AI in Clinical Trials Market Size, Share & Forecast to 2030

The AI in clinical trials market is projected to reach USD 2.74 billion by 2030 from USD 1.35 billion in 2024, at a CAGR of 12.4% from 2024 to 2030. The growing demand for improvements in effectiveness, recruitment of patients in a shorter duration, and accurate analysis of data is the key factor fuelling the market for AI in clinical trials. Solutions powered by AI assist in shortening the duration of various phases of the trial and also in improving patient retention levels using predictive modelling and engagement strategies. In addition, the increase in use of wearables and EMR systems facilitates monitoring at every stage of the course, hence reinforcing the application of AI in trials. Nevertheless, a few obstacles including regulatory norms, prohibitively high cost of implementation and fears of data breach act as constraints hindering the full-scale use of AI in clinical trials.

Infectious diseases had the fastest growth rate in the AI in clinical trials market during the forecast period, by indication.

In the sector of conducting clinical studies with the application of AI technologies, it is likely that among all indications infectious diseases will experience the most rapid growth. Such development is very fast owing to the global appeal for quicker and better solutions against disease outbreaks such as the pandemic. AI speed up the patient enrolment process, enhance forecasting, better structure the trials all of which help to deal with fast spreading viruses in a common sense. There has been a significant rise in the use of advanced technologies especially AI owing to the increased campaigns of fighting infectious diseases.

By end user, the pharmaceutical & biopharma companies to account for largest market share in 2023.

By end user, AI in clinical trials market is bifurcated into pharmaceutical & biopharma companies, research institutes & labs, healthcare providers, contract research organizations, and medical device manufacturers. The majority of the market share to be occupied by pharmaceutical & biopharma companies’ segment. This is due to the great extent of research and development expenditure, which in turn raises the application of AI for faster drug development processes, better clinical trial designs as well as enhanced patient recruitment for the companies. Such AI systems are designed for such firms to help in a complex analysis of large data sets, quicken the introduction of products into the market, and control the ever-increasing costs which are very essential in winning the competition in the case of the pharmaceutical sector.

Asia Pacific is estimated to register the highest CAGR over the forecast period.

The AI in clinical trials market is geographically segmented into North America, Europe, Asia Pacific, Latin America, and Middle East & Africa. The Asia Pacific AI in clinical trials market is projected to register highest CAGR during the forecast period. The Asia Pacific is benefiting from the fast-developing healthcare infrastructure, advances in AI technologies and expansion of clinical research. With countries such as China, India and Japan encouraging the use of AI in healthcare to facilitate large and varied populations and organize clinical trials more efficiently. Furthermore, owing to the favourable government policies, increasing proliferations of contract research organizations (CROs) and cheaper operation costs in the market relative to the Western regions, many multinational pharmaceutical companies are making it their business to invest in AI clinical trials within the region.

Breakdown of supply-side primary interviews by company type, designation, and region:

By Company Type: Tier 1 (40%), Tier 2 (35%), and Tier 3 (25%)
By Designation: Managers (40%), Directors (35%), and Others (25%)
By Region: North America (40%), Europe (30%), Asia Pacific (20%), Latin America (5%) and Middle East Africa (5%)

List of Companies Profiled in the Report:

IQVIA Inc. (US)
Saama. (US)
Dassault Systèmes (Medidata) (France)
Phesi (US)
PathAI, Inc. (US)
Unlearn.ai, Inc. (US)
Deep6.ai (US)
Microsoft (US)
IBM (US)
NVIDIA Corporation (US)
Insilico Medicine (US)
ConcertAI. (US)
AiCure. (US)
Median Technologies. (France)
Lantern Pharma Inc. (US)
Citeline, a Norstella Company (US)
Tempus AI, Inc. (US)
TriNetX, LLC (US)
ReviveMed Inc. (US)
Euretos. (US)
VeriSIM Life. (US)
Triomics (US)
Ardigen (Poland)
QuantHealth Ltd. US)
DEEP GENOMICS. (Canada)

Research Coverage:

