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市场调查报告书
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1454042

到 2030 年临床试验中的人工智慧市场预测：按产品类型、流程、应用、最终用户和地区进行的全球分析

AI in Clinical Trials Market Forecasts to 2030 - Global Analysis By Product (Methacrylic (Methacrylic Ester Copolymer), Modified Aromatic (Brominated Aromatic Matrix) and Other Products), Type, Process, 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 AIAI 临床试验市场规模将达到 19 亿美元，预计 2030 年将达到 105 亿美元，预测期内复合年增长率为 27.6%。

临床试验中的人工智慧是指利用人工智慧（AI）技术来增强临床试验过程的各个方面，从患者招募和资料分析到试验设计和药物开发。透过利用机器学习演算法和资料分析，人工智慧可以简化流程、识别合适的候选人、预测结果并优化测试通讯协定。这种人工智慧整合旨在提高效率、降低成本，并最终加速医疗保健行业新治疗方法和治疗方法的开发。

高盛研究预计，2023年全球製药业将花费约7,000亿美元用于研发和收购。

改善病患招募和保留的潜力

人工智慧技术为病人参与来提高保留率。透过先进的演算法，人工智慧可以简化患者选择流程，透过识别高风险个体来降低退出率，并根据即时资料分析优化试验通讯协定。这些功能预计将使临床试验更加高效和成功，最终推进医学研究并改善患者的治疗结果。这些都是市场成长的驱动因素。

资料隐私和安全问题

随着大量敏感患者资讯被收集和分析，确保采取强有力的安全措施防止资料外洩和未授权存取至关重要。个人健康资料的滥用和潜在滥用会引发道德和法律问题，并需要严格的法规结构。人工智慧技术的整合带来了资料匿名和同意管理的复杂性，需要在整个测试过程中仔细考虑隐私和安全通讯协定。因此，对资料隐私和安全的担忧是限制市场成长的因素。

扩大基于人工智慧的平台的使用

人工智慧系统利用机器学习和资料分析来改善患者招募、试验设计和资料分析。製药公司和研究机构正在利用人工智慧驱动的平台，透过管理大量资讯和预测患者反应的能力来加速药物开发并改善试验结果。市场正在扩大，因为人工智慧正在获得认可，并且具有突破性的能力，将改变临床研究和开发的格局。

实施成本高

成本由多种因素产生，包括对专业基础设施、先进人工智慧演算法、资料管理系统和监管合规措施的需求。儘管有潜在的好处，例如提高临床试验过程的效率和准确性，但公司必须仔细考虑在临床研究中采用人工智慧技术的财务影响。因此，由于实施成本高昂，人工智慧与临床试验的整合已成为重大挑战。

COVID-19 的影响：

COVID-19 大流行显着加速了人工智慧在临床试验中的采用。传统研究被颠覆，人工智慧为远端监控、资料分析和患者招募提供了解决方案。这提高了效率、降低了成本并缩短了测试完成时间。人工智慧促进了虚拟测试、远端患者监护和预测分析，使研究人员能够适应新常态。此外，人工智慧处理大量资料的能力对于识别模式和开发治疗方法变得至关重要。因此，COVID-19 成为临床试验市场人工智慧成长的催化剂。

预计深度学习领域在预测期内将是最大的

预计深度学习领域在预测期内将是最大的。深度学习演算法使研究人员和开发人员能够从大量医疗资料中提取有意义的见解，从而实现更高效的试验设计、更快的药物开发并改善患者的治疗结果。随着製药公司和研究机构越来越多地采用这些技术来提高其测试的有效性和成本效益，该市场的深度学习市场正在经历显着增长。

预计感染疾病领域在预测期内的复合年增长率最高。

由于需要高效、准确的解决方案，预计感染疾病产业在预测期内将出现最高的复合年增长率。人工智慧技术提供先进的分析、预测建模和资料解释，以增强决策流程。该细分市场的特点是创新的人工智慧演算法、强大的资料整合能力以及对监管合规性的关注，以确保治疗的安全性和有效性。

比最大的地区

由于技术进步以及医疗保健领域对高效和资料主导解决方案的需求不断增加，预计北美将在预测期内占据最大的市场占有率。人工智慧技术正在彻底改变临床试验的许多方面，包括患者招募、资料分析和个人化医疗。主要製药公司的存在、强大的医疗基础设施和支持性的法规环境等关键因素进一步促进了该地区市场的扩张。

