종양학용 소프트웨어 의료기기(SaMD) 시장 : 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the software as a medical device for oncology market size is projected to expand from USD 22.22 billion in 2025 and USD 25.16 billion in 2026 to USD 46.88 billion by 2031, registering a CAGR of 23.25% between 2026 to 2031.

This report is Segmented by Application (Screening, Diagnosis and Triage, Treatment Planning, Monitoring, and More), Technology (ML, Computer Vision, NLP, Predictive Analytics), End User (Hospitals, Diagnostic Labs, Pharma, Academic Institutes), Deployment (Cloud-Based, On-Premise), and Geography (North America, Europe, Asia-Pacific, MEA, South America). Forecasts are in Value (USD).

Global Software As A Medical Device (SaMD) For Oncology Market Trends and Insights

Growing Use of AI-Based Cancer Triage and Decision Support

The Software as a Medical Device (SaMD) for oncology market is generating near-term demand from clinical decision support tools embedded directly within radiology and pathology workflows. A 2025 JAMA Network Open analysis of 222 FDA-cleared AI medical device software products showed that the 510(k) pathway had become the primary route to commercialization, helping accelerate deployment while maintaining high performance expectations. Aidoc's CARE foundation model and its broader clinical AI initiatives showed that buyers were shifting from single-use tools to platforms capable of managing multiple triage tasks through one system. This trend is significant because hospitals rarely operate a single imaging stack, making integration easier for platform vendors than for narrow algorithm suppliers and supporting larger enterprise deals over isolated department-level purchases.

Rising Need for Earlier Cancer Detection and Risk Stratification

The Software as a Medical Device (SaMD) for oncology market is gaining momentum from the shift from single-cancer screening to broader multi-cancer detection programs. GRAIL submitted the Premarket Approval application for its Galleri multi-cancer early detection test to the FDA in January 2026 under its existing Breakthrough Device Designation. At the 2026 ASCO Annual Meeting, PATHFINDER 2 results showed that Galleri increased cancer detection by more than sevenfold when added to U.S. Preventive Services Task Force-recommended screenings, while the NHS-Galleri trial reported a 25% reduction in Stage IV cancer diagnoses in the third screening year across 12 pre-specified cancer types. As these programs expand, providers need software for test result delivery, call handling, routing, tracking, and follow-up coordination, making early detection a durable demand driver even when assays and software are sold through different channels.

Fragmented Reimbursement for Oncology Software Claims

The Software as a Medical Device (SaMD) for oncology market still faces a major commercial hurdle because reimbursement rules have not kept pace with product approvals and clinical use. Oncology software vendors often must manage country-level or payer-level negotiations even after market entry. In the United States, uneven coding and payment treatment for AI-assisted digital pathology and multi-cancer early detection workflows limits adoption beyond large health systems. GRAIL's Galleri process has highlighted the gap between growing clinical evidence and the payment certainty required for large-scale screening adoption.

Other drivers and restraints analyzed in the detailed report include:

1. Expansion of Multimodal Oncology Data Platforms
2. Hospital Demand for Workflow Automation in Imaging, Pathology, and Genomics
3. High Clinical Validation Burden Across Tumor Types and Geographies

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Diagnosis and Triage held 35.45% of the Software as a Medical Device (SaMD) for oncology market share in 2025, making it the largest application area in revenue terms. The segment addressed an immediate clinical need, as radiology and pathology backlogs directly affected patient flow and treatment timelines. Paige PanCancer Detect received FDA Breakthrough Device Designation in April 2025, underscoring the value of tools that flag suspicious findings across tissue types and anatomic sites. Diagnosis and triage tools also fit existing reading workflows, which supported faster adoption than software requiring a separate review pathway.

The Software as a Medical Device (SaMD) for oncology market size for Screening and Early Detection is projected to expand at a 16.93% CAGR through 2031, making it the fastest-growing application segment. Growth is linked to multi-cancer early detection programs, AI-assisted mammography, and low-dose CT screening workflows moving toward wider deployment. Tempus launched Paige Predict in January 2026, and the platform analyzed standard H&E slides to predict 123 biomarkers across 16 cancer types using tissue that would otherwise require separate molecular assays. This launch showed how diagnosis, pathology support, and therapy selection were becoming increasingly connected through the same software base.