This research report categorizes the AI in clinical trials market by offerings (end-to-end solutions, niche solutions, technology providers and services), function (patient recruitment, trial design optimization, data management & quality control, adverse event prediction & detection, drug repurposing, and regulatory compliance), phase (phase I, phase II, phase III and phase IV), deployment mode (cloud-based solutions, and on-premise solutions), indication (oncology, neurological diseases, cardiovascular diseases, metabolic diseases, infectious diseases, immunology diseases, and others (gastrointestinal, respiratory & reproductive), technology (machine learning, NLP, computer vision, robotic process automation, and others), application (biomarkers, cell & gene therapy, regenerative medicine, and medical devices & diagnostics), end user (pharmaceutical & biotechnology companies, research institutes & labs, healthcare providers, contract research organizations (CROs), and medical device manufacturers) and region. The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the AI in clinical trials market. A thorough analysis of the key industry players has been done to provide insights into their business overview, offerings, and key strategies such as acquisitions, collaborations, partnerships, mergers, product/service launches & enhancements, and approvals in the AI in clinical trials market. Competitive analysis of upcoming startups in the AI in clinical trials market ecosystem is covered in this report.

Reasons to Buy the Report

The report will help market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI in clinical trials market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. The report also helps stakeholders understand the market pulse and provides information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

Analysis of key drivers: (Growing demand for faster and more efficient drug development), restraints (High costs associated with implementing AI solutions), opportunities (Increased focus on precision medicine), and challenges (Complexity of integrating AI into traditional clinical trial frameworks) influencing the growth of the AI in clinical trials market.
Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI in clinical trials market.
Market Development: Comprehensive information about lucrative markets - the report analyses the AI in clinical trials market across varied regions.
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI in clinical trials market.
Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players such as IQVIA Inc. (US), Dassault Systèmes (Medidata) (France), Tempus AI, Inc. (US), Insilico Medicine (US), ConcertAI. (US), AiCure. (US) PathAI, Inc. (US), etc. among others in AI in clinical trials market

1 Introduction

1.1 Study Objectives
1.2 Market Definition
1.3 Study Scope
1.3.1 Segments Considered
1.3.2 Inclusions & Exclusions
1.3.3 Years Considered
1.3.4 Currency Considered
1.4 Stakeholders

2 Research Methodology

2.1 Research Data
2.1.1 Secondary Data
2.1.1.1 Key Sources for Secondary Data
2.1.1.2 Key Data from Secondary Sources
2.1.2 Primary Data
2.1.2.1 Key Sources for Primary Data
2.1.2.2 Objectives of Primary Research
2.1.2.3 Key Data from Primary Sources
2.1.2.4 Key Insights from Primary Experts
2.2 Market Size Estimation
2.2.1 Supply-Side Revenue Share Analysis
2.2.2 Parent Market Approach
2.2.3 Company Presentations and Primary Interviews
2.2.4 Market Segment Assessment
2.2.5 Geographic Market Assessment
2.3 Data Triangulation
2.4 Market Share Estimation
2.5 Study Assumptions
2.6 Research Limitations
2.6.1 Methodology-Related Limitations
2.6.2 Scope-Related Limitations
2.7 Risk Assessment

3 Executive Summary

4 Premium Insights

4.1 AI in Clinical Trials Market Overview
4.2 AI in Clinical Trials Market, by Region
4.3 North America: AI in Clinical Trials Market, by End-user and Country
4.4 AI in Clinical Trials Market: Geographical Snapshot
4.5 AI in Clinical Trials Market: Developed vs. Emerging Markets