复合年增长率最高的地区：

由于人口成长、人口老化和慢性病负担增加等因素，预计亚太地区在预测期内将维持最高复合年增长率。这导致对医疗基础设施和技术（包括人工智慧）的投资增加，以提高临床试验的效率和结果。该地区出现了众多专注于医疗保健和生命科学的人工智慧新兴企业。人工智慧、机器学习和资料分析技术正在该地区迅速发展。

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、预测和复合年增长率（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

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 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

第三章市场趋势分析

  • 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
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第五章临床试验中的全球人工智慧市场：透过提供

  • 软体
    • 临床试验管理系统（CTMS）
    • 电子资料撷取(EDC) 系统
    • 统计分析软体
  • 服务
    • 资料管理与分析
    • 监理咨询

第六章临床试验中的全球人工智慧市场：按技术分类

  • 老师有空
  • 深度学习
  • 机器学习
  • 自然语言处理
  • 电脑视觉
  • 预测分析
  • 其他技术

第七章临床试验中的全球人工智慧市场：按应用分类

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

第八章临床试验中的全球人工智慧市场：按最终用户划分

  • 製药和生物技术公司
  • 受託研究机构
  • 学术机构
  • 其他最终用户

第九章全球临床试验中的人工智慧市场：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 主要进展

  • 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

第十一章 公司简介

  • Antidote Technologies, Inc.
  • Innoplexus
  • Symphony AI
  • Saama Technologies
  • Intelligencia
  • Median Technologies
  • Paradigm Health Inc.
  • Halo Health Systems
  • Trials.Ai
  • Pharmaseal
  • Koneksa Health
  • GNS Healthcare
  • Google-Verily
  • AstraZeneca
  • AiCure, LLC
  • BioSymetrics
  • Euretos
  • Ardigen
Product Code: SMRC25594

According to Stratistics MRC, the Global AI in Clinical Trials Market is accounted for $1.9 billion in 2023 and is expected to reach $10.5 billion by 2030 growing at a CAGR of 27.6% during the forecast period. AI in clinical trials refers to the utilization of artificial intelligence (AI) technologies to enhance various aspects of the trial process, from patient recruitment and data analysis to trial design and drug development. By leveraging machine learning algorithms and data analytics, AI can streamline processes, identify suitable candidates, predict outcomes, and optimize trial protocols. This integration of AI aims to improve efficiency, reduce costs, and ultimately accelerate the development of new therapies and treatments within the healthcare industry.

According to estimates by Goldman Sachs Research, the global pharmaceutical industry will have about $700 billion in 2023 to spend on R&D and acquisitions of other businesses.

Market Dynamics:

Driver:

Potential for improved patient recruitment and retention

AI technologies offer tailored approaches for patient engagement, utilizing predictive analytics to identify suitable candidates and personalized interventions to improve retention rates. Through advanced algorithms, AI can streamline patient selection processes, mitigate dropout rates by identifying at-risk individuals, and optimize trial protocols based on real-time data analysis. These capabilities hold promise for more efficient and successful clinical trials, ultimately advancing medical research and improving patient outcomes. These are the factors propelling the growth of the market.

Restraint:

Data privacy and security concerns

With vast amounts of sensitive patient information being collected and analyzed, ensuring robust safeguards against data breaches and unauthorized access is paramount. The potential for misuse or exploitation of personal health data raises ethical and legal questions, demanding stringent regulatory frameworks. The integration of AI technologies introduces complexities in data anonymization and consent management, necessitating careful consideration of privacy and security protocols throughout the trial process. Hence, data privacy and security concerns are the factors restraining the growth of the market.

Opportunity:

Growing usage of AI-based platform

AI systems improve patient recruitment, trial design, and data analysis by utilizing machine learning and data analytics. Pharmaceutical businesses and research institutions are utilizing AI-powered platforms to accelerate medication development and enhance trial outcomes, owing to its capacity to manage extensive information and forecast patient reactions. The market is expanding because of the growing acceptance of AI and its revolutionary ability to change the clinical research and development landscape.

Threat:

High implementation costs

The costs arise from various factors, including the need for specialized infrastructure, sophisticated AI algorithms, data management systems, and regulatory compliance measures. Despite the potential benefits, such as improved efficiency and accuracy in trial processes, organizations must carefully weigh the financial implications of adopting AI technologies in clinical research. Therefore, the integration of AI in Clinical Trials presents substantial challenges due to high implementation costs.

