약물 스크리닝 및 평가용 마우스 모델 시장 : 세계 예측(2026-2032년)

The Mouse Model for Drug Screening & Evaluation Market is projected to grow by USD 1,198.64 million at a CAGR of 7.32% by 2032.

Mouse Models Anchor Translational Drug Screening and Evaluation

Mouse models remain a foundational tool for evaluating pharmacology, toxicology, efficacy, disease mechanisms, and biomarker relationships before human studies. Their value comes from combining controlled genetics and environments with measurable physiological and behavioral endpoints. However, findings must be interpreted alongside species differences, model-specific limitations, and complementary human-relevant methods. Effective programs increasingly position mouse studies within integrated evidence packages rather than treating them as standalone validation.

Demand is shaped by therapeutic complexity, regulatory expectations, reproducibility requirements, and the need to identify safety or efficacy risks earlier. Standardized protocols, rigorous controls, transparent reporting, and careful model selection are therefore central to credible decision-making. Applications span oncology, immunology, infectious disease, neuroscience, metabolic disorders, and rare diseases, with approaches ranging from conventional strains to genetically engineered, humanized, and patient-derived models.

Translational Rigor and Model Diversity Are Reshaping Preclinical Research

The landscape is shifting from broad reliance on traditional inbred strains toward fit-for-purpose model portfolios. Genetically engineered mice, humanized systems, immunocompromised hosts, patient-derived xenografts, and models incorporating sex, age, and comorbidity diversity can address questions that conventional designs may not capture. At the same time, improved study registration, randomization, blinding, power calculations, and independent replication are raising expectations for reproducibility.

Ethical governance is also becoming more consequential. The principles of replacement, reduction, and refinement encourage researchers to limit animal use while improving welfare and information yield. Imaging, longitudinal sampling, microsampling, organoid comparisons, and computational analysis can help extract more data from each study. These changes favor organizations that connect model selection, experimental design, data quality, and translational interpretation from the outset.

Artificial Intelligence Accelerates Design, Analysis, and Translational Interpretation

Artificial intelligence is increasingly applied to select experimental models, prioritize compounds, analyze images, classify phenotypes, and identify relationships across multimodal datasets. Computer vision can support more consistent assessment of tumor burden, tissue pathology, movement, behavior, and cellular responses, while machine-learning workflows can integrate molecular, clinical, and preclinical information to improve hypothesis generation.

The strongest value arises when AI augments-not replaces-experimental judgment. Training-data quality, annotation consistency, external validation, explainability, and bias control remain essential. Models developed from narrow strain, sex, laboratory, or disease datasets may perform poorly when transferred elsewhere. Leaders should establish governance covering data provenance, version control, model performance, human review, and reproducibility, while using AI to reduce avoidable variability and prioritize the most informative studies.

Regional Priorities Reflect Different Research Infrastructures and Regulatory Contexts

In North America, sophisticated biomedical infrastructure, translational partnerships, and strong emphasis on reproducibility support advanced genetically engineered, humanized, imaging, and data-rich mouse studies. Latin America is shaped by uneven access to specialized facilities, growing academic and public-sector research capacity, and the importance of scalable protocols, local disease priorities, and collaborative platforms.

Europe combines substantial pharmaceutical and academic capability with strong animal-welfare expectations, harmonized regulatory principles, and continued interest in alternatives and refinement. The Middle East is developing biomedical research capacity through investment in health science, precision medicine, and specialized facilities, while workforce development and cross-border collaboration remain important. Africa presents opportunities tied to infectious disease, neglected conditions, and locally relevant translational research, alongside infrastructure, funding, and access constraints. Asia-Pacific includes highly advanced research ecosystems as well as rapidly developing markets, with priorities spanning oncology, immunology, metabolic disease, infectious disease, and precision medicine. Across all regions, quality systems, skilled personnel, and interoperable data practices determine whether mouse-model findings translate effectively.

International Groups Shape Collaboration, Standards, and Research Access

The ASEAN countries can benefit from shared infrastructure, harmonized training, and regional study networks that address infectious disease, metabolic health, and locally relevant conditions. BRICS collaboration can broaden access to capabilities, strengthen comparative research, and support model development for diverse populations, provided that data standards and ethical oversight are aligned.

The European Union emphasizes coordinated regulation, animal-welfare safeguards, and alternatives-oriented innovation. The G7 provides a platform for advanced research cooperation, biosecurity dialogue, and reproducibility practices. The GCC is investing in biomedical capacity and can accelerate specialized preclinical research through coordinated facilities and international partnerships. NATO members and associated research networks have particular incentives to strengthen preparedness for infectious disease, biological threats, and medical countermeasure development while maintaining strict governance and responsible-use controls.

Country Capabilities Differ in Scale, Specialization, and Translational Priorities

The United States combines deep academic, biotechnology, and pharmaceutical capabilities with extensive demand for rigorous translational evidence. Canada contributes strong public research, disease-model expertise, and collaborative networks. Mexico is expanding biomedical capacity, with opportunities to strengthen standardized facilities, training, and cross-border partnerships. Brazil has substantial academic and public-health expertise, particularly for infectious, tropical, and chronic diseases, while infrastructure consistency remains important.