5 Market Overview

5.1 Introduction
5.2 Market Dynamics
5.3 Market Dynamics
5.3.1 Drivers
5.3.1.1 Increasing Demand for Personalized Treatments
5.3.1.2 Support for Decentralized and Global Trials
5.3.1.3 Regulatory Compliance and Ethical Considerations
5.3.1.4 Automated Document Review for Better Regulatory Compliance
5.3.1.5 Focus on Real-Time Data Management and Analysis
5.3.2 Restraints
5.3.2.1 Data Privacy and Security Concerns
5.3.2.2 Integration Challenges with Legacy Systems and Resistance from Healthcare Professionals
5.3.2.3 High Implementation Cost and Need for Skilled AI Professionals
5.3.3 Opportunities
5.3.3.1 Use of Predictive Analytics in Clinical Trials
5.3.3.2 Development of Virtual Control Arms for Faster Trials
5.3.3.3 Integrating Natural Language Processing into Clinical Trials for Data Extraction
5.3.4 Challenges
5.3.4.1 Addressing Algorithm Bias and Fairness
5.3.4.2 Insufficient Technical Expertise in AI-based Solutions
5.4 Industry Trends
5.4.1 Increasing Adoption of Decentralized Clinical Trials
5.4.2 Rising Focus on AI-Powered Patient Recruitment and Retention
5.5 Ecosystem Analysis
5.6 Case Study Analysis
5.6.1 AI-Powered Approach to Overcome Challenges in Ipf Drug Development
5.6.2 Revolutionizing Clinical Trial Enrollment with Advanced Matching Networks
5.6.3 Breakthrough in Cancer Treatment with Fda Approval for Phase 1 Trials
5.7 Value Chain Analysis
5.8 Porter's Five Forces Analysis
5.8.1 Bargaining Power of Suppliers
5.8.2 Bargaining Power of Buyers
5.8.3 Threat of Substitutes
5.8.4 Threat of New Entrants
5.8.5 Intensity of Competitive Rivalry
5.9 Key Stakeholders & Buying Criteria
5.9.1 Key Stakeholders in Buying Process
5.9.2 Key Buying Criteria
5.10 Regulatory Landscape
5.10.1 Regulatory Bodies, Government Agencies, and Other Organizations
5.10.2 Regulatory Framework
5.11 Patent Analysis
5.11.1 Patent Publication Trends for AI in Clinical Trials
5.11.2 Jurisdiction and Top Applicant Analysis
5.12 Technology Analysis
5.12.1 Key Technologies
5.12.1.1 Machine Learning
5.12.1.2 Natural Language Processing
5.12.1.3 Computer Vision
5.12.2 Complementary Technologies
5.12.2.1 Internet of Things
5.12.2.2 Cloud Computing
5.12.3 Adjacent Technologies
5.12.3.1 Advanced Genomics
5.13 Pricing Analysis
5.13.1 Indicative Price of Key AI Software, by Key Player, 2023
5.13.2 Indicative Price Trend of Key AI Software, by Region, 2022-2024
5.14 Key Conferences & Events, 2024-2025
5.15 Trends and Disruptions Impacting Customer's Business
5.16 Unmet Needs and End-user Expectations
5.16.1 Unmet Needs
5.16.2 End-user Expectations
5.17 Investment & Funding Scenario
5.18 Impact of AI/Gen AI on AI in Clinical Trials Market
5.18.1 Key Use Cases
5.18.2 Impact of AI/Gen AI on Interconnected and Adjacent Ecosystems
5.18.2.1 Case Study
5.18.2.2 Clinical Trials Market
5.18.2.3 Eclinical Solutions Market
5.18.2.4 AI in Biotechnology Market
5.18.3 Users Readiness and Impact Assessment
5.18.3.1 User Readiness
5.18.3.1.1 Pharmaceutical & Biopharmaceutical Companies
5.18.3.1.2 Contract Research Organizations
5.18.3.2 Impact Assessment
5.18.3.2.1 User A: Healthcare Providers
5.18.3.2.2 User B: Research Institutes & Laboratories

6 AI in Clinical Trials Market, by Offering

6.1 Introduction
6.2 End-To-End Solutions
6.2.1 Cost-Effectiveness, Improved Efficiency, and Reduced Human Errors to Drive Adoption in Clinical Trials
6.3 Niche Solutions
6.3.1 High Failure Rates of Clinical Trials and Need for Streamlined Processes to Fuel Market Growth
6.4 Technology Providers
6.4.1 Need to Accelerate Drug Development Processes and High Demand for Personalized Medicines to Aid Market Growth
6.5 Services
6.5.1 Consulting Services
6.5.1.1 Consulting Services to Optimize Trial Design, Enhance Patient Recruitment, and Improve Data Management
6.5.2 Implementation Services & Ongoing IT Support
6.5.2.1 Need for Smooth Integration and Optimization of AI Technologies to Boost Segment Growth
6.5.3 Training & Education Services
6.5.3.1 Need for Skilled Talent for Managing Complex AI Systems to Augment Segment Growth
6.5.4 Post-Sales & Maintenance Services
6.5.4.1 Development of Complex AI Systems and Need for Continuous Improvement in AI Algorithms to Drive Segment Growth

