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市场调查报告书
商品编码
1371876

到 2030 年临床试验中的人工智慧市场预测：按部署模式、技术、用途、最终用户和地区进行的全球分析

Artificial Intelligence in Clinical Trials Market Forecasts to 2030 - Global Analysis By Deployment Mode, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据Stratistics MRC的数据，2023年全球人工智慧（AI）临床试验市场规模为18.8亿美元，预计到2030年将达到92.8亿美元，预测期内年复合成长率为25.6，预计将成长%。

临床试验中的人工智慧（AI）是指在临床试验和药物研发过程中使用人工智慧工具和解决方案，包括设计试验计划、选择试验地点以及规划患者招募和监测系统。在临床试验中使用人工智慧技术可以透过更快地提供结果并增加临床试验中使用的人群的多样性来帮助克服传统临床试验程序的缺点。

根据世界卫生组织（WHO）的数据，2021年，美国在临床试验领域处于领先地位，过去20年度註册的临床试验约为157,618项。

对抗罕见疾病和遗传疾病的药物需求不断增长

基因治疗和癌症药物开发部门的研究和开发提供了应用人工智慧工具和技术为这些疾病创造新的、强大的治疗方法的机会。由于一些罕见疾病的发展和研究，最近增加了使用基于人工智慧的临床试验来加快设计试验的过程，以确定特定疾病的原因并检查潜在治疗方法的有效性。此外，已开发国家和新兴国家的政府都在推动临床试验并增加患者的参与，从而扩大了市场。

严格法规

医疗保健领域人工智慧的法规环境仍在不断发展。确保人工智慧系统符合法规要求，例如食品药物管理局(FDA) 制定的要求，可能会成为采用的障碍。开发和实施人工智慧解决方案成本高且资源密集。此外，规模较小的研究机构和医疗保健提供者可能面临资金和专业知识方面的挑战。

加大人工智慧投资

过去年度，全球许多投资人曾向为临床试验提供人工智慧软体和服务的企业投资了近25亿美元，证明了市场兴趣日益浓厚。在创投轮之后，种子轮融资筹集了大部分资金。此外，百时美施贵宝、默克、诺华、辉瑞、赛诺菲等大型製药公司也在投资用于临床试验的人工智慧软体和服务供应商，开闢了广泛的市场机会。

临床试验中无法获得健康资料

临床试验中的人工智慧技术需要分析大量现有资料，以获得有助于推进临床试验的重要见解。目前可用的资料可能不足以开发针对新发现或未知疾病（例如冠状病毒）的治疗方法。如果历史资料不可靠，基于人工智慧的解决方案的有效性可能会受到限制。此外，任何参考资料资料的偏差都会使人工智慧支援的临床试验的结论和结果产生偏差。这些条件可能会限制市场扩张。

COVID-19 的影响：

COVID-19 的爆发促使人们更多地使用基于人工智慧的技术。由于多种要素，包括越来越多地采用技术先进的药物研发发现和开发解决方案以及对招募的患者资料进行分析，基于人工智慧的药物开发和临床实验解决方案正在广泛使用。分散式药物临床实验也有所增加，因为许多临床实验试验因 COVID-19 而被搁置，并且许多大公司在此期间专注于汇总可存取的患者资料。

预计肿瘤学将成为预测期内最大的领域

肿瘤学领域将在预测期内继续增长，因为癌症治疗的需求不断增长以及该领域进行的大量药物临床试验正在影响人工智慧技术在该应用领域的采用。预计将占到市场占有率最大。此外，许多参与者正在创建和利用以肿瘤学为中心的人工智慧工具进行临床试验，这正在推动领域的扩张。

预计製药领域在预测期内年复合成长率最高

製药公司业务预计将迅速扩张。越来越多地采用人工智慧技术可以提高临床试验的生产力和有效性。此外，跨产业的伙伴关係和协作也正在发生，以在整个研发和开发过程中利用人工智慧作为工具。这些因素正在推动该细分市场的成长。

