세계 임상시험 분야 인공지능(AI) 시장 : 전개 모드별, 기술별, 용도별, 최종사용자별 및 지역별 분석(-2030년)_

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Clinical Trials Market is accounted for $1.88 billion in 2023 and is expected to reach $9.28 billion by 2030 growing at a CAGR of 25.6% during the forecast period. Artificial intelligence (AI) in clinical trials refers to the use of artificial intelligence tools and solutions in clinical trials and drug discovery processes, including designing the trial plan, choosing the trial site, and planning the patient recruitment and monitoring systems. By producing results more quickly and increasing the diversity of the population used in a clinical trial, the use of AI technology in clinical trials aids in overcoming the drawbacks of traditional clinical trial procedures.

According to the World Health Organization, in 2021, the USA is leading in the clinical trial field and has registered approximately 157,618 clinical trials over the last two decades.

Market Dynamics:

Driver:

Increasing need for drugs to combat rare and genetic diseases

The research and development conducted in the division that develops genetic and oncological drugs presents an opportunity to apply AI tools and technology to create new, potent treatments for these diseases. The use of AI-based clinical trials to expedite the process of identifying the cause of origin of a specific disease and designing a trial plan to examine the efficacy of a potential treatment has increased recently due to developments in the genetic context and research on some rare diseases. Additionally, governments in both developed and developing countries are working hard to promote clinical trials and entice patients to participate, which is expanding the market.

Restraint:

Stringent regulations

The regulatory landscape for AI in healthcare is still evolving. Ensuring that AI systems meet regulatory requirements, such as those set by the Food and Drug Administration (FDA), can be a barrier to adoption. Developing and implementing AI solutions can be expensive and resource-intensive. Moreover, smaller research organizations and healthcare providers may face challenges in terms of funding and expertise.

Opportunity:

Rising investment in AI

In the last five years, close to $2.5 billion has been invested in businesses that provide AI software and services for clinical trials by a number of investors based all over the world, which serves as evidence of the increased interest in the market for clinical trials that use AI. Following venture rounds, seed financing rounds were used to raise the majority of the money. Moreover, major pharmaceutical companies, including Bristol-Myers Squibb, Merck, Novartis, Pfizer, and Sanofi, have also invested in AI software and service providers for clinical trials, opening up a wide range of market opportunities.

Threat:

Unavailability of health data in clinical trials

AI technology in clinical trials necessitates the analysis of sizable pre-existing datasets in order to produce significant insights that will aid in the advancement of clinical trials. To create medications for any newly discovered or unidentified diseases, such as the Corona virus, the datasets currently available may not be sufficient. The effectiveness of AI-based solutions may be constrained in cases where historical data cannot be trusted. Additionally, the existence of bias in any of the reference datasets may result in biased conclusions and outcomes in clinical trials supported by AI. These situations might limit market expansion.

COVID-19 Impact:

The COVID-19 epidemic prompted a rise in the use of AI-based technologies. AI-based drug development and drug trial solutions are becoming more widely used due to a number of factors, including the increasing adoption of technologically advanced drug discovery and development solutions and the analysis of recruited patient data. Decentralized drug trials also saw a rise as a result of COVID-19, which caused many trials to be put on hold and led many major players to focus on compiling patient data that was accessible during this period.

The oncology segment is expected to be the largest during the forecast period

The oncology segment is anticipated to hold the largest market share during the forecast period due to the rising demand for cancer treatments and the significant number of drug trials conducted in this field, both of which have influenced the adoption of AI-enabled technologies in this application space. Additionally, a lot of players are creating and utilizing AI tools with an oncology focus for clinical trials, which is driving the segment's expansion.

The pharmaceutical companies segment is expected to have the highest CAGR during the forecast period

It is anticipated that the pharmaceutical companies segment will expand rapidly. The increasing adoption of AI-enabled technologies can increase clinical trials' productivity and efficacy. Additionally, cross-industry partnerships and collaborations are also being made in order to use AI as a tool for R&D and the entire development process. Such elements are propelling this segment's growth.

Region with largest share:

North America currently dominates the market for providers of AI-based clinical trial solutions, and this dominance is anticipated to persist over the forecast period. This is explained by the fact that the area is home to several AI-based start-ups. The adoption of AI-based technologies to improve the results of drug trials and rising awareness of these technologies are driving market growth in the area. The demand for AI-based clinical trial solutions in the region is also being driven by encouraging government initiatives and growing strategic initiatives by major players.

Region with highest CAGR:

Due to the increasing adoption of AI-based tools and supportive government initiatives for the adoption of AI in various healthcare fields, Asia Pacific is expected to have the highest growth rate for the market for providers of AI-based clinical trial solutions. Due to an extensive patient base and low trial costs, clinical trial recruitment is growing in Asia. Additionally, according to the CEO of Novotech, clinical-phase biotechnology companies now recognize Asia Pacific for accelerated patient enrollment, particularly in infectious diseases. These elements are predicted to increase the adoption of AI-based clinical trial analysis and interpretation solutions, leading to market expansion.

Key players in the market:

Some of the key players in Artificial Intelligence (AI) in Clinical Trials market include: AiCure, LLC, Antidote Technologies, Ardigen, BioAge Labs, Inc., BioSymetrics, CONSILX, Deep 6 AI, DEEP LENS AI, Euretos, Exscientia, GNS Healthcare, Verily, Halo Health Systems, IBM Watson, Innoplexus, Intelligencia, IQVIA, Koneksa Health, Median Technologies, Mendel.ai, Pharmaseal, Phesi, Saama Technologies, Signant Health, Symphony AI, Trials.ai and Unlearn.AI, Inc.