7 AI in Clinical Trials Market, by Function

7.1 Introduction
7.2 Patient Recruitment
7.2.1 Patient Identification & Screening
7.2.1.1 Reduced Patient Screening Time and Better Accuracy Than Human Clinicians to Drive Market
7.2.2 Patient Engagement & Retention
7.2.2.1 Better Personalized Communication and Support for Clinical Trials to Propel Market Growth
7.2.3 Site Optimization
7.2.3.1 Cost-Effective and Improved Participant Recruitment and Retention to Fuel Segment Growth
7.3 Trial Design Optimization
7.3.1 Workflow Management
7.3.1.1 Effective Real-Time Tracking, Automated Reporting, and Milestone Monitoring to Spur Segment Growth
7.3.2 Predictive Modeling
7.3.2.1 Ability to Optimize Trial Design, Predict Risks, and Identify Effective Treatment Protocols to Drive Segment
7.3.3 Risk Management
7.3.3.1 AI-Driven Solutions for Risk Prediction to Improve Patient Safety and Data Integrity
7.4 Data Management & Quality Control
7.4.1 Focus on Maintaining Data Accuracy and Integrity in Clinical Trials to Boost Adoption
7.5 Adverse Event Prediction & Detection
7.5.1 Mitigating Risks and Harnessing AI-Driven Adverse Event Detection to Spur Market Growth
7.6 Drug Repurposing
7.6.1 Drug Repurposing to Validate Hypotheses Against Real-Time Patient Data in Rare Diseases
7.7 Regulatory Compliance
7.7.1 Complexity of Global Regulatory Environments and Need for Faster Drug Approvals to Aid Market Growth

8 AI in Clinical Trials Market, by Phase

8.1 Introduction
8.2 Phase I Clinical Trials
8.2.1 Faster Patient Identification and Recruitment to Propel Adoption of AI
8.3 Phase II Clinical Trials
8.3.1 Need for Accurate Prediction of Optimal Dosage in Phase II Trials to Boost Use of AI
8.4 Phase III Clinical Trials
8.4.1 Need to Check Drug Efficacy and Monitor Adverse Reactions to Augment Market Growth
8.5 Phase IV Clinical Trials
8.5.1 AI to Assess Safety and Long-Term Outcomes of Treatment in Larger Patient Population Under Phase IV Trials

9 AI in Clinical Trials Market, by Deployment Mode

9.1 Introduction
9.2 Cloud-based Solutions
9.2.1 Public Cloud-based Solutions
9.2.1.1 Reduced Need for Costly On-Premises Infrastructure and Better Regulatory Compliance to Fuel Adoption
9.2.2 Private Cloud-based Solutions
9.2.2.1 Better Security and Personalization for Sensitive Data to Propel Segment Growth
9.2.3 Multi Cloud-based Solutions
9.2.3.1 Use of Advanced Predictive Modeling for Patient Recruitment and Site Performance Optimization to Drive Market
9.2.4 Hybrid Cloud-based Solutions
9.2.4.1 Better Flexibility in Data Management to Reduce Resource Requirements in Clinical Trials
9.3 On-Premises Solutions
9.3.1 On-Premises Solutions to Offer Secure Environment for Managing Sensitive Data and Running Complex Algorithms

10 AI in Clinical Trials Market, by Indication

10.1 Introduction
10.2 Oncology
10.2.1 High Prevalence of Cancer and Shortage of Effective Drugs to Drive Segment Growth
10.3 Neurological Diseases
10.3.1 Complexity of Neurogenerative Disorders and Shortage of Drugs for Parkinson's Disease to Spur Market Growth
10.4 Cardiovascular Diseases
10.4.1 Rising Demand for Novel Cardiovascular Drugs to Drive Segment
10.5 Metabolic Diseases
10.5.1 Rising Prevalence of Diabetes and Obesity to Support Market Growth
10.6 Infectious Diseases
10.6.1 Recent Epidemic Outbreaks to Boost Drug Discovery Activities for Infectious Diseases
10.7 Immunology Diseases
10.7.1 Growing Drug Pipeline for Immunological Disorders to Favor Market Growth
10.8 Other Diseases

11 AI in Clinical Trials Market, by Technology

11.1 Introduction
11.2 Machine Learning
11.2.1 Deep Learning
11.2.1.1 Reduced Chance of Errors in Clinical Trials and Enhanced Data Consistency to Augment Segment Growth
11.2.2 Supervised Learning
11.2.2.1 Supervised Learning to Focus on Effective Patient Stratification, Disease Progression Prediction, and Biomarker Identification
11.2.3 Unsupervised Learning
11.2.3.1 Effective Handling of Complex and Unstructured Datasets to Aid Adoption in Trial Design and Execution
11.2.4 Reinforcement Learning
11.2.4.1 Dynamic Learning Capabilities to Aid Adoption in Personalized Medicine and Precision Oncology
11.2.5 Other Machine Learning Technologies
11.3 Natural Language Processing
11.3.1 Abundance of Unstructured Data in Clinical Research to Propel Growth in Trial Management
11.4 Computer Vision
11.4.1 Rising Need for Reproducible Analysis in Clinical Endpoints to Drive Market
11.5 Robotic Process Automation
11.5.1 Robotic Process Automation to Enhance Operational Efficiency by Automating Administrative Workflows
11.6 Other Technologies