Covid-19 Impact:

The COVID-19 pandemic significantly accelerated the adoption of AI in clinical trials. With traditional research disrupted, AI offered solutions for remote monitoring, data analysis, and patient recruitment. This led to increased efficiency, reduced costs, and faster trial completion times. AI facilitated virtual trials, remote patient monitoring, and predictive analytics, enabling researchers to adapt to the new normal. Furthermore, AI's ability to handle vast amounts of data became crucial in identifying patterns and developing treatments. Thus, COVID-19 acted as a catalyst for the growth of AI in the clinical trials market.

The deep learning segment is expected to be the largest during the forecast period

The deep learning segment is expected to be the largest during the forecast period. By leveraging deep learning algorithms, researchers can extract meaningful insights from vast amounts of medical data, leading to more efficient trial designs, faster drug development, and improved patient outcomes. The market for deep learning in the market is witnessing significant growth as pharmaceutical companies and research institutions increasingly adopt these technologies to enhance the efficacy and cost-effectiveness of their trials.

The infectious diseases segment is expected to have the highest CAGR during the forecast period

The infectious diseases segment is expected to have the highest CAGR during the forecast period driven by the need for efficient and accurate solutions. AI technologies offer advanced analytics, predictive modeling, and data interpretation, enhancing decision-making processes. This market segment is characterized by innovative AI algorithms, robust data integration capabilities, and a focus on regulatory compliance to ensure the safety and efficacy of treatments.

Region with largest share:

North America is projected to hold the largest market share during the forecast period driven by technological advancements and increasing demand for efficient and data-driven solutions in healthcare. AI technologies are revolutionizing various aspects of clinical trials, including patient recruitment, data analysis, and personalized medicine. Key factors such as the presence of major pharmaceutical companies, robust healthcare infrastructure, and supportive regulatory environment further contribute to the expansion of this market in the region.

Region with highest CAGR:

Asia Pacific is projected to hold the highest CAGR over the forecast period driven by factors such as population growth, aging demographics, and the growing burden of chronic diseases. This increased investment in healthcare infrastructure and technology, including AI, to improve clinical trial efficiency and outcomes. The region was witnessing the emergence of numerous AI startups specializing in healthcare and life sciences. The region has seen rapid advancements in AI, machine learning, and data analytics technologies.

Key players in the market

Some of the key players in AI in Clinical Trials market include Antidote Technologies, Inc.,m Innoplexus, Symphony AI, Saama Technologies, Intelligencia, Median Technologies, Paradigm Health Inc., Halo Health Systems, Trials.Ai, Pharmaseal, Koneksa Health, GNS Healthcare, Google- Verily, AstraZeneca, AiCure, LLC, BioSymetrics, Euretos and Ardigen.

Key Developments:

In November 2023, AstraZeneca announced the opening of Evinova, a health technology firm whose goal is to provide patients, clinical research organizations (CROs), trial sponsors, care teams, and other stakeholders with access to digital health solutions that the pharmaceutical giant already uses on a worldwide scale.

In January 2023, Paradigm Health Inc., a US-based healthcare technology company, acquired Deep Lens Inc. for an undisclosed amount. The acquisition aims to provide Paradigm with Deep Lens's platform, which enables equal access to trials for all patients while enhancing trial efficiency and reducing the barriers to participation for healthcare providers.

Offerings Covered:

  • Software
  • Services

Technologies Covered:

  • Supervised
  • Deep learning
  • Machine learning
  • Natural Language Processing
  • Computer Vision
  • Predictive Analytics
  • Other Technologies

Applications Covered:

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

End Users Covered:

  • Pharmaceutical & Biotechnology Companies
  • Contract Research Organizations
  • Academic Institutions
  • 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 AI in Clinical Trials Market, By Offering

  • 5.1 Introduction
  • 5.2 Software
    • 5.2.1 Clinical Trial Management Systems (CTMS)
    • 5.2.2 Electronic Data Capture (EDC) Systems
    • 5.2.3 Statistical Analysis Software
  • 5.3 Services
    • 5.3.1 Data Management and Analysis
    • 5.3.2 Regulatory Consulting

6 Global AI in Clinical Trials Market, By Technology

  • 6.1 Introduction
  • 6.2 Supervised
  • 6.3 Deep learning
  • 6.4 Machine learning
  • 6.5 Natural Language Processing
  • 6.6 Computer Vision
  • 6.7 Predictive Analytics
  • 6.8 Other Technologies

