세계의 임상시험용 AI 시장

The global market for Artificial Intelligence (AI) in Clinical Trials was valued at $2 billion in 2024 and is estimated to increase from $2.4 billion in 2025 to reach $6.5 billion by 2030, at a compound annual growth rate (CAGR) of 22.6% from 2025 through 2030.

The North American market for AI in Clinical Trials was valued at $771.2 million in 2024 and is estimated to increase from $936.7 million in 2025 to reach $2.7 billion by 2030, at a CAGR of 23.7% from 2025 through 2030.

The Asia-Pacific market for AI in Clinical Trials was valued at $372.8 million in 2024 and is estimated to increase from $467.9 million in 2025 to reach $1.6 billion by 2030, at a CAGR of 28.4% from 2025 through 2030.

Report Scope

The report examines trends in the global market for AI in clinical trials. It segments the global market by component, phase, deployment mode, therapeutic area and end user. It also provides insights into key emerging trends and potential growth drivers. Components consist of software and services. Deployment mode include cloud, on-premise, and hybrid. Therapeutic areas include cancers, infectious diseases and neurological diseases. End users include pharmaceutical and biotech companies, contract research organizations (CROs), and research and academic institutes.

The report's regional analysis covers North America, Europe, Asia-Pacific, South America, and the Middle East and Africa. It evaluates the impact of AI adoption in clinical trials and the market dynamics, including drivers and challenges. The study concludes with an analysis of leading companies in the market and their product portfolios.

It includes global revenue ($ millions) for the base year of 2024, estimates for 2025, and data for the forecast period of 2026 through 2030.

Report Includes

• 56 data tables and 52 additional tables
• In-depth analysis of the global market for artificial intelligence (AI) in pharmaceutical clinical trials
• Analyses of the global market trends, with historic revenue data from 2022 to 2024, estimates for 2025, and projections of CAGRs through 2030
• Estimates of the market's size and revenue growth prospects, accompanied by a market share analysis by offerings, deployment type, trial phase, therapeutic area, end user and region
• Facts and figures pertaining to market dynamics, technological advances, regulations, prospects and the impacts of macroeconomic variables
• Impact analysis of U.S. tariff laws on AI in the clinical trials market
• Insights derived from Porter's Five Forces model, as well as a global supply chain analysis
• A look at the regulatory landscape featuring key international and regional regulations and standards for AI adoption
• Evaluation of recent patent activity and key granted and published patents
• Overview of sustainability trends and ESG developments, with emphasis on consumer attitudes, and the ESG scores and practices of leading companies
• Analysis of the industry structure, including companies' market shares and rankings, strategic alliances, M&A activity and a venture funding outlook
• Company profiles of major players within the industry, including IQVIA, Medidata, Saama, Merative, and Nvidia Corp.

Table of Contents

Chapter 1 Executive Summary

• Market Outlook
• Scope of Report
• Market Summary

Chapter 2 Market Overview

• Overview
• Future Outlook
• Macroeconomic Factors
• Global GDP Growth
• Demographic Factors
• Impact of U.S. Tariffs
• Porter's Five Forces Analysis
• Impact of AI Adoption on Clinical Trials Market
• Overview
• Use Cases/Case Studies
• Use Case 1: Oncology Patient Recruitment
• Use Case 2: Accelerating Data Processing in Infectious Disease Vaccine Trials
• Use Case 3: Enhancing Patient Retention in Alzheimer's Disease Trials
• AI Adoption: Clinical Trials
• Adoption Trends at Regional/Country Levels
• AI Disruption Trends
• Impact of AI on Industry Verticals
• Impact of AI on the Value Chain
• Market Spending and Investment
• Market Spending and Forecasting Analysis
• Venture Capital Investment in AI Focused on Clinical Trials

Chapter 3 Market Dynamics

• Market Drivers
• Need for a Faster Drug Development Process
• AI-driven Clinical Trials
• Advanced Data Handling for Complex Clinical Input
• Market Restraints
• Data Privacy and Security Concerns
• Regulatory Uncertainties
• High Costs and Technical Complexity
• Market Opportunities
• Accelerated Trials Through Adaptive AI Design
• AI-Augmented Remote Patient Monitoring

Chapter 4 Regulatory Landscape

• Regulatory Framework

Chapter 5 Emerging Technologies

• Overview
• Emerging Technologies
• Machine Learning for Predictive Analytics and Stratification
• Digital Twin Technology
• NLP for Extracting Insights from Unstructured Data
• AI-Powered Trial Design and Optimization
• Blockchain for Secure Clinical Data Management
• Decentralized and Virtual Trial Platforms
• Remote Monitoring Via Wearable Technologies
• Generative AI for Protocol Authoring
• Real-World Evidence Integration in Clinical Trials
• Cloud-based AI Platforms for Scalable Deployment
• Clinical Trial Analysis
• Takeaways

Chapter 6 Market Segmentation Analysis

• Segmentation Breakdown
• Global Market for AI in Clinical Trials, by Component
• Takeaways
• Software
• Services
• Global AI in Clinical Trials Market, by Phase
• Takeaways
• Phase III
• Phase II Trials
• Phase I
• Phase IV Clinical Trials
• Global Market for AI in Clinical Trials, by Deployment Mode
• Takeaways
• Cloud
• On-premise
• Hybrid Deployments
• Global Market for AI in Clinical Trials, by Therapeutic Area
• Takeaways
• Oncology
• Infectious Disease Clinical Trials
• Neurological Diseases
• Other Conditions
• Global Market for AI in Clinical Trials, by End User
• Takeaways
• Pharmaceutical and Biotech Companies
• Contract Research Organizations
• Research and Academic Institutes
• Other End Users
• Geographic Breakdown
• North America
• Europe
• Asia-Pacific
• Middle East and Africa
• South America

Chapter 7 Competitive Intelligence

• Overview

Chapter 8 Sustainability in AI in Clinical Trials: ESG Perspective

• Sustainability Trends and AI Initiatives
• Concluding Remarks

Chapter 9 Appendix

• Methodology
• Sources
• Abbreviations
• Company Profiles
• AICURE
• CONCERTAI
• DNANEXUS INC.
• INSILICO MEDICINE
• INTELLIGENCIA AI
• IQVIA
• MEDIDATA
• MERATIVE
• NVIDIA CORP.
• PHESI
• SAAMA
• TEMPUS
• TRINETX LLC
• TRIOMICS
• UNLEARN.AI INC.
• Emerging Start-ups/ Market Disruptors