PUBLISHER: Global Market Insights Inc. | PRODUCT CODE: 1535897
PUBLISHER: Global Market Insights Inc. | PRODUCT CODE: 1535897
AI in Clinical Trials Market Size - By Component (Software, Service), By Technology (Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Contextual Bots), By Application, By End User & Forecast, 2024 - 2032
Global AI in Clinical Trials Market size will capture a 14% CAGR between 2024 and 2032, driven by continuous advancements in AI technologies and personalized medicine. Enhanced AI algorithms enable more accurate data analysis, faster drug development, and improved trial efficiency. Also, the rise of personalized medicine allows for tailored treatment plans based on individual patient data, optimizing therapeutic outcomes. As AI technologies evolve and personalized approaches become more prevalent, their combined impact will accelerate clinical trials, making them more efficient and effective, thereby expanding the market.
For instance, in November 2023, AstraZeneca introduced Evinova to integrate AI and digital health solutions into clinical trials, targeting CROs, trial sponsors, care teams, and patients, leveraging technologies already used globally by the company. This move indicates a rising trend towards integrating advanced technologies in clinical research, driving innovation, improving trial outcomes, and potentially increasing market adoption. As major players like AstraZeneca adopt AI, it underscores the expanding role of AI in transforming clinical trial processes and outcomes.
The AI in clinical trials industry is segmented based on component, technology, application, end-user, and region.
The machine learning segment will witness substantial growth throughout 2024-2032. Machine learning algorithms play a pivotal role in processing vast amounts of clinical data, identifying patterns, and predicting trial outcomes. These capabilities significantly reduce the time required for data analysis and enhance decision-making accuracy. Pharmaceutical companies are increasingly leveraging machine learning to optimize patient selection, monitor trial progress, and ensure compliance with regulatory standards. The integration of machine learning in clinical trials improves efficiency and enhances the overall quality of trials, supporting market expansion.
The drug discovery segment will amass considerable gains by 2032, attributed to its transformative impact on accelerating drug development processes. AI technologies enhance predictive modeling, optimize clinical trial designs, and identify potential drug candidates more efficiently, considerably reducing time and costs. Advanced algorithms analyze vast datasets to uncover novel drug interactions and biomarkers, leading to more targeted therapies. As pharmaceutical companies increasingly adopt AI for its ability to streamline discovery and improve success rates, this segment will hold a decent market share.
Asia Pacific AI in clinical trials market will achieve a moderate CAGR from 2024 to 2032. The region's rapidly evolving healthcare infrastructure, increasing investment in medical research, and supportive government policies create a conducive environment for AI adoption. Countries like China, India, and Japan are at the forefront of integrating AI technologies into clinical trials, driven by the need to improve healthcare outcomes and address the growing burden of chronic diseases. The presence of a large patient population and the availability of advanced technological solutions further support the expansion of the Asia Pacific AI in clinical trials industry.
