환자 유래 이종이식 모델 시장 규모, 점유율, 동향 분석 보고서 : 종양 유형별, 모델 유형별, 최종 용도별, 지역별, 부문별 예측(2025-2030년)

Patient-derived Xenograft Model Market Growth & Trends:

The global patient-derived xenograft model market size is expected to reach USD 505.3 million in 2030 and is projected to grow at a CAGR of 9.64% from 2025 to 2030. Growing burden of cancer, which is promoting the demand for new treatment options, along with significant demand for personalized therapies worldwide will boost the growth of the industry. Patient-derived Xenograft (PDX) models have garnered increasing awareness during the past decade. These types are typically characterized by the introduction of fresh immunodeficient mice with patient-derived tumor tissues. These models have been used with efficacy in preclinical studies to identify prospective biomarkers for drug response and resistance, as well as to monitor the development of tumors in therapy response. The concept of a co-clinical study, which involves using several models at once-referred to as "Avatar models"-has recently grown in popularity and has been expanded to incorporate PDX models.

Moreover, PDX models were used in a few prospective trials to direct therapeutic therapy decisions for a limited number of patients with confirmed extended survival. The COVID-19 pandemic had a negative impact on the industry. It disrupted the clinical trials and also reduced the productivity of pharmaceutical & biopharmaceutical companies. According to research by Avantor Sciences, 70% of global clinical trials were disrupted as of July 2020. 369 trials related to oncology had been delayed in the USA alone, central nervous system trials at 223, gastrointestinal trials at 116, and cardiovascular trials at 99. Despite COVID-19, the rising number of cancer cases & increased R&D activities by pharmaceutical companies will contribute to the growth of the market. For instance, as per the GLOBOCAN Report 2020, 19.3 million new cancer cases and almost 10.0 million cancer deaths occurred in 2020. The majorly impacted cancers were breast, lung, colorectal, and prostate cancer.

Patient-derived Xenograft Model Market Report Highlights:

• The breast cancer segment dominated with 31.7% of the revenue share in 2024 owing to increasing cases of breast cancer globally.
• For instance, female breast cancer is expected 2.3 million new cases & has surpassed lung cancer as the most prevalent disease diagnosed.
• The mice model segment dominated the market in 2024. Mice are the most commonly used species for xenograft studies due to their well-established immunodeficient strains, cost-effectiveness, and ease of handling.
• The CRO and CDMO segment dominated the market in 2024 owing to increasing outsourcing activities by pharmaceutical and biotechnology companies for research and development activities.
• Pharmaceutical and biopharmaceutical companies are projected to witness considerable growth from 2025 to 2030 owing to the increasing demand for more accurate and reliable preclinical models to advance drug discovery and development.
• North America patient-derived xenograft model market dominated the global market and accounted for a 44.6% share in 2024.

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
• 1.2. Market Definitions
  • 1.2.1. Tumor Type
  • 1.2.2. Model Type
  • 1.2.3. End Use
• 1.3. Research Methodology
• 1.4. Information Procurement
  • 1.4.1. Purchased Database
  • 1.4.2. GVR's Internal Database
  • 1.4.3. Secondary Sources
  • 1.4.4. Primary Research
• 1.5. Market Formulation & Validation
• 1.6. Model Details
  • 1.6.1. Commodity Flow Analysis
  • 1.6.2. Bottom-up Approach
• 1.7. List of Secondary Sources
• 1.8. List of Abbreviations
• 1.9. Objectives

Chapter 2. Executive Summary

• 2.1. Market Outlook
• 2.2. Segment Snapshot
• 2.3. Competitive Landscape Snapshot

Chapter 3. Patient-derived Xenograft Model Market Variables, Trends & Scope

• 3.1. Market Lineage Outlook
  • 3.1.1. Parent market outlook
  • 3.1.2. Related/ancillary market outlook.
• 3.2. Market Dynamics
  • 3.2.1. Market Driver Analysis
    • 3.2.1.1. Growing Burden of Cancer Across the Globe
    • 3.2.1.2. Increasing R&D Investment for Cancer Research
    • 3.2.1.3. Demand for Personalized Therapies Worldwide
  • 3.2.2. Market Restraint Analysis
    • 3.2.2.1. High Cost of Personalized PDX Models
    • 3.2.2.2. Stringent Regulations Towards the Use of Animal Models
• 3.3. Market Analysis Tools
  • 3.3.1. Porter's Five Forces Analysis
  • 3.3.2. PESTEL Analysis
  • 3.3.3. COVID-19 Impact Analysis

Chapter 4. Patient-derived Xenograft Model Market: Tumor Type Estimates & Trend Analysis