比最大的地区

北美目前在基于人工智慧的临床试验解决方案提供商市场中占据主导地位，预计这种主导地位在预测期内将持续下去。这是由于该地区存在多家基于人工智慧的新兴企业。采用基于人工智慧的技术来改善药物测试结果以及对这些技术的认识不断提高正在推动该地区的市场成长。该地区对基于人工智慧的临床试验解决方案的需求也受到政府配合措施和领先公司不断增长的战略倡议的推动。

复合年复合成长率最高的地区：

在基于人工智慧的工具越来越多地采用以及政府在各个医疗保健领域实施人工智慧的配合措施的推动下，亚太地区预计将见证基于人工智慧的临床试验解决方案提供者的市场成长率。成为最高的。由于其广泛的患者基础和较低的试验成本，亚洲的临床试验招募人数正在增加。此外，Novotech 执行长表示，临床阶段生物技术公司现在正在寻求亚太地区加快患者入组速度，特别是在感染疾病。这些因素预计将增加基于人工智慧的临床试验分析和解释解决方案的采用，从而导致市场扩张。

提供免费客製化：

订阅此报告的客户可以存取以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和年复合成长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第1章执行摘要

第2章前言

  • 概述
  • 利害关係人
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 调查来源
    • 主要调查来源
    • 二次调查来源
    • 先决条件

第3章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • 新型冠状病毒感染疾病（COVID-19）的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第5章全球人工智慧（AI）临床试验市场：依临床实验阶段划分

  • 第一阶段
  • 第二阶段
  • 第三阶段
  • 第四阶段

第6章全球临床试验市场中的人工智慧（AI）：按技术分类

  • 机器学习
  • 深度学习
  • 影像分析
  • 自然语言处理（NLP）
  • 预测分析
  • 监督学习
  • 其他技术

第7章全球临床试验市场中的人工智慧（AI）：按应用分类

  • 心血管疾病
  • 免疫疾病
  • 感染疾病
  • 代谢性疾病
  • 神经系统疾病
  • 肿瘤学
  • 其他用途

第8章临床试验市场中的全球人工智慧（AI）：按最终用户分类

  • 製药公司
  • 合约研究组织（CRO）
  • 学术界
  • 其他最终用户

第9章全球临床试验市场中的人工智慧（AI）：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲

第10章进展

  • 合约、伙伴关係、协作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第11章公司简介

  • 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
  • Unlearn.AI, Inc.
Product Code: SMRC23932

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.

List of Tables

  • Table 1 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Trial Phase (2021-2030) ($MN)
  • Table 3 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Phase I (2021-2030) ($MN)
  • Table 4 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Phase II (2021-2030) ($MN)
  • Table 5 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Phase III (2021-2030) ($MN)
  • Table 6 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Phase IV (2021-2030) ($MN)
  • Table 7 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Technology (2021-2030) ($MN)
  • Table 8 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Machine Learning (2021-2030) ($MN)
  • Table 9 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Deep Learning (2021-2030) ($MN)
  • Table 10 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Image Analysis (2021-2030) ($MN)
  • Table 11 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Natural Language Processing (NLP) (2021-2030) ($MN)
  • Table 12 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Predictive Analytics (2021-2030) ($MN)
  • Table 13 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Supervised Learning (2021-2030) ($MN)
  • Table 14 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Other Technologies (2021-2030) ($MN)
  • Table 15 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Application (2021-2030) ($MN)
  • Table 16 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Cardiovascular Diseases (2021-2030) ($MN)
  • Table 17 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Immunology Disease (2021-2030) ($MN)
  • Table 18 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Infectious Disease (2021-2030) ($MN)
  • Table 19 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Metabolic Diseases (2021-2030) ($MN)
  • Table 20 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Neurological Diseases (2021-2030) ($MN)
  • Table 21 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Oncology (2021-2030) ($MN)
  • Table 22 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Other Applications (2021-2030) ($MN)
  • Table 23 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By End User (2021-2030) ($MN)
  • Table 24 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Pharmaceutical Companies (2021-2030) ($MN)
  • Table 25 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Contract Research Organizations (CROs) (2021-2030) ($MN)
  • Table 26 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Academia (2021-2030) ($MN)
  • Table 27 Global Artificial Intelligence (AI) in Clinical Trials Market Outlook, By Other End Users (2021-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.