Multi-cancer early detection (MCED)

01Overview and value chain

Markers: [EC: IVDR 2017/746 | OECD: Biotech-health | Regulator: FDA (USA), EMA (European Union), NMPA (China)]

Multi-cancer early detection (MCED) screens asymptomatic, average-risk individuals from a single blood draw for molecular signals shared across dozens of cancer types simultaneously, aiming to catch cancer at an earlier, more treatable stage before symptoms or standard single-cancer screening would detect it — a population-screening use case distinct from the treatment-matched companion diagnostics covered elsewhere in this catalog. GRAIL’s Galleri test reported full results from the NHS-Galleri trial at the 2026 ASCO Annual Meeting, demonstrating a substantial reduction in stage IV cancer diagnoses, increased stage I/II detection of deadly cancers, and a four-fold higher cancer detection rate; GRAIL also presented Pathfinder 2 results from more than 35,000 participants and has submitted an FDA premarket approval (PMA) application for Galleri. Exact Sciences launched Cancerguard, which it calls the first-of-its-kind multi-cancer early detection blood test. Freenome’s SimpleScreen colorectal-cancer blood test met all primary and secondary endpoints with 85% sensitivity for CRC and 22% for advanced precancerous lesions, alongside separate multiomic blood-screening data for lung cancer. In Switzerland, Novigenix runs an AI-powered blood-transcriptomic platform with published results on early colorectal-cancer detection, recently securing funding to scale its precision-oncology platform. In China, Singlera Genomics develops multi-cancer early-screening panels including its ColonAiQ product.

The key directions of multi-cancer early detection are:

1. Cell-free DNA methylation screening (Cell-Free DNA Methylation): methylation-pattern analysis of cell-free DNA to detect and localize a cancer signal across dozens of cancer types from one blood draw — GRAIL’s Galleri.
2. Multiomic blood screening (Multiomic Blood Screening): combining genomic, proteomic and other molecular layers from blood to improve single- and multi-cancer detection sensitivity — Freenome, Exact Sciences’ Cancerguard.
3. Blood transcriptomic AI screening (Blood Transcriptomic Screening): RNA expression signatures in blood analyzed with machine learning to flag early cancer signals — Novigenix.
4. Regional MCED panels (Regional MCED Panels): multi-cancer screening products developed and validated for a domestic population and regulatory pathway — Singlera Genomics.

Sectoral value chain

[blood draw] ──> [cfDNA/multiomic/transcriptomic signal extraction] ──> [ML classifier & cancer-signal-origin prediction]
                                                    │
                                       (screening result & confirmatory workup)
                                                    │
                                                    ▼
[population screening program adoption] <─── [regulatory approval & clinical validation] <─────┘

Value chain levels

Cross-cutting technologies of the sector:

• Cell-free DNA methylation analysis (Cell-Free DNA Methylation): cancer-specific methylation patterns in cell-free DNA distinguish tumor-derived signal from background and predict the cancer’s tissue of origin, GRAIL’s core Galleri technology.
• Multiomic integration (Multiomic Blood Screening): combining multiple molecular data types (genomic, proteomic) from a single blood sample improves detection sensitivity beyond any single biomarker class, Freenome’s core approach.
• AI-based transcriptomic classification (Blood Transcriptomic Screening): machine-learning models trained on blood RNA expression signatures flag early cancer-associated immune and tissue response patterns, Novigenix’s core technology.

02US

The US anchors the deepest MCED platform bench, with large prospective trial results now driving regulatory submissions and payer conversations.

Galleri, Cancerguard, SimpleScreen, FDA

• GRAIL: reported full NHS-Galleri trial results at the 2026 ASCO Annual Meeting showing a substantial reduction in stage IV cancer diagnoses and a four-fold higher cancer detection rate, presented Pathfinder 2 results from more than 35,000 participants, and has submitted an FDA PMA application for Galleri.
• Exact Sciences: launched Cancerguard, which the company calls the first-of-its-kind multi-cancer early detection blood test.
• Freenome: its SimpleScreen colorectal-cancer blood test met all primary and secondary endpoints (85% sensitivity for CRC, 22% for advanced precancerous lesions), alongside separate multiomic lung-cancer screening data.
• FDA framework: MCED tests currently reach the US market predominantly as laboratory-developed tests (LDTs) under CLIA, with GRAIL’s Galleri PMA submission representing the category’s push toward full FDA premarket approval.

03CN

China develops domestic multi-cancer early-screening panels adapted to the local population and regulatory pathway, with Singlera Genomics among the active developers.