Machine Learning and Deep Learning represented 41.23% of revenue in 2025 and remained the core technology base for the Software as a Medical Device (SaMD) for oncology market. The segment remained anchored by deep learning methods in imaging review and newer transformer-based approaches in biomarker and genomic interpretation. Buyers drew a clearer distinction between narrow algorithms and foundation-model-style platforms, as larger models supported several downstream tasks from the same training base. Philips expanded its partnership with Ibex Medical Analytics in 2025 to strengthen AI-enabled pathology workflows and capture more software value on installed systems.

Computer Vision and Imaging AI is projected to grow at a 19.67% CAGR through 2031, making it the fastest-rising technology area. This growth reflects the shift in digital pathology and radiology from hardware-led purchases toward recurring software subscriptions and inference services. Natural Language Processing became more useful in trial matching and structured reporting, as unstructured oncology notes continued to contain important clinical details. Predictive Analytics and Risk Scoring remained smaller, but products such as SOPHiA GENETICS Digital Twins showed how software was beginning to model likely treatment response using combined genomic and clinical inputs.

Complete Report Scope:

• By Application
  • Screening and Early Detection
  • Diagnosis and Triage
  • Treatment Planning and Therapy Selection
  • Monitoring, Recurrence, and Response Assessment
  • Clinical Trial Matching and Patient Stratification
  • Pathology and Molecular Analysis Support
• By Technology
  • Machine Learning and Deep Learning
  • Computer Vision and Imaging AI
  • Natural Language Processing
  • Predictive Analytics and Risk Scoring
• By End User
  • Hospitals and Cancer Centers
  • Diagnostic Laboratories
  • Pharmaceutical and Biotechnology Companies
  • Academic and Research Institutes
• By Deployment Mode
  • Cloud-Based
  • On-Premise
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
    • Rest of Asia-Pacific
  • Middle East and Africa
    • GCC
    • South Africa
    • Rest of Middle East and Africa
  • South America
    • Brazil
    • Argentina
    • Rest of South America

Geography Analysis

North America held 41.52% of the Software as a Medical Device (SaMD) for oncology market share in 2025, making it the clear regional leader. The region benefited from a mature FDA pathway, strong venture and strategic capital support, and health systems familiar with software subscriptions in clinical settings. The Federal Register final order issued in June 2026 for radiological machine learning-based quantitative imaging software provided a clearer regulatory base for a key market segment. Lunit reported more than 330 screening sites and approximately 1 million annual mammography screenings across the Americas in April 2026, showing that cleared oncology AI tools were moving into population-scale use.

Europe remained the second-largest region in the Software as a Medical Device (SaMD) for oncology market, supported by established oncology care networks in Germany, the United Kingdom, and France. The region combined strong demand for clinically validated tools with a stricter compliance culture, raising barriers to entry while favoring well-prepared vendors. The NHS-Galleri trial results presented in 2026 strengthened the United Kingdom's role as an important test bed for software-enabled multi-cancer screening pathways. Europe remained important due to its revenue base and the influence of its regulatory and public health decisions on deployment standards in other regions.

Asia-Pacific is projected to grow at a 17.56% CAGR through 2031, making it the fastest-growing regional segment in the Software as a Medical Device (SaMD) for oncology market. The region is expanding from a lower installed base, supported by rising cancer care demand, growing digital health investment, and active local developer ecosystems. Hospitals and laboratories are adopting these tools to manage higher diagnostic volumes amid limited specialist capacity. Outside the major markets, the Middle East and Africa remain at an earlier stage, but modernization programs and hospital-level deployments are beginning to create measurable demand.

