반려동물 진단 시장 - 세계 예측(2026-2032년)

The Companion Animal Diagnostics Market is projected to grow by USD 6.55 billion at a CAGR of 8.94% by 2032.

Companion Animal Diagnostics Executive Summary

Companion animal diagnostics is becoming a core pillar of modern veterinary care as pet ownership, preventive medicine, and chronic disease management converge. Diagnostic testing for dogs, cats, and other companion animals spans clinical chemistry, hematology, immunodiagnostics, molecular diagnostics, urinalysis, cytology, histopathology, microbiology, imaging support, and point-of-care testing. Demand is being shaped by rising awareness of zoonotic diseases, longer pet lifespans, growth in pet insurance adoption in several countries, and increasing expectations for evidence-based veterinary decisions. Veterinarians are using diagnostics not only to confirm disease but also to monitor wellness, guide antimicrobial stewardship, personalize treatment, and support early detection of endocrine, renal, hepatic, infectious, oncologic, and cardiometabolic conditions. The sector is also influenced by the shift from episodic sick visits to longitudinal pet health management, where laboratory data, digital medical records, and connected diagnostic devices help create a more complete clinical picture. As a result, companion animal diagnostics is moving from a back-office clinical function to a strategic enabler of quality care, client trust, clinic efficiency, and public health surveillance.

Transformative Shifts in the Companion Animal Diagnostics Landscape

The companion animal diagnostics landscape is undergoing transformative shifts driven by clinical, technological, and operational change. Veterinary practices are increasingly adopting in-clinic analyzers and rapid point-of-care diagnostics to shorten turnaround times and support same-visit treatment decisions, while reference laboratories remain essential for complex testing, confirmatory diagnostics, pathology, advanced molecular assays, and quality-controlled high-throughput workflows. Molecular diagnostics, including polymerase chain reaction-based testing and sequencing-enabled approaches, is strengthening detection of infectious diseases, inherited disorders, and emerging pathogens. At the same time, immunoassays and biomarker-based panels are expanding the ability to evaluate inflammation, organ function, endocrine disorders, cardiac stress, and cancer-associated signals. Digitalization is another major shift, with laboratory information systems, electronic medical records, tele-triage, and cloud-connected devices improving data continuity across clinics, laboratories, and pet owners. The sector is also responding to antimicrobial resistance concerns by emphasizing culture, susceptibility testing, and evidence-based prescribing. These changes are creating a diagnostics environment that is faster, more connected, more preventive, and more clinically integrated than the traditional test-and-report model.

Cumulative Impact of Artificial Intelligence on Diagnostic Care

Artificial intelligence is having a cumulative impact on companion animal diagnostics by improving workflow efficiency, decision support, pattern recognition, and predictive clinical insight. In diagnostic imaging and digital pathology, AI-enabled tools can assist in identifying abnormalities, prioritizing cases, and standardizing interpretation, while clinicians retain responsibility for diagnosis and treatment decisions. In laboratory medicine, AI and machine learning can support quality control, flag outlier results, identify trends across longitudinal patient data, and help detect subtle deviations from species- and breed-relevant reference patterns. AI is also strengthening syndromic surveillance by analyzing aggregated diagnostic signals for infectious disease trends, seasonal patterns, and geographic clusters, which is especially relevant for zoonotic and vector-borne diseases. In veterinary clinics, AI-driven decision support can help align test selection with clinical signs, age, breed, vaccination history, travel exposure, and comorbidities, potentially reducing missed diagnoses and unnecessary testing. However, responsible implementation requires validated datasets, transparent model performance, cybersecurity safeguards, clinician oversight, and attention to bias across breeds, species, ages, and regional disease prevalence. The greatest value of AI in companion animal diagnostics will come from augmenting veterinary expertise rather than replacing it.

Key Regional Insights Across Global Companion Animal Diagnostics

Asia-Pacific is experiencing strong momentum in companion animal diagnostics as urban pet ownership expands, veterinary infrastructure improves, and awareness of preventive care grows across China, India, Japan, South Korea, Australia, and Southeast Asia. The region is also highly relevant for infectious disease diagnostics due to diverse climates, vector exposure, companion animal rabies control priorities, and the need for surveillance of zoonotic pathogens. North America remains one of the most advanced regions for companion animal diagnostics, supported by high veterinary service utilization, broad availability of reference laboratories and point-of-care testing, established wellness programs, and strong integration of electronic medical records in clinical workflows. In Latin America, Brazil and Mexico are important growth centers as pet populations, middle-class spending on veterinary care, and clinic modernization increase, though access disparities between urban and rural areas remain a key consideration. Europe demonstrates mature adoption of diagnostic testing, with strong emphasis on animal welfare, antimicrobial stewardship, laboratory quality standards, preventive medicine, and companion animal disease surveillance across major countries. The Middle East is seeing rising demand linked to premium pet care, growing veterinary hospital networks, increased importation of companion animals, and greater attention to urban companion animal health. Africa presents a heterogeneous landscape, where companion animal diagnostics is developing alongside broader veterinary capacity-building, zoonotic disease awareness, rabies prevention initiatives, and expanding access to laboratory services in major metropolitan areas.

