing has the sensitivity to capture these rare cells, as well as cell-to-cell variation in other attributes. That means that even if only a few cells in a population have a potentially dangerous mutation, single-cell analysis can identify them.

How single-cell analysis can smooth the path to approval

Single-cell data has an advantage over bulk methods because it offers greater resolution. Comprehensive characterization early in preclinical development can help identify critical quality attributes (CQAs)—criteria for ensuring a product’s identity, potency, purity, and safety. Well-defined CQAs ensure quality control throughout product and process development, and can help companies avoid costly surprises and preventable complications later in clinical stages.

Currently, if there’s a report of an adverse reaction or the development of cancer in a patient in a cell or gene therapy clinical trial, the FDA launches an investigation. In that case, the trial is paused for months at a time, so the agency can determine if the therapy was the cause.

But if the developer was already equipped with a detailed, cell-by-cell data profile, they could quickly rule out whether the therapy was the cause of the safety concern. The key is to characterize well, and to do it early.

In addition to increasing the resolution at which researchers can scrutinize cells, single-cell analysis also reduces the time, number of instruments, and personnel needed to run assays. Instead of splitting a sample across disparate assays and analyzing them separately, attributes can be co-measured at the same time in the same cells. Additionally, single-cell analysis offers a speed advantage because it doesn’t require colony picking or clonal outgrowth. By skipping that step, thousands of individual cells can be analyzed in a matter of days, rather than weeks.

The wider availability of innovative analytics tools and their ability to reduce risk in the drug development process is likely to fuel more cell and gene therapy companies to adopt single-cell characterization as a preclinical best practice.