12 AI in Clinical Trials Market, by Application

12.1 Introduction
12.2 Biomarkers
12.2.1 Increasing Investments in AI-based Innovation to Aid Development of Personalized Healthcare Solutions
12.3 Cell & Gene Therapy
12.3.1 High Prevalence of Genetic Disorders and Technological Advancements in Car-T Therapies to Drive Growth
12.4 Regenerative Medicines
12.4.1 Increased Need for Precise Monitoring and Advancements in Stem Cell Research to Spur Market Growth
12.5 Medical Devices & Diagnostics
12.5.1 Need for Real-Time Monitoring and Remote Data Acquisition During Trials to Accelerate Market Growth

13 AI in Clinical Trials Market, by End-user

13.1 Introduction
13.2 Pharmaceutical & Biopharmaceutical Companies
13.2.1 High R&D Investments and Increased Regulatory Compliance to Augment Market Growth
13.3 Research Institutes & Laboratories
13.3.1 Increased Government Grants and Collaborations with Pharmaceutical Companies to Support Market Growth
13.4 Healthcare Providers
13.4.1 Advancements in Precision Medicines and Need for Real-World Evidence in Clinical Research to Drive Market
13.5 Contract Research Organizations
13.5.1 Rising Demand for Outsourcing Clinical Trial Activities by Pharmaceutical Companies to Aid Market Growth
13.6 Medical Device Manufacturers
13.6.1 Demand for AI-Driven Diagnostics and Monitoring Devices for Remote Care to Propel Market Growth

14 AI in Clinical Trials Market, by Region

14.1 Introduction
14.2 North America
14.2.1 Macroeconomic Outlook for North America
14.2.2 US
14.2.2.1 US to Dominate North American AI in Clinical Trials Market During Study Period
14.2.3 Canada
14.2.3.1 Rising Need for Data Standardization and Increasing Health Expenditure to Support Market Growth
14.3 Europe
14.3.1 Macroeconomic Outlook for Europe
14.3.2 UK
14.3.2.1 High R&D Investment by Government Organizations to Augment Market Growth
14.3.3 Germany
14.3.3.1 Increased Focus on Research Activities and Strategic Developments by Pharma & Biotech Companies to Drive Market
14.3.4 France
14.3.4.1 Strong Government Support and Focus on Domestic Drug Research to Propel Market Growth
14.3.5 Italy
14.3.5.1 Increased R&D Investments from Pharmaceutical Companies and Reduced Time for Drug Approvals to Fuel Market Growth
14.3.6 Spain
14.3.6.1 Increased Technological Investments by Private Organizations and Integrated Healthcare Systems to Spur Market Growth
14.3.7 Rest of Europe
14.4 Asia-Pacific
14.4.1 Macroeconomic Outlook for Asia-Pacific
14.4.2 Japan
14.4.2.1 Well-Established Clinical Trial Infrastructure and Advanced Biomedical Research to Support Market Growth
14.4.3 China
14.4.3.1 Low Cost of Clinical Trials and Availability of Treatment-Naïve Population to Propel Market Growth
14.4.4 India
14.4.4.1 Favorable Government Policies and High R&D Expenditure by Indian Pharmaceutical Companies to Spur Market Growth
14.4.5 Rest of Asia-Pacific
14.5 Latin America
14.5.1 Macroeconomic Outlook for Latin America
14.5.2 Brazil
14.5.2.1 Increasing Governmental Support for Innovation and Growing Biotechnology Sector to Drive Market
14.5.3 Mexico
14.5.3.1 Strong Technological and Research Capabilities in AI Applications to Fuel Market Growth
14.5.4 Rest of Latin America
14.6 Middle East & Africa
14.6.1 Macroeconomic Outlook for Middle East & Africa
14.6.2 GCC Countries
14.6.2.1 Technological Innovations and Focus on Precision Medicines to Augment Market Growth
14.6.3 Rest of Middle East & Africa