7 Global AI in Clinical Trials Market, By Application

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

8 Global AI in Clinical Trials Market, By End User

  • 8.1 Introduction
  • 8.2 Pharmaceutical & Biotechnology Companies
  • 8.3 Contract Research Organizations
  • 8.4 Academic Institutions
  • 8.5 Other End Users

9 Global 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 Antidote Technologies, Inc.
  • 11.2 Innoplexus
  • 11.3 Symphony AI
  • 11.4 Saama Technologies
  • 11.5 Intelligencia
  • 11.6 Median Technologies
  • 11.7 Paradigm Health Inc.
  • 11.8 Halo Health Systems
  • 11.9 Trials.Ai
  • 11.10 Pharmaseal
  • 11.11 Koneksa Health
  • 11.12 GNS Healthcare
  • 11.13 Google- Verily
  • 11.14 AstraZeneca
  • 11.15 AiCure, LLC
  • 11.16 BioSymetrics
  • 11.17 Euretos
  • 11.18 Ardigen

List of Tables

  • Table 1 Global AI in Clinical Trials Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global AI in Clinical Trials Market Outlook, By Offering (2021-2030) ($MN)
  • Table 3 Global AI in Clinical Trials Market Outlook, By Software (2021-2030) ($MN)
  • Table 4 Global AI in Clinical Trials Market Outlook, By Clinical Trial Management Systems (CTMS) (2021-2030) ($MN)
  • Table 5 Global AI in Clinical Trials Market Outlook, By Electronic Data Capture (EDC) Systems (2021-2030) ($MN)
  • Table 6 Global AI in Clinical Trials Market Outlook, By Statistical Analysis Software (2021-2030) ($MN)
  • Table 7 Global AI in Clinical Trials Market Outlook, By Services (2021-2030) ($MN)
  • Table 8 Global AI in Clinical Trials Market Outlook, By Data Management and Analysis (2021-2030) ($MN)
  • Table 9 Global AI in Clinical Trials Market Outlook, By Regulatory Consulting (2021-2030) ($MN)
  • Table 10 Global AI in Clinical Trials Market Outlook, By Technology (2021-2030) ($MN)
  • Table 11 Global AI in Clinical Trials Market Outlook, By Supervised (2021-2030) ($MN)
  • Table 12 Global AI in Clinical Trials Market Outlook, By Deep learning (2021-2030) ($MN)
  • Table 13 Global AI in Clinical Trials Market Outlook, By Machine learning (2021-2030) ($MN)
  • Table 14 Global AI in Clinical Trials Market Outlook, By Natural Language Processing (2021-2030) ($MN)
  • Table 15 Global AI in Clinical Trials Market Outlook, By Computer Vision (2021-2030) ($MN)
  • Table 16 Global AI in Clinical Trials Market Outlook, By Predictive Analytics (2021-2030) ($MN)
  • Table 17 Global AI in Clinical Trials Market Outlook, By Other Technologies (2021-2030) ($MN)
  • Table 18 Global AI in Clinical Trials Market Outlook, By Application (2021-2030) ($MN)
  • Table 19 Global AI in Clinical Trials Market Outlook, By Neurological (2021-2030) ($MN)
  • Table 20 Global AI in Clinical Trials Market Outlook, By Cardiovascular (2021-2030) ($MN)
  • Table 21 Global AI in Clinical Trials Market Outlook, By Metabolic (2021-2030) ($MN)
  • Table 22 Global AI in Clinical Trials Market Outlook, By Oncology (2021-2030) ($MN)
  • Table 23 Global AI in Clinical Trials Market Outlook, By Infectious Diseases (2021-2030) ($MN)
  • Table 24 Global AI in Clinical Trials Market Outlook, By Immunology Diseases (2021-2030) ($MN)
  • Table 25 Global AI in Clinical Trials Market Outlook, By Other Applications (2021-2030) ($MN)
  • Table 26 Global AI in Clinical Trials Market Outlook, By End User (2021-2030) ($MN)
  • Table 27 Global AI in Clinical Trials Market Outlook, By Pharmaceutical & Biotechnology Companies (2021-2030) ($MN)
  • Table 28 Global AI in Clinical Trials Market Outlook, By Contract Research Organizations (2021-2030) ($MN)
  • Table 29 Global AI in Clinical Trials Market Outlook, By Academic Institutions (2021-2030) ($MN)
  • Table 30 Global AI in Clinical Trials Market Outlook, By Other End Users (2021-2030) ($MN)

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