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市場調查報告書
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1454042

到 2030 年臨床試驗中的人工智慧市場預測：按產品類型、流程、應用、最終用戶和地區進行的全球分析

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個工作天內

價格

根據 Stratistics MRC 的數據，2023 年全球 AIAI 臨床試驗市場規模將達到 19 億美元，預計 2030 年將達到 105 億美元，預測期內年複合成長率為 27.6%。

臨床試驗中的人工智慧是指利用人工智慧（AI）技術來增強臨床試驗過程的各個方面，從患者招募和資料分析到試驗設計和藥物開發。透過利用機器學習演算法和資料分析，人工智慧可以簡化流程、識別合適的候選人、預測結果並最佳化測試通訊協定。這種人工智慧整合旨在提高效率、降低成本，並最終加速醫療保健行業新治療方法和治療方法的開發。

高盛研究預計，2023年全球製藥業將花費約7,000億美元用於研發和收購。

改善病患招募和保留的潛力

人工智慧技術為病人參與來提高保留率。透過先進的演算法，人工智慧可以簡化患者選擇流程，透過識別高風險個體來降低退出率，並根據即時資料分析最佳化試驗通訊協定。這些功能預計將使臨床試驗更加高效和成功，最終推進醫學研究並改善患者的治療結果。這些都是市場成長的促進因素。

資料隱私和安全問題

隨著大量敏感患者資訊被收集和分析，確保採取強力的安全措施防止資料外洩和未授權存取至關重要。個人健康資料的濫用和潛在濫用會引發道德和法律問題，並需要嚴格的法規結構。人工智慧技術的整合帶來了資料匿名和同意管理的複雜性，需要在整個測試過程中仔細考慮隱私和安全通訊協定。因此，對資料隱私和安全的擔憂是限制市場成長的因素。

擴大基於人工智慧的平台的使用

人工智慧系統利用機器學習和資料分析來改善患者招募、試驗設計和資料分析。製藥公司和研究機構正在利用人工智慧驅動的平台，透過管理大量資訊和預測患者反應的能力來加速藥物開發並改善試驗結果。市場正在擴大，因為人工智慧正在獲得認可，並且具有突破性的能力，將改變臨床研究和開發的格局。

實施成本高

成本由多種因素產生，包括對專業基礎設施、先進人工智慧演算法、資料管理系統和監管合規措施的需求。儘管有潛在的好處，例如提高臨床試驗過程的效率和準確性，但公司必須仔細考慮在臨床研究中採用人工智慧技術的財務影響。因此，由於實施成本高昂，人工智慧與臨床試驗的整合已成為重大挑戰。

COVID-19 的影響：

COVID-19 大流行顯著加速了人工智慧在臨床試驗中的採用。傳統研究被顛覆，人工智慧為遠端監控、資料分析和患者招募提供了解決方案。這提高了效率、降低了成本並縮短了測試完成時間。人工智慧促進了虛擬測試、遠端患者監護和預測分析，使研究人員能夠適應新常態。此外，人工智慧處理大量資料的能力對於識別模式和開發治療方法變得至關重要。因此，COVID-19 成為臨床試驗市場人工智慧成長的催化劑。

預計深度學習領域在預測期內將是最大的

預計深度學習領域在預測期內將是最大的。深度學習演算法使研究人員和開發人員能夠從大量醫療資料中提取有意義的見解，從而實現更高效的試驗設計、更快的藥物開發並改善患者的治療結果。隨著製藥公司和研究機構擴大採用這些技術來提高其測試的有效性和成本效益，該市場的深度學習市場正在經歷顯著成長。

預計感染疾病領域在預測期內的年複合成長率最高。

由於需要高效、準確的解決方案，預計感染疾病產業在預測期內將出現最高的年複合成長率。人工智慧技術提供先進的分析、預測建模和資料解釋，以增強決策流程。該細分市場的特點是創新的人工智慧演算法、強大的資料整合能力以及對監管合規性的關注，以確保治療的安全性和有效性。

比最大的地區

由於技術進步以及醫療保健領域對高效和資料主導解決方案的需求不斷增加，預計北美將在預測期內佔據最大的市場佔有率。人工智慧技術正在徹底改變臨床試驗的許多方面，包括患者招募、資料分析和個人化醫療。主要製藥公司的存在、強大的醫療基礎設施和支持性的法規環境等關鍵因素進一步促進了該地區市場的擴張。

年複合成長率最高的地區：

由於人口成長、人口老化和慢性病負擔增加等因素，預計亞太地區在預測期內將維持最高年複合成長率。這導致對醫療基礎設施和技術（包括人工智慧）的投資增加，以提高臨床試驗的效率和結果。該地區出現了眾多專注於醫療保健和生命科學的人工智慧新興企業。人工智慧、機器學習和資料分析技術正在該地區迅速發展。

提供免費客製化：

訂閱此報告的客戶可以存取以下免費自訂選項之一：

  • 公司簡介
    • 其他市場參與者的綜合分析（最多 3 家公司）
    • 主要企業SWOT分析（最多3家企業）
  • 區域分割
    • 根據客戶興趣對主要國家的市場估計、預測和年複合成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 調查來源
    • 主要調查來源
    • 二次調查來源
    • 先決條件

第3章市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • 新型冠狀病毒感染疾病（COVID-19）的影響

第4章波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章臨床試驗中的全球人工智慧市場：透過提供

  • 軟體
    • 臨床試驗管理系統（CTMS）
    • 電子資料擷取(EDC) 系統
    • 統計分析軟體
  • 服務
    • 資料管理與分析
    • 監理諮詢

第6章臨床試驗中的全球人工智慧市場：按技術分類

  • 老師有空
  • 深度學習
  • 機器學習
  • 自然語言處理
  • 電腦視覺
  • 預測分析
  • 其他技術

第7章臨床試驗中的全球人工智慧市場：按應用分類

  • 神經系統
  • 心血管
  • 代謝
  • 腫瘤學
  • 感染疾病
  • 免疫疾病
  • 其他用途

第8章臨床試驗中的全球人工智慧市場：按最終用戶分類

  • 製藥和生物技術公司
  • 受託研究機構
  • 學術機構
  • 其他最終用戶

第9章全球臨床試驗中的人工智慧市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第10章 主要進展

  • 合約、夥伴關係、協作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第11章 公司簡介

  • 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.