15 Competitive Landscape

15.1 Introduction
15.2 Key Player Strategy/Right to Win
15.2.1 Overview of Strategies Adopted by Key Players in AI in Clinical Trials Market
15.3 Revenue Analysis, 2019-2023
15.4 Market Share Analysis, 2023
15.4.1 Ranking of Key Market Players
15.5 Company Evaluation Matrix: Key Players, 2023
15.5.1 Stars
15.5.2 Emerging Leaders
15.5.3 Pervasive Players
15.5.4 Participants
15.5.5 Company Footprint: Key Players, 2023
15.5.5.1 Company Footprint
15.5.5.2 Region Footprint
15.5.5.3 Offering Footprint
15.5.5.4 Function Footprint
15.5.5.5 End-user Footprint
15.6 Company Evaluation Quadrant: Startup/SMEs, 2023
15.6.1 Progressive Companies
15.6.2 Responsive Companies
15.6.3 Dynamic Companies
15.6.4 Starting Blocks
15.6.5 Competitive Benchmarking: Startups/SMEs, 2023
15.7 Company Evaluation & Financial Metrics
15.8 Brand/Product Comparison
15.9 Competitive Scenario
15.9.1 Product/Service/Solution Launches
15.9.2 Deals
15.9.3 Other Developments

16 Company Profiles

16.1 Key Players
16.1.1 Iqvia Inc.
16.1.1.1 Products/Services/Solutions Offered
16.1.1.2 Recent Developments
16.1.1.2.1 Solution Launches
16.1.1.2.2 Deals
16.1.1.3 Analyst's View
16.1.1.3.1 Right to Win
16.1.1.3.2 Strategic Choices
16.1.1.3.3 Weaknesses & Competitive Threats
16.1.2 Dassault Systèmes (Medidata)
16.1.2.1 Business Overview
16.1.2.2 Products/Services/Solutions Offered
16.1.2.3 Recent Developments
16.1.2.3.1 Solution Launches
16.1.2.3.2 Deals
16.1.2.4 Analyst's View
16.1.2.4.1 Right to Win
16.1.2.4.2 Strategic Choices
16.1.2.4.3 Weaknesses & Competitive Threats
16.1.3 Insilico Medicine
16.1.3.1 Business Overview
16.1.3.2 Products/Services/Solutions Offered
16.1.3.3 Recent Developments
16.1.3.3.1 Other Developments
16.1.3.4 Analyst's View
16.1.3.4.1 Right to Win
16.1.3.4.2 Strategic Choices
16.1.3.4.3 Weaknesses & Competitive Threats
16.1.4 Tempus AI, Inc.
16.1.4.1 Business Overview
16.1.4.2 Products/Services/Solutions Offered
16.1.4.3 Recent Developments
16.1.4.3.1 Solution Launches
16.1.4.3.2 Deals
16.1.4.3.3 Other Developments
16.1.4.4 Analyst's View
16.1.4.4.1 Right to Win
16.1.4.4.2 Strategic Choices
16.1.4.4.3 Weaknesses & Competitive Threats
16.1.5 Nvidia Corporation
16.1.5.1 Business Overview
16.1.5.2 Products/Services/Solutions Offered
16.1.5.3 Recent Developments
16.1.5.3.1 Product and Service Launches
16.1.5.3.2 Deals
16.1.5.4 Analyst's View
16.1.5.4.1 Right to Win
16.1.5.4.2 Strategic Choices
16.1.5.4.3 Weaknesses & Competitive Threats
16.1.6 Saama
16.1.6.1 Business Overview
16.1.6.2 Products/Services/Solutions Offered
16.1.6.3 Recent Developments
16.1.6.3.1 Solution Launches
16.1.6.3.2 Deals
16.1.7 Phesi
16.1.7.1 Business Overview
16.1.7.2 Products/Services/Solutions Offered
16.1.7.3 Recent Developments
16.1.7.3.1 Solution Launches
16.1.7.3.2 Deals
16.1.8 Pathai, Inc.
16.1.8.1 Business Overview
16.1.8.2 Products/Services/Solutions Offered
16.1.9 Unlearn.AI, Inc.
16.1.9.1 Business Overview
16.1.9.2 Products/Services/Solutions Offered
16.1.9.3 Recent Developments
16.1.9.3.1 Solution Launches
16.1.9.3.2 Deals
16.1.9.3.3 Other Developments
16.1.10 Deep6.AI
16.1.10.1 Business Overview
16.1.10.2 Products/Services/Solutions Offered
16.1.10.3 Recent Developments
16.1.10.3.1 Solution Launch
16.1.10.3.2 Deals
16.1.11 Microsoft
16.1.11.1 Business Overview
16.1.11.2 Products/Services/Solutions Offered
16.1.11.3 Recent Developments
16.1.12 IBM
16.1.12.1 Business Overview
16.1.12.2 Products/Services/Solutions Offered
16.1.12.3 Recent Developments
16.1.12.3.1 Deals
16.1.13 Concertai
16.1.13.1 Business Overview
16.1.13.2 Products/Services/Solutions Offered
16.1.13.3 Recent Developments
16.1.13.3.1 Solution Launches
16.1.13.3.2 Deals
16.1.13.3.3 Other Developments
16.1.14 Aicure
16.1.14.1 Business Overview
16.1.14.2 Products/Services/Solutions Offered
16.1.14.3 Recent Developments
16.1.14.3.1 Service Launches
16.1.14.3.2 Deals
16.1.15 Median Technologies
16.1.15.1 Business Overview
16.1.15.2 Products/Services/Solutions Offered
16.1.16 Lantern Pharma Inc.
16.1.16.1 Business Overview
16.1.16.2 Products/Services/Solutions Offered
16.1.16.3 Recent Developments
16.1.16.3.1 Deals
16.1.17 Citeline, a Norstella Company
16.1.17.1 Business Overview
16.1.17.2 Products/Services/Solutions Offered
16.1.17.3 Recent Developments
16.1.17.3.1 Solution Launches
16.1.17.3.2 Deals
16.1.18 Trinetx, LLC
16.1.18.1 Business Overview
16.1.18.2 Products/Services/Solutions Offered
16.1.18.3 Recent Developments
16.1.18.3.1 Deals
16.2 Other Players
16.2.1 Revivemed Inc.
16.2.2 Euretos
16.2.3 Verisim Life
16.2.4 Triomics
16.2.5 Ardigen
16.2.6 Quanthealth Ltd.
16.2.7 Deep Genomics