Singlera Genomics, NMPA

• Singlera Genomics: develops multi-cancer early-screening panels including its ColonAiQ product, part of China’s growing early-cancer-detection testing base.
• NMPA framework: multi-cancer screening tests in China require NMPA approval as in-vitro diagnostic products, validated against the domestic population’s cancer-incidence profile.

04EU

Switzerland anchors a European MCED entrant through Novigenix’s AI-powered blood-transcriptomic screening platform.

Novigenix, IVDR

• Novigenix: runs an AI-powered blood-transcriptomic platform with published results on early colorectal-cancer detection, and recently secured funding (EUR 1.8 million) to scale its precision-oncology platform and spun out an AI-focused unit to accelerate its immune-intelligence technology.
• IVDR framework: multi-cancer screening tests sold in the EU require conformity assessment and CE marking under the In Vitro Diagnostic Regulation (IVDR 2017/746), with clinical-utility evidence from large prospective trials increasingly central to that assessment.

05Leading companies and research institutes

06Tech stack and innovations

The stack converts a single blood draw into a multi-cancer signal by extracting a molecular layer (cfDNA methylation, multiomic markers, or transcriptomic RNA signatures) and classifying it with machine learning trained on large prospective screening cohorts.

1. cfDNA methylation-based detection (Cell-Free DNA Methylation):
   • GRAIL’s Galleri analyzes methylation patterns across cell-free DNA fragments to detect a shared cancer signal spanning dozens of cancer types and predict the likely tissue of origin, validated in the NHS-Galleri and Pathfinder 2 trials.
2. Multiomic blood-based screening (Multiomic Blood Screening):
   • Freenome combines genomic and proteomic signal layers from a single blood draw, achieving 85% sensitivity for colorectal cancer in its SimpleScreen test while extending the same multiomic approach to lung-cancer screening.
3. AI-powered blood transcriptomics (Blood Transcriptomic Screening):
   • Novigenix applies machine learning to blood RNA expression signatures, identifying immune and tissue-response patterns associated with early-stage colorectal cancer.
4. Domestic MCED panel development (Regional MCED Panels):
   • Singlera Genomics builds multi-cancer screening panels (including ColonAiQ) validated against China’s domestic population and regulatory requirements.

07Value chains and production pipelines

Industrial pipeline of a multi-cancer early detection test (FDA LDT/PMA / EU IVDR 2017/746)

┌───────────────────────────┐      ┌───────────────────────────┐
│ 1. Blood draw             │ ───> │ 2. Signal extraction      │
└───────────────────────────┘      └───────────────────────────┘
                                                   │
                                                   ▼
┌───────────────────────────┐      ┌───────────────────────────┐
│ 4. Screening result &     │ <─── │ 3. ML classifier &        │
│    confirmatory workup     │      │    origin prediction        │
└───────────────────────────┘      └───────────────────────────┘
              │
              ▼
┌───────────────────────────┐      ┌───────────────────────────┐
│ 5. Regulatory approval &  │ ───> │ 6. Population screening   │
│    validation               │      │    adoption                 │
└───────────────────────────┘      └───────────────────────────┘

Stage 1: Blood draw

A single venous blood sample is collected from an asymptomatic, average-risk individual as part of a routine or opt-in screening visit, requiring no prior symptom or elevated-risk trigger.

Stage 2: Signal extraction

The molecular signal is extracted from the sample — cfDNA methylation patterns (GRAIL), combined genomic/proteomic multiomic markers (Freenome), or blood transcriptomic RNA expression (Novigenix) — depending on the platform’s core technology.

Stage 3: ML classifier and origin prediction

A machine-learning classifier trained on large prospective cohorts (GRAIL’s Pathfinder 2 exceeded 35,000 participants) determines whether a cancer signal is present and predicts the likely tissue of origin to guide follow-up.

Stage 4: Screening result and confirmatory workup

A signal-detected result triggers diagnostic imaging or biopsy workup targeted at the predicted cancer origin to confirm or rule out a diagnosis; a signal-not-detected result returns the individual to standard screening guidelines.

Stage 5: Regulatory approval and validation

Large prospective trials such as NHS-Galleri and FDA PMA review (for GRAIL) or IVDR conformity assessment (for Novigenix) establish the clinical-utility evidence base required before a test is adopted into standard care.

Stage 6: Population screening adoption

Health systems and payers adopt the validated test into routine average-risk population-screening programs, the stage the NHS-Galleri trial’s stage-IV-reduction and detection-rate results are specifically designed to support.