1. Aidoc Medical Ltd.
2. Caris Life Sciences, Inc.
3. DeepBio Inc.
4. Exact Sciences
5. GE HealthCare Technologies Inc.
6. GRAIL, Inc.
7. Ibex Medical Analytics Ltd.
8. Koninklijke Philips
9. Lunit
10. Median Technologies
11. Nucleix Ltd.
12. Oncora Medical, Inc.
13. Paige.AI, Inc.
14. PathAI, Inc.
15. Roche
16. Siemens Healthineers
17. SOPHiA GENETICS SA
18. Tempus AI, Inc.
19. Viz.ai, Inc.
20. Volpara Health Technologies Limited

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Growing Use of AI-Based Cancer Triage and Decision Support
  • 4.2.2 Regulatory Preference for SaMD With Traceable Clinical Evidence
  • 4.2.3 Expansion of Multimodal Oncology Data Platforms
  • 4.2.4 Hospital Demand for Workflow Automation in Imaging, Pathology, and Molecular Oncology
  • 4.2.5 Rising Need for Earlier Cancer Detection and Risk Stratification
  • 4.2.6 Increasing Use of Software to Support Precision Oncology and Therapy Selection
• 4.3 Market Restraints
  • 4.3.1 Fragmented Reimbursement for Oncology Software Claims
  • 4.3.2 High Clinical Validation Burden Across Tumor Types and Geographies
  • 4.3.3 Data Access Constraints Across Imaging, Pathology, and Genomics Silos
  • 4.3.4 Compliance Complexity Due to Evolving AI and Medical Device Regulations
• 4.4 Value Chain and Supply Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Buyers
  • 4.7.2 Bargaining Power of Suppliers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Industry Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE, USD)

• 5.1 By Application
  • 5.1.1 Screening and Early Detection
  • 5.1.2 Diagnosis and Triage
  • 5.1.3 Treatment Planning and Therapy Selection
  • 5.1.4 Monitoring, Recurrence, and Response Assessment
  • 5.1.5 Clinical Trial Matching and Patient Stratification
  • 5.1.6 Pathology and Molecular Analysis Support
• 5.2 By Technology
  • 5.2.1 Machine Learning and Deep Learning
  • 5.2.2 Computer Vision and Imaging AI
  • 5.2.3 Natural Language Processing
  • 5.2.4 Predictive Analytics and Risk Scoring
• 5.3 By End User
  • 5.3.1 Hospitals and Cancer Centers
  • 5.3.2 Diagnostic Laboratories
  • 5.3.3 Pharmaceutical and Biotechnology Companies
  • 5.3.4 Academic and Research Institutes
• 5.4 By Deployment Mode
  • 5.4.1 Cloud-Based
  • 5.4.2 On-Premise
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 Europe
    • 5.5.2.1 Germany
    • 5.5.2.2 United Kingdom
    • 5.5.2.3 France
    • 5.5.2.4 Italy
    • 5.5.2.5 Spain
    • 5.5.2.6 Rest of Europe
  • 5.5.3 Asia-Pacific
    • 5.5.3.1 China
    • 5.5.3.2 India
    • 5.5.3.3 Japan
    • 5.5.3.4 Australia
    • 5.5.3.5 South Korea
    • 5.5.3.6 Rest of Asia-Pacific
  • 5.5.4 Middle East and Africa
    • 5.5.4.1 GCC
    • 5.5.4.2 South Africa
    • 5.5.4.3 Rest of Middle East and Africa
  • 5.5.5 South America
    • 5.5.5.1 Brazil
    • 5.5.5.2 Argentina
    • 5.5.5.3 Rest of South America

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Market Share Analysis
• 6.3 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.3.1 Aidoc Medical Ltd.
  • 6.3.2 Caris Life Sciences, Inc.
  • 6.3.3 DeepBio Inc.
  • 6.3.4 Exact Sciences Corporation
  • 6.3.5 GE HealthCare Technologies Inc.
  • 6.3.6 GRAIL, Inc.
  • 6.3.7 Ibex Medical Analytics Ltd.
  • 6.3.8 Koninklijke Philips N.V.
  • 6.3.9 Lunit Inc.
  • 6.3.10 Median Technologies
  • 6.3.11 Nucleix Ltd.
  • 6.3.12 Oncora Medical, Inc.
  • 6.3.13 Paige.AI, Inc.
  • 6.3.14 PathAI, Inc.
  • 6.3.15 Roche Holding AG
  • 6.3.16 Siemens Healthineers AG
  • 6.3.17 SOPHiA GENETICS SA
  • 6.3.18 Tempus AI, Inc.
  • 6.3.19 Viz.ai, Inc.
  • 6.3.20 Volpara Health Technologies Limited

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White Space and Unmet Need Assessment