Key Economic and Policy Group Insights for Companion Animal Diagnostics

ASEAN countries are becoming increasingly important in companion animal diagnostics as urbanization, pet humanization, and expanding private veterinary services support greater use of rapid tests, wellness panels, parasitology, and infectious disease screening. The GCC is characterized by rising demand for advanced veterinary services, especially in urban pet care settings where premium diagnostics, imaging support, laboratory partnerships, and specialty referrals are gaining relevance. The European Union plays a critical role through its regulatory emphasis on animal health, antimicrobial resistance reduction, data quality, laboratory standards, and cross-border disease monitoring, creating a favorable environment for evidence-based diagnostics and responsible test utilization. BRICS countries represent a diverse but influential group, combining large companion animal populations, expanding veterinary education, and growing diagnostic adoption, while also facing affordability, infrastructure, and regional access challenges. G7 countries generally show high diagnostic maturity, supported by advanced veterinary networks, stronger insurance penetration in selected markets, digital practice management, laboratory accreditation practices, and greater client acceptance of preventive screening. NATO member countries overlap significantly with developed veterinary systems in North America and Europe, where companion animal diagnostics is shaped by high clinical standards, biosurveillance awareness, and increasing use of data-driven disease monitoring. Across these groups, the strongest opportunities are linked to accessible point-of-care testing, laboratory integration, practitioner education, and diagnostics that support preventive, chronic, and infectious disease management.

Key Country Insights Shaping Companion Animal Diagnostics Adoption

The United States leads in broad clinical adoption of companion animal diagnostics, supported by extensive veterinary hospital networks, reference laboratory access, wellness testing, specialty practices, and growing use of digital tools in practice management. Canada demonstrates a similar emphasis on preventive care, laboratory quality, and companion animal health monitoring, with demand shaped by high pet ownership and strong veterinary professionalism. Mexico is advancing through expanding urban veterinary services and rising awareness of infectious disease testing, while Brazil shows significant relevance due to its large pet population, increasing private veterinary care, and growing demand for laboratory-backed diagnosis. The United Kingdom has a mature veterinary care environment influenced by pet insurance, preventive medicine, and strong clinical guidelines. Germany, France, Italy, and Spain reflect advanced European diagnostic adoption, with growing attention to chronic disease monitoring, antimicrobial stewardship, parasitology, vector-borne diseases, and laboratory quality. Russia presents demand shaped by urban pet care growth and expanding private clinics, though regional access variation remains important. China is rapidly modernizing veterinary diagnostics as pet ownership rises in major cities and demand for premium veterinary care increases. India is progressing from basic clinical testing toward broader diagnostic use, particularly in metropolitan areas where pet care awareness and veterinary service capacity are expanding. Japan has a sophisticated companion animal care culture, with strong relevance for geriatric pet diagnostics due to aging pet populations and high demand for preventive screening. Australia benefits from high pet ownership, preventive veterinary engagement, and strong awareness of infectious, parasitic, and biosecurity-related disease risks. South Korea is seeing rising diagnostic adoption as pet humanization, specialty veterinary services, insurance interest, and digital health engagement continue to advance.

Actionable Recommendations for Companion Animal Diagnostics Leaders

Industry leaders should prioritize diagnostic solutions that address real clinical pain points: faster turnaround, high analytical reliability, intuitive workflows, and actionable interpretation for veterinarians. Expanding point-of-care testing should be balanced with strong quality assurance, calibration protocols, staff training, external proficiency practices, and clear pathways for confirmatory reference laboratory testing. Leaders should invest in integrated data ecosystems that connect analyzers, laboratory information systems, electronic medical records, and client communication platforms to support longitudinal pet health management. Product development should focus on high-burden clinical areas, including renal disease, endocrine disorders, infectious diseases, oncology, cardiology, gastrointestinal disease, dermatology, parasitology, and antimicrobial stewardship. AI-enabled tools should be clinically validated, transparent, and designed to support veterinarian decision-making rather than create opaque automation. Regional strategies should reflect local disease prevalence, veterinary infrastructure, affordability, regulatory expectations, and language needs. Partnerships with veterinary educators, professional associations, and diagnostic training programs can improve test utilization and interpretation quality. Leaders should also strengthen supply resilience for reagents, consumables, and instruments, while ensuring cybersecurity and data privacy for connected diagnostic platforms.

Research Methodology for Companion Animal Diagnostics Analysis

This executive summary is developed through a structured secondary research approach using publicly available, verified sources such as veterinary medical literature, peer-reviewed journals, animal health authorities, regulatory publications, professional veterinary guidelines, disease surveillance resources, laboratory quality frameworks, and public health documentation. The analysis emphasizes evidence-backed trends in companion animal diagnostics, including technological adoption, clinical applications, regional development, artificial intelligence use cases, and diagnostic workflow evolution. Insights are synthesized through thematic assessment of veterinary care delivery, laboratory medicine, point-of-care testing, molecular diagnostics, immunodiagnostics, antimicrobial stewardship, zoonotic disease monitoring, and digital health integration. Regional, group, and country perspectives are interpreted based on observable indicators such as veterinary infrastructure, pet ownership trends, regulatory emphasis, clinical practice maturity, preventive care adoption, and infectious disease relevance. The methodology avoids market sizing, market share, numerical forecasting, and vendor-specific positioning. The result is a qualitative, decision-oriented view designed to support strategic planning, content positioning, and informed understanding of the companion animal diagnostics ecosystem.

