查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1371876

到 2030 年臨床試驗中的人工智慧市場預測：按部署模式、技術、用途、最終用戶和地區進行的全球分析

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個工作天內

價格

根據Stratistics MRC的數據，2023年全球人工智慧（AI）臨床試驗市場規模為18.8億美元，預計到2030年將達到92.8億美元，預測期內年複合成長率為25.6，預計將成長%。

臨床試驗中的人工智慧（AI）是指在臨床試驗和藥物研發過程中使用人工智慧工具和解決方案，包括設計試驗計劃、選擇試驗地點以及規劃患者招募和監測系統。在臨床試驗中使用人工智慧技術可以透過更快地提供結果並增加臨床試驗中使用的人群的多樣性來幫助克服傳統臨床試驗程序的缺點。

根據世界衛生組織（WHO）的數據，2021年，美國在臨床試驗領域處於領先地位，過去20年度註冊的臨床試驗約為157,618項。

對抗罕見疾病和遺傳疾病的藥物需求不斷成長

基因治療和癌症藥物開發部門的研究和開發提供了應用人工智慧工具和技術為這些疾病創造新的、強大的治療方法的機會。由於一些罕見疾病的發展和研究，最近增加了使用基於人工智慧的臨床試驗來加快設計試驗的過程，以確定特定疾病的原因並檢查潛在治療方法的有效性。此外，已開發國家和新興國家的政府都在推動臨床試驗並增加患者的參與，從而擴大了市場。

嚴格法規

醫療保健領域人工智慧的法規環境仍在不斷發展。確保人工智慧系統符合法規要求，例如食品藥物管理局(FDA) 制定的要求，可能會成為採用的障礙。開發和實施人工智慧解決方案成本高且資源密集。此外，規模較小的研究機構和醫療保健提供者可能面臨資金和專業知識方面的挑戰。

加大人工智慧投資

過去年度，全球許多投資人曾向為臨床試驗提供人工智慧軟體和服務的企業投資了近25億美元，證明了市場興趣日益濃厚。在創投輪之後，種子輪融資籌集了大部分資金。此外，百時美施貴寶、默克、諾華、輝瑞、賽諾菲等大型製藥公司也在投資用於臨床試驗的人工智慧軟體和服務供應商，開闢了廣泛的市場機會。

臨床試驗中無法獲得健康資料

臨床試驗中的人工智慧技術需要分析大量現有資料，以獲得有助於推進臨床試驗的重要見解。目前可用的資料可能不足以開發針對新發現或未知疾病（例如冠狀病毒）的治療方法。如果歷史資料不可靠，基於人工智慧的解決方案的有效性可能會受到限制。此外，任何參考資料資料的偏差都會使人工智慧支援的臨床試驗的結論和結果產生偏差。這些條件可能會限制市場擴張。

COVID-19 的影響：

COVID-19 的爆發促使人們更多地使用基於人工智慧的技術。由於多種要素，包括擴大採用技術先進的藥物研發發現和開發解決方案以及對招募的患者資料進行分析，基於人工智慧的藥物開發和臨床實驗解決方案正在廣泛使用。分散式藥物臨床實驗也有所增加，因為許多臨床實驗試驗因 COVID-19 而被擱置，並且許多大公司在此期間專注於匯總可存取的患者資料。

預計腫瘤學將成為預測期內最大的領域

腫瘤學領域將在預測期內繼續成長，因為癌症治療的需求不斷成長以及該領域進行的大量藥物臨床試驗正在影響人工智慧技術在該應用領域的採用。預計將佔到市場佔有率最大。此外，許多參與者正在創建和利用以腫瘤學為中心的人工智慧工具進行臨床試驗，這正在推動領域的擴張。

預計製藥領域在預測期內年複合成長率最高

製藥公司業務預計將迅速擴張。擴大採用人工智慧技術可以提高臨床試驗的生產力和有效性。此外，跨產業的夥伴關係和協作也正在發生，以在整個研發和開發過程中利用人工智慧作為工具。這些因素正在推動該細分市場的成長。

比最大的地區

北美目前在基於人工智慧的臨床試驗解決方案提供商市場中佔據主導地位，預計這種主導地位在預測期內將持續下去。這是由於該地區存在多家基於人工智慧的新興企業。採用基於人工智慧的技術來改善藥物測試結果以及對這些技術的認知不斷提高正在推動該地區的市場成長。該地區對基於人工智慧的臨床試驗解決方案的需求也受到政府配合措施和領先公司不斷成長的戰略舉措的推動。

複合年複合成長率最高的地區：

在基於人工智慧的工具擴大採用以及政府在各個醫療保健領域實施人工智慧的配合措施的推動下，亞太地區預計將見證基於人工智慧的臨床試驗解決方案提供者的市場成長率。成為最高的。由於其廣泛的患者基礎和較低的試驗成本，亞洲的臨床試驗招募人數正在增加。此外，Novotech 執行長表示，臨床階段生物技術公司現在正在尋求亞太地區加快患者入組速度，特別是在感染疾病。這些因素預計將增加基於人工智慧的臨床試驗分析和解釋解決方案的採用，從而導致市場擴張。

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
  • 利害關係人
  • 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
  • 替代的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章 全球人工智慧（AI）臨床試驗市場：依臨床實驗階段分類

  • 第一階段
  • 第二階段
  • 第三階段
  • 第四階段

第6章 全球臨床試驗市場中的人工智慧（AI）：按技術分類

  • 機器學習
  • 深度學習
  • 影像分析
  • 自然語言處理（NLP）
  • 預測分析
  • 監督學習
  • 其他技術

第7章 全球臨床試驗市場中的人工智慧（AI）：按應用分類

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

第8章 臨床試驗市場中的全球人工智慧（AI）：按最終用戶分類

  • 製藥公司
  • 合約研究組織（CRO）
  • 學術界
  • 其他最終用戶

第9章 全球臨床試驗市場中的人工智慧（AI）：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 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

  • 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.