Table of Contents
Chapter 1 Methodology & Scope
- 1.1 Market scope & definition
- 1.2 Research design
- 1.2.1 Research approach
- 1.2.2 Data collection methods
- 1.3 Base estimates & calculations
- 1.3.1 Base year calculation
- 1.3.2 Key trends for market estimation
- 1.4 Forecast model
- 1.5 Primary research and validation
- 1.5.1 Primary sources
- 1.5.2 Data mining sources
Chapter 2 Executive Summary
- 2.1 Industry360°synopsis, 2021 - 2032
Chapter 3 Industry Insights
- 3.1 Industry ecosystem analysis
- 3.2 Supplier landscape
- 3.2.1 Platform provider
- 3.2.2 Software provider
- 3.2.3 Service provider
- 3.2.4 Distribution channel
- 3.2.5 End user
- 3.3 Profit margin analysis
- 3.4 Technology & innovation landscape
- 3.5 Patent analysis
- 3.6 Key news & initiatives
- 3.7 Regulatory landscape
- 3.8 Impact forces
- 3.8.1 Growth drivers
- 3.8.1.1 Accelerated drug development and discovery
- 3.8.1.2 Improved patient recruitment
- 3.8.1.3 Enhanced data analysis and real time monitoring
- 3.8.1.4 Rising need of personalized medicine
- 3.8.2 Industry pitfalls & challenges
- 3.8.2.1 Data privacy and security concerns
- 3.8.2.2 Integration with existing systems
- 3.8.1 Growth drivers
- 3.9 Growth potential analysis
- 3.10 Porter's analysis
- 3.10.1 Supplier power
- 3.10.2 Buyer power
- 3.10.3 Threat of new entrants
- 3.10.4 Threat of substitutes
- 3.10.5 Industry rivalry
- 3.11 PESTEL analysis
Chapter 4 Competitive Landscape, 2023
- 4.1 Introduction
- 4.2 Company market share analysis
- 4.3 Competitive positioning matrix
- 4.4 Strategic outlook matrix
Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2032 ($Bn)
- 5.1 Key trends
- 5.2 Software
- 5.2.1 Phase I
- 5.2.2 Phase II
- 5.2.3 Phase III
- 5.3 Service
- 5.3.1 Phase I
- 5.3.2 Phase II
- 5.3.3 Phase III
Chapter 6 Market Estimates & Forecast, By Technology, 2021 - 2032 ($Bn)
- 6.1 Key trends
- 6.2 Machine learning
- 6.3 Natural Language Processing (NLP)
- 6.4 Computer vision
- 6.5 Contextual bots
- 6.6 Others
Chapter 7 Market Estimates & Forecast, By Application, 2021 - 2032 ($Bn)
- 7.1 Key trends
- 7.2 Drug development
- 7.3 Drug discovery
- 7.4 Clinical trial management
- 7.4.1 Patient recruitment
- 7.4.2 Clinical trial monitoring
- 7.4.3 Clinical data management
- 7.4.4 Risk-based monitoring
- 7.5 Others
Chapter 8 Market Estimates & Forecast, By End User, 2021 - 2032 ($Bn)
- 8.1 Key trends
- 8.2 Pharmaceutical and biotechnology companies
- 8.3 Contract Research Organizations (CROs)
- 8.4 Academic and research institutes
- 8.5 Others
Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2032 ($Bn)
- 9.1 Key trends
- 9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
- 9.3 Europe
- 9.3.1 UK
- 9.3.2 Germany
- 9.3.3 France
- 9.3.4 Italy
- 9.3.5 Spain
- 9.3.6 Russia
- 9.3.7 Nordics
- 9.3.8 Rest of Europe
- 9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 India
- 9.4.3 Japan
- 9.4.4 Australia
- 9.4.5 South Korea
- 9.4.6 Southeast Asia
- 9.4.7 Rest of Asia Pacific
- 9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Argentina
- 9.5.4 Rest of Latin America
- 9.6 MEA
- 9.6.1 UAE
- 9.6.2 South Africa
- 9.6.3 Saudi Arabia
- 9.6.4 Rest of MEA
Chapter 10 Company Profiles
- 10.1 BenevolentAI Ltd.
- 10.2 ConcertAI, Inc.
- 10.3 Exscientia Ltd.
- 10.4 GNS Healthcare
- 10.5 Halo Health Systems
- 10.6 IBM (International Business Machines Corporation)
- 10.7 Insilico Medicine, Inc.
- 10.8 IQVIA Holdings Inc.
- 10.9 Medidata Solutions, Inc.
- 10.10 Nuance Communications, Inc.
- 10.11 Numerate
- 10.12 NVIDIA Corporation
- 10.13 Owkin Inc.
- 10.14 Parexel International Corporation
- 10.15 Prometheus Biosciences Inc.
- 10.16 Renalytix AI plc
- 10.17 ReviveMed Ltd.
- 10.18 Saama Technologies, Inc.
- 10.19 Sensyne Health plc
- 10.20 TrialTrove Inc.
