Giovanna Prout, MBA
Chief Executive Officer
Countable Labs
Polymerase chain reaction (PCR) is a workhorse for quantifying nucleic acids across a range of applications, including biomanufacturing and clinical research for viral titer, vector copy number, residual DNA impurities in gene and cell therapy, and circulating tumor DNA and minimal residual disease in oncology. Countable Labs has developed a cutting-edge PCR platform that addresses single-molecule quantification. In this Innovation Spotlight, Giovanna Prout, chief executive officer at Countable Labs, discusses how this platform enables better sensitivity and reproducibility for single-molecule quantification across a wide range of applications.
What is the basic premise of using PCR technology in biomanufacturing and clinical research?
The basic premise is straightforward: amplify a target sequence so it can be detected and counted, then use that count to infer how much of the target was present in the original sample. In practice, two challenges define how useful that measurement actually is.
The first is rare event detection. Many of the most consequential measurements involve targets present at very low concentrations relative to background, whether that's a low-frequency variant in cell-free DNA, or a trace plasmid impurity in a vector batch. The second is reproducibility. Since most PCR methods rely on statistical inference (standard curves, Poisson corrections) rather than direct counts, run-to-run and lab-to-lab variability can make it difficult to set confident thresholds, track changes over time, or compare results across sites.
These two challenges—sensitivity for rare events, and reproducibility of the measurement itself—are where newer approaches to PCR, including single-molecule counting methods, have aimed to make the most meaningful improvements.
What are some of the main bottlenecks to achieving high sensitivity with PCR?
Most PCR methods, such as digital PCR, deliver statistical estimates, not absolute counts of molecules. Poisson statistics, standard curves, and other methods of error correction mean that data generated by these methods leaves much room for ambiguity. In applications that touch human health, like manufacturing cell and gene therapies, or measuring minimal residual disease, there’s no room for ambiguity. Additionally, technologies like digital PCR impose input limits to improve their statistical estimates. This restricts the number of molecules going into a reaction, limiting the ability to detect "needle-in-the-haystack" events.
Countable PCR’s single-molecule isolation allows for much higher input, improving the ability to detect rare molecules and events. By combining this with predesigned assays for direct single-molecule counting, Countable PCR eliminates ambiguity and delivers unbiased, absolute counts with more than ten times better sensitivity than digital PCR.
How does Countable Labs’ PCR platform address single-molecule quantification?
Countable PCR divides a sample into roughly 30 million compartments per reaction, about 1,000-fold more than digital PCR, so that individual target molecules are isolated essentially one-per-compartment. This isolation happens through a transparent, gel-like matrix generated via spin column, which spatially separates each molecule in place for direct imaging in the PCR tube after amplification.
Because each compartment reliably contains zero or one target molecule, Countable PCR doesn't need Poisson statistics to estimate concentration. Instead, it counts fluorescent signals directly, yielding an absolute molecule count. This single-molecule isolation also eliminates PCR bias, simplifying multiplex assay design, and supports a broad dynamic range, detecting anywhere from ten to one million target molecules in a single reaction. This same physical isolation also enables direct DNA linkage analysis, confirming that multiple distinct regions detected within a compartment originate from a single molecule, a capability not possible on other platforms without complex statistical frameworks.
Newer approaches to PCR, including single-molecule counting methods, aim to meaningfully improve sensitivity for rare events and measurement reproducibility.
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What types of rare events are important to identify and measure to ensure high sensitivity and what are some examples of applications?
Rare event detection and measurement is highly application specific. For example, in cell and gene therapy, it’s critical to ensure the quality and potency of the therapy with an accurate quantification of critical quality attributes, including titer, vector copy number, genome integrity, and impurities. Countable PCR's broad dynamic range and simple multiplexing allow multiple quality attributes, such as titer and impurities, to be measured in a single reaction. The technology's single-molecule linkage analysis capability, which detects multiple regions present on a single molecule, also simplifies genome integrity analysis.
Similarly, in minimal residual disease measurement, it’s critical to detect low frequency events, and to measure changes in those events over time. Countable PCR can identify rare events as low as 0.004 percent variant allele frequency, delivering more than ten times the sensitivity of other PCR technologies.
How have your customers used single-molecule precision PCR in research?
One area where Countable PCR has been advantageous is monitoring isoforms of BCR-ABL1 for chronic myeloid leukemia and acute lymphoblastic leukemia. Because there are many possible isoforms, clinical labs often need to run multiple separate PCR tests to cover them, which can introduce high run-to-run variability and erode confidence in results. With multiplexed detection on Countable PCR, labs can achieve broad coverage across BCR-ABL1 isoforms in a single reaction, with the precision of direct molecule counting.
In gene therapy, David Dobnik from the National Institute of Biology has pioneered using Countable PCR for characterizing DNA impurities during recombinant adeno-associated virus manufacturing. Conventional PCR methods can quantify residual DNA impurities from plasmids and host cell genomes, but they can't distinguish between fragmented DNA and intact sequences that retain biological activity, which are more likely to impact safety. By using single-molecule DNA linkage analysis, Dobnik's work enables a deeper risk assessment, with direct implications for quality control and process characterization in gene therapy.
