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临床实验人工智能

市场调查报告书

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1535897

临床试验中的人工智慧市场规模- 按组件（软体、服务）、按技术（机器学习(ML)、自然语言处理(NLP)、电脑视觉、情境机器人）、按应用、按最终用户和预测，2024 - 2032 年

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

出版日期: 2024年06月21日 | 出版商:

Global Market Insights Inc. | 英文 270 Pages | 商品交期: 2-3个工作天内

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简介目录

在人工智慧技术和个人化医疗不断进步的推动下，2024 年至 2032 年间，全球人工智慧临床试验市场规模将达到 14% 的复合年增长率。增强的人工智慧演算法可以实现更准确的资料分析、更快的药物开发并提高试验效率。此外，个人化医疗的兴起允许根据个别患者资料制定客製化治疗计划，优化治疗结果。随着人工智慧技术的发展和个人化方法变得更加普遍，它们的综合影响将加速临床试验，使其更有效率和有效，从而扩大市场。

例如，2023 年 11 月，阿斯特捷利康推出 Evinova，将人工智慧和数位健康解决方案整合到临床试验中，针对 CRO、试验申办者、照护团队和患者，利用该公司已在全球使用的技术。此举显示将先进技术融入临床研究、推动创新、改善试验结果以及潜在增加市场采用的趋势不断上升。随着阿斯特捷利康等主要参与者采用人工智慧，这凸显了人工智慧在改变临床试验流程和结果方面的不断扩大的作用。

临床试验产业中的人工智慧根据组件、技术、应用、最终用户和地区进行细分。

机器学习领域将在 2024 年至 2032 年期间大幅成长。机器学习演算法在处理大量临床资料、识别模式和预测试验结果方面发挥关键作用。这些功能显着减少了资料分析所需的时间并提高了决策的准确性。製药公司越来越多地利用机器学习来优化患者选择、监控试验进度并确保符合监管标准。将机器学习整合到临床试验中可以提高效率并提高试验的整体质量，支持市场扩张。

到 2032 年，药物发现领域将获得可观的效益，这归因于其对加速药物开发进程的变革性影响。人工智慧技术增强了预测模型，优化了临床试验设计，并更有效地识别潜在的候选药物，从而大大减少了时间和成本。先进的演算法分析大量数据集，以发现新的药物交互作用和生物标誌物，从而产生更有针对性的治疗方法。随着製药公司越来越多地采用人工智慧来简化发现和提高成功率，这一领域将占据相当大的市场份额。

亚太地区人工智慧临床试验市场将在2024年至2032年实现适度的复合年增长率。有利的环境。由于改善医疗保健结果和解决日益严重的慢性病负担的需要，中国、印度和日本等国家处于将人工智慧技术融入临床试验的最前沿。大量患者群体的存在和先进技术解决方案的可用性进一步支持亚太地区人工智慧在临床试验行业的扩张。

产业生态系统分析
供应商格局
- 平台提供者
- 软体供应商
- 服务商
- 配销通路
- 最终用户
利润率分析
技术与创新格局
专利分析
重要新闻和倡议
监管环境
衝击力
- 成长动力
  - 加速药物开发和发现
  - 改善病患招募
  - 增强的资料分析和即时监控
  - 个人化医疗的需求不断成长
- 产业陷阱与挑战
  - 资料隐私和安全问题
  - 与现有系统集成
成长潜力分析
波特的分析
PESTEL分析

第 4 章：竞争格局

介绍
公司市占率分析
竞争定位矩阵
战略展望矩阵

第 5 章：市场估计与预测：按组成部分，2021 - 2032 年

主要趋势
软体
- 第一阶段
- 第二阶段
- 第三阶段
服务
- 第一阶段
- 第二阶段
- 第三阶段

第 6 章：市场估计与预测：依技术分类，2021 - 2032

主要趋势
机器学习
自然语言处理（NLP）
电脑视觉
情境机器人
其他的

第 7 章：市场估计与预测：依应用分类，2021 - 2032

主要趋势
药物开发
药物发现
临床试验管理
- 病患招募
- 临床试验监测
- 临床资料管理
- 基于风险的监控
其他的

第 8 章：市场估计与预测：按最终用户划分，2021 - 2032 年

主要趋势
製药和生物技术公司
合约研究组织 (CRO)
学术及研究机构
其他的

第 9 章：市场估计与预测：按地区，2021 - 2032

主要趋势
北美洲
- 我们
- 加拿大
欧洲
- 英国
- 德国
- 法国
- 义大利
- 西班牙
- 俄罗斯
- 北欧人
- 欧洲其他地区
亚太地区
- 中国
- 印度
- 日本
- 澳洲
- 韩国
- 东南亚
- 亚太地区其他地区
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
- 拉丁美洲其他地区
MEA
- 阿联酋
- 南非
- 沙乌地阿拉伯
- MEA 的其余部分

第 10 章：公司简介

BenevolentAI Ltd.
ConcertAI, Inc.
Exscientia Ltd.
GNS Healthcare
Halo Health Systems
IBM (International Business Machines Corporation)
Insilico Medicine, Inc.
IQVIA Holdings Inc.
Medidata Solutions, Inc.
Nuance Communications, Inc.
Numerate
NVIDIA Corporation
Owkin Inc.
Parexel International Corporation
Prometheus Biosciences Inc.
Renalytix AI plc
ReviveMed Ltd.
Saama Technologies, Inc.
Sensyne Health plc
TrialTrove Inc.

简介目录

Product Code: 9965

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.

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
3.9 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