In Europe, France, Germany, Italy, Spain, and the United Kingdom support diverse preclinical programs within demanding welfare, quality, and regulatory environments. Russia retains expertise in biomedical research but faces constraints related to international access, collaboration, and supply continuity. In Asia, China, Japan, South Korea, India, and Australia offer distinct strengths: China in scale and model development; Japan in advanced biomedical research and aging-related science; South Korea in biotechnology and translational innovation; India in expanding research capacity and disease-focused programs; and Australia in high-quality biomedical science, infectious-disease research, and strong institutional governance. Country-level execution depends on facility standards, talent, procurement, regulatory clarity, and access to validated model systems.

Industry Leaders Should Build Evidence Portfolios, Not Isolated Mouse Studies

Leaders should begin with a decision-oriented model strategy: define the biological question, translational endpoint, target population, and failure criteria before selecting a strain or platform. Use complementary models when one system cannot represent human heterogeneity, and predefine how results will be integrated with human cells, organoids, pharmacokinetics, biomarkers, and computational analyses.

Invest in reproducibility through randomization, blinding, appropriate controls, preregistered protocols where suitable, power analysis, independent replication, and transparent reporting. Establish digital data standards that preserve metadata, images, sample lineage, and analytical decisions. Apply AI selectively with documented validation and human oversight. Finally, strengthen partnerships with accredited facilities and specialist laboratories, maintain contingency plans for animals and critical reagents, and measure programs by decision quality, translational relevance, welfare performance, and time saved-not by study volume alone.

Methodology Combines Structured Secondary Evidence With Translational Interpretation

This executive summary uses the defined market scope-mouse models used for drug screening and evaluation-and organizes analysis around application needs, model types, research workflows, technology adoption, regulation, ethics, and geographic capability. The assessment integrates established principles from preclinical pharmacology, toxicology, laboratory-animal science, translational medicine, data governance, and reproducibility research.

Insights are synthesized comparatively across North America, Latin America, Europe, the Middle East, Africa, and Asia-Pacific; ASEAN, BRICS, the European Union, G7, GCC, and NATO; and the specified countries. Because the scope excludes estimates, sizing, shares, forecasts, and company profiling, conclusions focus on verified structural drivers, operational requirements, regional characteristics, and evidence-quality considerations. Interpretations should be updated as regulations, technologies, disease priorities, and institutional capabilities change.

The Next Advantage Will Come From Better Translation, Reproducibility, and Integration

Mouse models will remain important because they connect molecular hypotheses with whole-organism pharmacology, safety, and disease biology. Their future effectiveness will depend less on using more models and more on selecting the right model, measuring the right endpoints, and acknowledging where mouse biology does not represent human disease.

Organizations that combine rigorous experimental design, welfare-conscious practice, AI-enabled analysis, complementary human-relevant systems, and transparent data workflows will be better positioned to make reliable development decisions. Regional and international collaboration can further improve access, standardization, and preparedness. The central strategic priority is an integrated translational framework in which mouse evidence is credible, reproducible, appropriately qualified, and connected to the human questions that ultimately determine therapeutic value.

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Definition
• 1.3. Market Segmentation & Coverage
• 1.4. Years Considered for the Study
• 1.5. Currency Considered for the Study
• 1.6. Language Considered for the Study
• 1.7. Key Stakeholders

2. Research Methodology

• 2.1. Introduction
• 2.2. Research Design
  • 2.2.1. Primary Research
  • 2.2.2. Secondary Research
• 2.3. Research Framework
  • 2.3.1. Qualitative Analysis
  • 2.3.2. Quantitative Analysis
• 2.4. Market Size Estimation
  • 2.4.1. Top-Down Approach
  • 2.4.2. Bottom-Up Approach
• 2.5. Data Triangulation
• 2.6. Research Outcomes
• 2.7. Research Assumptions
• 2.8. Research Limitations

3. Executive Summary

• 3.1. Introduction
• 3.2. CXO Perspective
• 3.3. New Revenue Opportunities
• 3.4. Next-Generation Business Models
• 3.5. Industry Roadmap

4. Market Overview

• 4.1. Introduction
• 4.2. Industry Ecosystem & Value Chain Analysis
  • 4.2.1. Supply-Side Analysis
  • 4.2.2. Demand-Side Analysis
  • 4.2.3. Stakeholder Analysis
• 4.3. Market Dynamics
  • 4.3.1. Key Drivers
  • 4.3.2. Key Restraints
  • 4.3.3. Key Opportunities
  • 4.3.4. Key Challenges
• 4.4. Porter's Five Forces Analysis
• 4.5. PESTLE Analysis
• 4.6. Market Outlook
  • 4.6.1. Near-Term Market Outlook (0-2 Years)
  • 4.6.2. Medium-Term Market Outlook (3-5 Years)
  • 4.6.3. Long-Term Market Outlook (5-10 Years)
• 4.7. Go-to-Market Strategy