Key Developments:

In October 2023, SymphonyAI, a leader in predictive and generative AI enterprise AI SaaS, today announced the Sensa Investigation Hub, a generative AI-enabled investigation and case management platform that propels financial institutions into the future of financial crime management.

In August 2023, EY announces strategic alliance with SymphonyAI to help digitally transform organizations with generative AI-enabled retail and financial services platforms. The Alliance will also support the expansion of AI-based solution delivery for retailers, including computer vision-based intelligence capabilites to improve store operations. It will also help to enhance customer experience and digital-industrial manufacturing, through asset management and worker connection solutions, which are intended to progress operations, yields and safety.

In February 2022, Unlearn and Merck KGaA have announced a partnership to accelerate drug trials using medical digital twins of patients. Unlearn uses recent developments from deep learning to create digital twins of patients in clinical trials. The new technique allows drug researchers to reduce the size of control arms by 30% or more and generate reliable clinical evidence in less time. Merck plans to focus on late-stage clinical trials for immunology drugs initially.

Trial Phases Covered:

• Phase I
• Phase II
• Phase III
• Phase IV

Technologies Covered:

• Machine Learning
• Deep Learning
• Image Analysis
• Natural Language Processing (NLP)
• Predictive Analytics
• Supervised Learning
• Other Technologies

Applications Covered:

• Cardiovascular Diseases
• Immunology Disease
• Infectious Disease
• Metabolic Diseases
• Neurological Diseases
• Oncology
• Other Applications

End Users Covered:

• Pharmaceutical Companies
• Contract Research Organizations (CROs)
• Academia
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Technology Analysis
• 3.7 Application Analysis
• 3.8 End User Analysis
• 3.9 Emerging Markets
• 3.10 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global Artificial Intelligence (AI) in Clinical Trials Market, By Trial Phase

• 5.1 Introduction
• 5.2 Phase I
• 5.3 Phase II
• 5.4 Phase III
• 5.5 Phase IV

6 Global Artificial Intelligence (AI) in Clinical Trials Market, By Technology

• 6.1 Introduction
• 6.2 Machine Learning
• 6.3 Deep Learning
• 6.4 Image Analysis
• 6.5 Natural Language Processing (NLP)
• 6.6 Predictive Analytics
• 6.7 Supervised Learning
• 6.8 Other Technologies

7 Global Artificial Intelligence (AI) in Clinical Trials Market, By Application

• 7.1 Introduction
• 7.2 Cardiovascular Diseases
• 7.3 Immunology Disease
• 7.4 Infectious Disease
• 7.5 Metabolic Diseases
• 7.6 Nuerological Diseases
• 7.7 Oncology
• 7.8 Other Applications

8 Global Artificial Intelligence (AI) in Clinical Trials Market, By End User

• 8.1 Introduction
• 8.2 Pharmaceutical Companies
• 8.3 Contract Research Organizations (CROs)
• 8.4 Academia
• 8.5 Other End Users

9 Global Artificial Intelligence (AI) in Clinical Trials Market, By Geography

• 9.1 Introduction
• 9.2 North America
  • 9.2.1 US
  • 9.2.2 Canada
  • 9.2.3 Mexico
• 9.3 Europe
  • 9.3.1 Germany
  • 9.3.2 UK
  • 9.3.3 Italy
  • 9.3.4 France
  • 9.3.5 Spain
  • 9.3.6 Rest of Europe
• 9.4 Asia Pacific
  • 9.4.1 Japan
  • 9.4.2 China
  • 9.4.3 India
  • 9.4.4 Australia
  • 9.4.5 New Zealand
  • 9.4.6 South Korea
  • 9.4.7 Rest of Asia Pacific
• 9.5 South America
  • 9.5.1 Argentina
  • 9.5.2 Brazil
  • 9.5.3 Chile
  • 9.5.4 Rest of South America
• 9.6 Middle East & Africa
  • 9.6.1 Saudi Arabia
  • 9.6.2 UAE
  • 9.6.3 Qatar
  • 9.6.4 South Africa
  • 9.6.5 Rest of Middle East & Africa

10 Key Developments

• 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 10.2 Acquisitions & Mergers
• 10.3 New Product Launch
• 10.4 Expansions
• 10.5 Other Key Strategies

11 Company Profiling

• 11.1 AiCure, LLC
• 11.2 Antidote Technologies
• 11.3 Ardigen
• 11.4 BioAge Labs, Inc.
• 11.5 BioSymetrics
• 11.6 CONSILX
• 11.7 Deep 6 AI
• 11.8 DEEP LENS AI
• 11.9 Euretos
• 11.10 Exscientia
• 11.11 GNS Healthcare
• 11.12 Verily
• 11.13 Halo Health Systems
• 11.14 IBM Watson
• 11.15 Innoplexus
• 11.16 Intelligencia
• 11.17 IQVIA
• 11.18 Koneksa Health
• 11.19 Median Technologies
• 11.20 Mendel.ai
• 11.21 Pharmaseal
• 11.22 Phesi
• 11.23 Saama Technologies
• 11.24 Signant Health
• 11.25 Symphony AI
• 11.26 Trials.ai
• 11.27 Unlearn.AI, Inc.