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Push residual disease detection a hundredfold deeper with whole-genome methods

Current blood tests miss leftover cancer in many patients. Reading thousands of mutations at once, rather than a few dozen, can detect far smaller amounts.

Whole-genome and error-corrected duplex approaches integrate signal across thousands to millions of tumour-specific sites, plus fragmentomic and methylation features, reaching detection limits reported near one part per million in research settings. Cost, turnaround and bioinformatics reproducibility are the barriers, not biology. If the limit of detection falls by two orders of magnitude, ctDNA-negative results become genuinely informative.

Hypothesis
Genome-wide MRD detection lowers the limit of detection by at least fiftyfold versus fixed panels, raising sensitivity for relapse at the six-month landmark above 90% while keeping specificity above 99%.
Rationale
Signal integration across many loci is a statistical rather than chemical improvement, so it scales with sequencing cost, which continues to fall. The same logic transformed non-invasive prenatal testing.
What would test it
Retrospective head-to-head on banked serial plasma from an adjuvant cohort with known outcomes, comparing panel and genome-wide assays on identical samples; then prospective validation within an MRD platform.
Maturity
early clinical
Who has to act
data
Cost to try
Medium ($1M to $50M)
Years to first evidence
4
Bottlenecks it attacks

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