5. Market Insights

• 5.1. Consumer Insights & End-User Perspective
• 5.2. Consumer Experience Benchmarking
• 5.3. Opportunity Mapping
• 5.4. Distribution Channel Analysis
• 5.5. Pricing Trend Analysis
• 5.6. Regulatory Compliance & Standards Framework
• 5.7. ESG & Sustainability Analysis
• 5.8. Disruption & Risk Scenarios
• 5.9. Return on Investment & Cost-Benefit Analysis

6. Cumulative Impact of Artificial Intelligence 2026

7. Mouse Model for Drug Screening & Evaluation Market, by Product Type

• 7.1. Introduction
• 7.2. Consumables
  • 7.2.1. Disposables
  • 7.2.2. Kits & Assays
  • 7.2.3. Media & Reagents
• 7.3. Instruments
• 7.4. Software & Services

8. Mouse Model for Drug Screening & Evaluation Market, by Model Type

• 8.1. Introduction
• 8.2. Genetically Engineered
  • 8.2.1. CRISPR/Cas9
  • 8.2.2. Knockin
  • 8.2.3. Knockout
  • 8.2.4. Transgenic
• 8.3. Humanized
• 8.4. Syngeneic
• 8.5. Xenograft

9. Mouse Model for Drug Screening & Evaluation Market, by Animal Species

• 9.1. Introduction
• 9.2. Athymic Nude
• 9.3. BALB/c
• 9.4. C57BL/6
• 9.5. SCID

10. Mouse Model for Drug Screening & Evaluation Market, by Application

• 10.1. Introduction
• 10.2. Cardiovascular Diseases
• 10.3. CNS Disorders
• 10.4. Infectious Diseases
• 10.5. Metabolic Disorders
• 10.6. Oncology

11. Mouse Model for Drug Screening & Evaluation Market, by End User

• 11.1. Introduction
• 11.2. Academic & Research Institutes
• 11.3. CROs
• 11.4. Pharmaceutical & Biotech Companies

12. Mouse Model for Drug Screening & Evaluation Market, by Region

• 12.1. Introduction
• 12.2. Asia-Pacific
• 12.3. North America
• 12.4. Latin America
• 12.5. Europe
• 12.6. Middle East
• 12.7. Africa

13. Mouse Model for Drug Screening & Evaluation Market, by Group

• 13.1. Introduction
• 13.2. ASEAN
• 13.3. GCC
• 13.4. European Union
• 13.5. BRICS
• 13.6. G7
• 13.7. NATO

14. Mouse Model for Drug Screening & Evaluation Market, by Country

• 14.1. Introduction
• 14.2. United States
• 14.3. Canada
• 14.4. Mexico
• 14.5. Brazil
• 14.6. United Kingdom
• 14.7. Germany
• 14.8. France
• 14.9. Russia
• 14.10. Italy
• 14.11. Spain
• 14.12. China
• 14.13. India
• 14.14. Japan
• 14.15. Australia
• 14.16. South Korea

15. Competitive Landscape

• 15.1. Market Share Analysis, 2025
• 15.2. Market Concentration Analysis, 2025
  • 15.2.1. Concentration Ratio (CR)
  • 15.2.2. Herfindahl Hirschman Index (HHI)
• 15.3. Recent Developments & Impact Analysis, 2025
• 15.4. Product Portfolio Analysis, 2025
• 15.5. Benchmarking Analysis, 2025

16. Company Profiles

• 16.1. Applied StemCell, Inc.
• 16.2. Beijing Vitalstar Biotechnology Co., Ltd.
• 16.3. Biocytogen Pharmaceuticals (Beijing) Co., Ltd.
• 16.4. BioIVT, Inc
• 16.5. Charles River Laboratories International, Inc.
• 16.6. Crown Bioscience International, Inc.
• 16.7. Cyagen Biosciences, Inc.
• 16.8. Envigo, Inc.
• 16.9. GemPharmatech Co., Ltd.
• 16.10. genOway SAS
• 16.11. Horizon Discovery Group Limited
• 16.12. Ingenious Targeting Laboratory, Inc.
• 16.13. Inotiv, Inc.
• 16.14. Janvier Labs
• 16.15. MD Anderson Cancer Center
• 16.16. Oriental BioService, Inc.
• 16.17. Regeneron Pharmaceuticals, Inc.
• 16.18. SAGE Labs, Inc.
• 16.19. Shanghai Biomodel Organism Science & Technology Development Co., Ltd.
• 16.20. Shanghai Model Organisms Center, Inc.
• 16.21. Taconic Biosciences, Inc.
• 16.22. The Jackson Laboratory
• 16.23. Transgenic, Inc.
• 16.24. University of California, Davis
• 16.25. Yecuris, Inc.

17. Key Experts