Minimal or measurable residual disease (MRD) Refers to the minute number of cancer cells that remain in a patient’s body during or after treatment. Detecting MRD is critical for assessing remission depth and relapse risk. In recent years, U.S. MRD testing facilities have advanced rapidly, driven by cutting-edge technologies and innovative companies. Below we analyze the key MRD testing methodologies, leading organizations spearheading these innovations, and notable technological breakthroughs from the past five years.
According to BIS research, U.S. MRD testing market is projected to reach $1,667.5 million by 2030, growing at a CAGR of 14.18% (2024-2030).
Also Read: US MRD Testing Facilities Set for Steady Growth Over the Next 10 Years
By labeling cells with panels of antibodies, flow cytometry identifies residual cancer cells based on abnormal antigen patterns. Improved 8-10 color flow protocols (sometimes termed “next-generation flow”) can routinely detect on the order of 1 cancer cell in 10^5 normal cells. Results are rapid and quantitative, guiding treatment adjustments in real time. Flow is universally applicable in blood cancers where malignant cells show immunophenotypic differences from normal. Standard BioTools (formerly Fluidigm) provides mass cytometry systems for high-parameter single-cell protein analysis, enabling detailed MRD assessment through advanced flow cytometry.
NGS has revolutionized MRD detection by identifying tiny fractions of tumor DNA or unique clone-specific sequences. For example, targeted immunoglobulin/T-cell receptor sequencing can reach sensitivities around 10^?6. Similarly, circulating tumor DNA (ctDNA) assays in solid tumors use deep sequencing to find mutant DNA fragments in blood. NGS offers unprecedented sensitivity and can profile multiple genes, providing detailed insight into residual disease genetics. In fact, most modern MRD tests for solid tumors rely on NGS-based ctDNA detection for early relapse warning. NeoGenomics, one of an emerging players in the sector Provides comprehensive cancer diagnostic services, including MRD testing, with a focus on next generation sequencing to monitor cancer recurrence.
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Droplet digital PCR is a refined molecular method that partitions samples into thousands of microreactions to precisely count DNA molecules. This approach improves upon traditional real-time PCR by enabling absolute quantification of rare mutations or fusion transcripts. Recent studies show ddPCR significantly outperforms qPCR in MRD sensitivity and quantitative accuracy. It can detect low-level leukemia gene targets with fewer false negatives, often matching the sensitivity of flow and NGS. dPCR’s high precision makes it a powerful tool for monitoring specific oncogenic mutations (eg. NPM1 in AML or BCR-ABL in CML) during therapy. Roche introduced the Digital LightCycler System, a next generation dPCR system designed to accurately quantify trace amounts of DNA and RNA targets, enhancing MRD detection capabilities.
Artificial intelligence and machine learning are increasingly applied to enhance MRD detection. AI algorithms can automate complex flow cytometry gating, reducing analyst subjectivity and analysis time by over 80% in some cases. In sequencing-based MRD, advanced software leverages machine learning to distinguish tumor-derived DNA fragments from background noise. For example, one newly launched MRD assay uses whole-genome sequencing with AI pattern recognition to rapidly flag residual cancer signals, requiring less blood and delivering faster results. Similarly, Tempus Labs reported that its MRD test employs machine learning to improve ctDNA variant calling, boosting the precision of MRD detection in colorectal cancer patients. Such AI-driven pipelines are poised to augment human expertise, especially in interpreting the massive data generated by high-complexity MRD assays. Veracyte Utilizes artificial intelligence to enhance cancer diagnostics, offering genomic tests powered by extensive genomic and clinical data, aiding in MRD detection.
U.S. MRD testing capabilities have advanced dramatically through next-generation sequencing, refined flow cytometry, digital PCR, and AI-driven analytics. Leading diagnostics companies and research institutions are collaboratively driving these innovations from bench to bedside. The result is ever-more sensitive MRD detection across both blood cancers and solid tumors, empowering clinicians with early warning of relapse and enabling more personalized, proactive cancer care.
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