17 Appendix

17.1 Discussion Guide
17.2 Knowledgestore: The Subscription Portal
17.3 Customization Options

List of Figures

Figure 1 AI in Clinical Trials Market: Segments Considered
Figure 2 AI in Clinical Trials Market: Years Considered
Figure 3 AI in Clinical Trials Market: Research Design
Figure 4 AI in Clinical Trials Market: Key Data from Secondary Sources
Figure 5 AI in Clinical Trials Market: Key Primary Sources
Figure 6 AI in Clinical Trials Market: Key Data from Primary Sources
Figure 7 AI in Clinical Trials Market: Key Insights from Primaries
Figure 8 Breakdown of Primary Interviews (Demand Side): by Company Type, Designation, and Region
Figure 9 Market Size Estimation: Supply-Side Revenue Share Analysis
Figure 10 AI in Clinical Trials Market: Top-Down Approach
Figure 11 AI in Clinical Trials Market: CAGR Projections from Analysis of Drivers, Restraints, Opportunities, and Challenges
Figure 12 CAGR Projections: Supply-Side Analysis
Figure 13 AI in Clinical Trials Market: Data Triangulation
Figure 14 AI in Clinical Trials Market, by Offering, 2024 vs. 2030 (USD Million)
Figure 15 AI in Clinical Trials Market, by Function, 2024 vs. 2030 (USD Million)
Figure 16 AI in Clinical Trials Market, by Deployment Mode, 2024 vs. 2030 (USD Million)
Figure 17 AI in Clinical Trials Market, by Phase, 2024 vs. 2030 (USD Million)
Figure 18 AI in Clinical Trials Market, by Application, 2024 vs. 2030 (USD Million)
Figure 19 AI in Clinical Trials Market, by Technology, 2024 vs. 2030 (USD Million)
Figure 20 AI in Clinical Trials Market, by Indication, 2024 vs. 2030 (USD Million)
Figure 21 AI in Clinical Trials Market, by End-user, 2024 vs. 2030 (USD Million)
Figure 22 AI in Clinical Trials Market: Regional Snapshot
Figure 23 Need for Data Standardization and Favorable Government Policies to Drive Market
Figure 24 North America to Dominate AI in Clinical Trials Market During Forecast Period
Figure 25 US and Pharmaceutical & Biopharmaceutical Companies Accounted for Largest Share of North American Market in 2023
Figure 26 UK to Register Highest Growth Rate During Study Period
Figure 27 Developed Markets to Register Higher Growth Rates from 2024 to 2029
Figure 28 AI in Clinical Trials Market: Drivers, Restraints, Opportunities, and Challenges
Figure 29 Approval of Personalized Medicines by US Fda, 2015-2023
Figure 30 Healthcare Security Breaches of 500+ Records (2009-2023)
Figure 31 AI in Clinical Trials Market: Ecosystem Analysis
Figure 32 AI in Clinical Trials Market: Value Chain Analysis
Figure 33 AI in Clinical Trials Market: Porter's Five Forces Analysis
Figure 34 Influence of Key Stakeholders on Buying Process for Top Three End-users
Figure 35 Key Buying Criteria for Top Three End-users
Figure 36 Patent Publication Trends in AI in Clinical Trials Market, 2015-2024
Figure 37 Top Applicants/Owners of Patents and Number of Patents Granted, January 2015-November 2024
Figure 38 AI in Clinical Trials Market: Trends and Disruptions Impacting Customer's Business
Figure 39 AI in Clinical Trials Market: Funding and Number of Deals, 2022-2024
Figure 40 Impact of AI/Gen AI on AI-based Clinical Trial Solutions
Figure 41 Impact of Gen AI on Interconnected and Adjacent Ecosystems
Figure 42 North America: AI in Clinical Trials Market Snapshot
Figure 43 Asia-Pacific: AI in Clinical Trials Market Snapshot
Figure 44 Revenue Analysis of Key Players in AI in Clinical Trials Market, 2019-2023 (USD Billion)
Figure 45 Market Share Analysis in AI in Clinical Trials Market (2023)
Figure 46 Ranking of Key Players in AI in Clinical Trials Market (2023)
Figure 47 AI in Clinical Trials Market: Company Evaluation Matrix (Key Players), 2023
Figure 48 AI in Clinical Trials Market: Company Footprint
Figure 49 AI in Clinical Trials Market: Company Evaluation Matrix (Startups/SMEs), 2023
Figure 50 EV/Ebitda of Key Vendors
Figure 51 Year-To-Date (Ytd) Price Total Return and 5-Year Stock Beta of AI in Clinical Trial Key Vendors
Figure 52 AI in Clinical Trials Market: Brand/Product Comparative Analysis
Figure 53 Iqvia Inc.: Company Snapshot
Figure 54 Dassault Systèmes (Medidata): Company Snapshot
Figure 55 Nvidia Corporation: Company Snapshot
Figure 56 Microsoft: Company Snapshot
Figure 57 IBM: Company Snapshot
Figure 58 Median Technologies: Company Snapshot