• 4.1. Segment Dashboard
• 4.2. Global Patient-derived Xenograft Model Market; Tumor Type Movement Analysis
• 4.3. Global Patient-derived Xenograft Model Size & Trend Analysis, by Tumor Type, 2018 to 2030 (USD Million)
• 4.4. Lung Cancer
  • 4.4.1. Lung cancer market estimates and forecasts 2018 to 2030 (USD Million)
• 4.5. Pancreatic Cancer
  • 4.5.1. Pancreatic cancer market estimates and forecasts 2018 to 2030 (USD Million)
• 4.6. Prostate Cancer
  • 4.6.1. Prostate cancer market estimates and forecasts 2018 to 2030 (USD Million)
• 4.7. Breast Cancer
  • 4.7.1. Breast cancer market estimates and forecasts 2018 to 2030 (USD Million)
• 4.8. Others
  • 4.8.1. Others market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 5. Patient-derived Xenograft Model Market: Model Type Estimates & Trend Analysis

• 5.1. Segment Dashboard
• 5.2. Global Patient-derived Xenograft Model Market; Model Type Movement Analysis
• 5.3. Global Patient-derived Xenograft Model Size & Trend Analysis, by Model Type, 2018 to 2030 (USD Million)
• 5.4. Mice Model
  • 5.4.1. Mice model market estimates and forecasts 2018 to 2030 (USD Million)
• 5.5. Rat Model
  • 5.5.1. Rat model market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 6. Patient-derived Xenograft Model Market: End Use Estimates & Trend Analysis

• 6.1. Segment Dashboard
• 6.2. Global Patient-derived Xenograft Model Market; End Use Movement Analysis
• 6.3. Global Patient-derived Xenograft Model Size & Trend Analysis, by End Use, 2018 to 2030 (USD Million)
• 6.4. Pharmaceutical and Biopharmaceutical Companies
  • 6.4.1. Pharmaceutical and biopharmaceutical companies market estimates and forecasts 2018 to 2030 (USD Million)
• 6.5. Academic and Research Institutes
  • 6.5.1. Academic and research institutes market estimates and forecasts 2018 to 2030 (USD Million)
• 6.6. CRO's and CDMO's
  • 6.6.1. CRO's and CDMO's market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 7. Patient-derived Xenograft Model Market: Regional Estimates & Trend Analysis

• 7.1. Regional Market Share Analysis, 2024 & 2030
• 7.2. Regional Market Dashboard
• 7.3. North America
  • 7.3.1. North America Market Estimates and Forecasts 2018 to 2030 (USD Million)
  • 7.3.2. U.S.
    • 7.3.2.1. Key country dynamics
    • 7.3.2.2. Competitive scenario
    • 7.3.2.3. Regulatory framework
    • 7.3.2.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.3.3. Canada
    • 7.3.3.1. Key country dynamics
    • 7.3.3.2. Competitive scenario
    • 7.3.3.3. Regulatory framework
    • 7.3.3.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.3.4. Mexico
    • 7.3.4.1. Key country dynamics
    • 7.3.4.2. Competitive scenario
    • 7.3.4.3. Regulatory framework
    • 7.3.4.4. Mexico market estimates and forecasts 2018 to 2030 (USD Million)
• 7.4. Europe
  • 7.4.1. Europe Market Estimates and Forecasts 2018 to 2030 (USD Million)
  • 7.4.2. UK
    • 7.4.2.1. Key country dynamics
    • 7.4.2.2. Competitive scenario
    • 7.4.2.3. Regulatory framework
    • 7.4.2.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.4.3. Germany
    • 7.4.3.1. Key country dynamics
    • 7.4.3.2. Competitive scenario
    • 7.4.3.3. Regulatory framework
    • 7.4.3.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.4.4. France
    • 7.4.4.1. Key country dynamics
    • 7.4.4.2. Competitive scenario
    • 7.4.4.3. Regulatory framework
    • 7.4.4.4. France market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.4.5. Italy
    • 7.4.5.1. Key country dynamics
    • 7.4.5.2. Competitive scenario
    • 7.4.5.3. Regulatory framework
    • 7.4.5.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.4.6. Spain
    • 7.4.6.1. Key country dynamics
    • 7.4.6.2. Competitive scenario
    • 7.4.6.3. Regulatory framework
    • 7.4.6.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.4.7. Denmark
    • 7.4.7.1. Key country dynamics
    • 7.4.7.2. Competitive scenario
    • 7.4.7.3. Regulatory framework
    • 7.4.7.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.4.8. Sweden
    • 7.4.8.1. Key country dynamics
    • 7.4.8.2. Competitive scenario
    • 7.4.8.3. Regulatory framework
    • 7.4.8.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.4.9. Norway
    • 7.4.9.1. Key country dynamics
    • 7.4.9.2. Competitive scenario
    • 7.4.9.3. Regulatory framework
    • 7.4.9.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
• 7.5. Asia Pacific
  • 7.5.1. Asia Pacific Market Estimates and Forecasts 2018 to 2030 (USD Million)
  • 7.5.2. Japan
    • 7.5.2.1. Key country dynamics
    • 7.5.2.2. Competitive scenario
    • 7.5.2.3. Regulatory framework
    • 7.5.2.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.5.3. China
    • 7.5.3.1. Key country dynamics
    • 7.5.3.2. Competitive scenario
    • 7.5.3.3. Regulatory framework
    • 7.5.3.4. China market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.5.4. India
    • 7.5.4.1. Key country dynamics
    • 7.5.4.2. Competitive scenario
    • 7.5.4.3. Regulatory framework
    • 7.5.4.4. India market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.5.5. Australia
    • 7.5.5.1. Key country dynamics
    • 7.5.5.2. Competitive scenario
    • 7.5.5.3. Regulatory framework
    • 7.5.5.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.5.6. South Korea
    • 7.5.6.1. Key country dynamics
    • 7.5.6.2. Competitive scenario
    • 7.5.6.3. Regulatory framework
    • 7.5.6.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.5.7. Thailand
    • 7.5.7.1. Key country dynamics
    • 7.5.7.2. Competitive scenario
    • 7.5.7.3. Regulatory framework
    • 7.5.7.4. Thailand market estimates and forecasts 2018 to 2030 (USD Million)
• 7.6. Latin America
  • 7.6.1. Latin America Market Estimates and Forecasts 2018 to 2030 (USD Million)
  • 7.6.2. Brazil
    • 7.6.2.1. Key country dynamics
    • 7.6.2.2. Competitive scenario
    • 7.6.2.3. Regulatory framework
    • 7.6.2.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.6.3. Argentina
    • 7.6.3.1. Key country dynamics
    • 7.6.3.2. Competitive scenario
    • 7.6.3.3. Regulatory framework
    • 7.6.3.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
• 7.7. MEA
  • 7.7.1. MEA Market Estimates and Forecasts 2018 to 2030 (USD Million)
  • 7.7.2. South Africa
    • 7.7.2.1. Key country dynamics
    • 7.7.2.2. Competitive scenario
    • 7.7.2.3. Regulatory framework
    • 7.7.2.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.7.3. Saudi Arabia
    • 7.7.3.1. Key country dynamics
    • 7.7.3.2. Competitive scenario
    • 7.7.3.3. Regulatory framework
    • 7.7.3.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.7.4. UAE
    • 7.7.4.1. Key country dynamics
    • 7.7.4.2. Competitive scenario
    • 7.7.4.3. Regulatory framework
    • 7.7.4.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
  • 7.7.5. Kuwait
    • 7.7.5.1. Key country dynamics
    • 7.7.5.2. Competitive scenario
    • 7.7.5.3. Regulatory framework
    • 7.7.5.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 8. Competitive Landscape