Conclusion: Companion Animal Diagnostics as a Strategic Veterinary Care Enabler

Companion animal diagnostics is evolving into a central component of proactive veterinary medicine, enabling earlier detection, more precise treatment, better chronic disease monitoring, and stronger infectious disease control. The field is being reshaped by point-of-care testing, advanced laboratory assays, molecular diagnostics, digital connectivity, and artificial intelligence, all of which are improving the speed and clinical value of diagnostic decision-making. Regional dynamics vary, with mature markets emphasizing integrated care and quality standards, while emerging markets focus on access, affordability, veterinary capacity, and infectious disease screening. The strongest path forward lies in combining reliable diagnostic science with practical clinic workflows, validated AI support, responsible data governance, and education that helps veterinarians translate results into better outcomes. As pet owners increasingly expect high-quality, preventive, and personalized care, companion animal diagnostics will remain essential to veterinary practice performance, animal welfare, antimicrobial stewardship, zoonotic disease monitoring, and the broader One Health agenda.

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. Market Size & Growth Trends
• 3.4. New Revenue Opportunities
• 3.5. Next-Generation Business Models
• 3.6. 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. Companion Animal Diagnostics Market, by Offering

• 7.1. Introduction
• 7.2. Consumables
  • 7.2.1. Reagents
  • 7.2.2. Test kits
• 7.3. Instruments/Analyzers
  • 7.3.1. Clinical chemistry analyzers
  • 7.3.2. Hematology analyzers
  • 7.3.3. Immunodiagnostic analyzers
  • 7.3.4. Molecular diagnostic analyzers

8. Companion Animal Diagnostics Market, by Test Type

• 8.1. Introduction
• 8.2. Hematology
  • 8.2.1. Blood Clotting Test
  • 8.2.2. Complete Blood Count (CBC)
• 8.3. Histopathology
• 8.4. Imaging
  • 8.4.1. Ultrasound
  • 8.4.2. X-Rays
• 8.5. Molecular Diagnostics
  • 8.5.1. DNA Sequencing
  • 8.5.2. PCR
• 8.6. Serology

9. Companion Animal Diagnostics Market, by Animal Type

• 9.1. Introduction
• 9.2. Birds
• 9.3. Cats
• 9.4. Dogs
• 9.5. Guinea pigs
• 9.6. Horses

10. Companion Animal Diagnostics Market, by Application

• 10.1. Introduction
• 10.2. Endocrinology Testing
• 10.3. Genetic Testing
• 10.4. Infectious Disease Diagnostics
• 10.5. Nutritional Analysis
• 10.6. Oncology
• 10.7. Therapeutic Drug Monitoring
• 10.8. Toxicology Testing

11. Companion Animal Diagnostics Market, by End-User

• 11.1. Introduction
• 11.2. In-House Testing Facilities
  • 11.2.1. Animal Shelters
  • 11.2.2. Pet Owners
• 11.3. Research Laboratories
• 11.4. Veterinary Hospitals & Clinics

12. Companion Animal Diagnostics Market, by Region

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

13. Companion Animal Diagnostics Market, by Group

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

14. Companion Animal Diagnostics Market, by Country

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

15. Competitive Landscape

• 15.1. Market Share Analysis, 2025
• 15.2. FPNV Positioning Matrix, 2025
• 15.3. Market Concentration Analysis, 2025
  • 15.3.1. Concentration Ratio (CR)
  • 15.3.2. Herfindahl Hirschman Index (HHI)
• 15.4. Recent Developments & Impact Analysis, 2025
• 15.5. Product Portfolio Analysis, 2025
• 15.6. Benchmarking Analysis, 2025

16. Company Profiles

• 16.1. Agrolabo S.p.A.
• 16.2. Bio-Rad Laboratories, Inc.
• 16.3. Biogal Galed Labs
• 16.4. BioMerieux S.A.
• 16.5. BioNote, Inc.
• 16.6. Demeditec Diagnostics GmbH
• 16.7. Eurofins Scientific SE
• 16.8. Fassisi GmbH
• 16.9. FUJIFILM Holdings Corporation
• 16.10. IDEXX Laboratories, Inc.
• 16.11. IDvet
• 16.12. Mars, Incorporated
• 16.13. Neogen Corporation
• 16.14. Nisseiken Co., Ltd
• 16.15. Qiagen N.V.
• 16.16. Randox Laboratories, Ltd.
• 16.17. Shenzhen Bioeasy Biotechnology Co., Ltd.
• 16.18. Shenzhen Mindray Animal Medical Technology Co., Ltd.
• 16.19. SKYER, Inc.
• 16.20. Skyla Corporation
• 16.21. Thermo Fisher Scientific Inc.
• 16.22. Vimian Group AB
• 16.23. Virbac S.A.
• 16.24. Zoetis Inc.