Companies Mentioned

Iqvia Inc.
Dassault Systèmes (Medidata)
Insilico Medicine
Tempus AI, Inc.
Nvidia Corporation
Saama
Phesi
Pathai, Inc.
Unlearn.AI, Inc.
Deep6.AI
Microsoft
IBM
Concertai
Aicure
Median Technologies
Lantern Pharma Inc.
Citeline, a Norstella Company
Trinetx, LLC
Revivemed Inc.
Euretos
Verisim Life
Triomics
Ardigen
Quanthealth Ltd.
Deep Genomics

Table Information

Report Attribute	Details
No. of Pages	373
Published	December 2024
Forecast Period	2024 - 2030
Estimated Market Value ( USD ) in 2024	$ 1.35 Billion
Forecasted Market Value ( USD ) by 2030	$ 2.74 Billion
Compound Annual Growth Rate	12.4%
Regions Covered	Global
No. of Companies Mentioned	25

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AI in Clinical Trials Market by Function, Phase, Indication, Tool, End-User & Region - Global Forecast to 2030

Infectious diseases had the fastest growth rate in the AI in clinical trials market during the forecast period, by indication.

By end user, the pharmaceutical & biopharma companies to account for largest market share in 2023.

Asia Pacific is estimated to register the highest CAGR over the forecast period.

Breakdown of supply-side primary interviews by company type, designation, and region:

List of Companies Profiled in the Report:

Research Coverage:

Reasons to Buy the Report

The report provides insights on the following pointers:

Table of Contents

Companies Mentioned

Table Information

Infectious diseases had the fastest growth rate in the AI in clinical trials market during the forecast period, by indication.

By end user, the pharmaceutical & biopharma companies to account for largest market share in 2023.

Asia Pacific is estimated to register the highest CAGR over the forecast period.

Breakdown of supply-side primary interviews by company type, designation, and region:

List of Companies Profiled in the Report:

Research Coverage:

Reasons to Buy the Report

The report provides insights on the following pointers:

Table of Contents

Companies Mentioned

Table Information

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About the AI Based Clinical Trials Market