• 8.1. Company Categorization
• 8.2. Company Market Position Analysis, 2024
• 8.3. Company Profiles
  • 8.3.1. Charles River Laboratories
    • 8.3.1.1. Company overview
    • 8.3.1.2. Financial performance
    • 8.3.1.3. Service benchmarking
    • 8.3.1.4. Strategic initiatives
  • 8.3.2. The Jackson Laboratory
    • 8.3.2.1. Company overview
    • 8.3.2.2. Financial performance
    • 8.3.2.3. Service benchmarking
    • 8.3.2.4. Strategic initiatives
  • 8.3.3. Crown Bioscience
    • 8.3.3.1. Company overview
    • 8.3.3.2. Financial performance
    • 8.3.3.3. Service benchmarking
    • 8.3.3.4. Strategic initiatives
  • 8.3.4. Altogen Labs
    • 8.3.4.1. Company overview
    • 8.3.4.2. Financial performance
    • 8.3.4.3. Service benchmarking
    • 8.3.4.4. Strategic initiatives
  • 8.3.5. Envigo
    • 8.3.5.1. Company overview
    • 8.3.5.2. Financial performance
    • 8.3.5.3. Service benchmarking
    • 8.3.5.4. Strategic initiatives
  • 8.3.6. WuXi AppTec
    • 8.3.6.1. Company overview
    • 8.3.6.2. Financial performance
    • 8.3.6.3. Service benchmarking
    • 8.3.6.4. Strategic initiatives
  • 8.3.7. Oncodesign
    • 8.3.7.1. Company overview
    • 8.3.7.2. Financial performance
    • 8.3.7.3. Service benchmarking
    • 8.3.7.4. Strategic initiatives
  • 8.3.8. Hera Biolabs
    • 8.3.8.1. Company overview
    • 8.3.8.2. Financial performance
    • 8.3.8.3. Service benchmarking
    • 8.3.8.4. Strategic initiatives
  • 8.3.9. XenTech
    • 8.3.9.1. Company overview
    • 8.3.9.2. Financial performance
    • 8.3.9.3. Service benchmarking
    • 8.3.9.4. Strategic initiatives
  • 8.3.10. Abnova Corp.
    • 8.3.10.1. Company overview
    • 8.3.10.2. Financial performance
    • 8.3.10.3. Service benchmarking
    • 8.3.10.4. Strategic initiatives