Ai In Clinical Trials Market
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
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
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o 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
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o 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
1 Global AI in Clinical Trials Market Outlook, By Region (2021-2030) ($MN)
2 Global AI in Clinical Trials Market Outlook, By Offering (2021-2030) ($MN)
3 Global AI in Clinical Trials Market Outlook, By Software (2021-2030) ($MN)
4 Global AI in Clinical Trials Market Outlook, By Clinical Trial Management Systems (CTMS) (2021-2030) ($MN)
5 Global AI in Clinical Trials Market Outlook, By Electronic Data Capture (EDC) Systems (2021-2030) ($MN)
6 Global AI in Clinical Trials Market Outlook, By Statistical Analysis Software (2021-2030) ($MN)
7 Global AI in Clinical Trials Market Outlook, By Services (2021-2030) ($MN)
8 Global AI in Clinical Trials Market Outlook, By Data Management and Analysis (2021-2030) ($MN)
9 Global AI in Clinical Trials Market Outlook, By Regulatory Consulting (2021-2030) ($MN)
10 Global AI in Clinical Trials Market Outlook, By Technology (2021-2030) ($MN)
11 Global AI in Clinical Trials Market Outlook, By Supervised (2021-2030) ($MN)
12 Global AI in Clinical Trials Market Outlook, By Deep learning (2021-2030) ($MN)
13 Global AI in Clinical Trials Market Outlook, By Machine learning (2021-2030) ($MN)
14 Global AI in Clinical Trials Market Outlook, By Natural Language Processing (2021-2030) ($MN)
15 Global AI in Clinical Trials Market Outlook, By Computer Vision (2021-2030) ($MN)
16 Global AI in Clinical Trials Market Outlook, By Predictive Analytics (2021-2030) ($MN)
17 Global AI in Clinical Trials Market Outlook, By Other Technologies (2021-2030) ($MN)
18 Global AI in Clinical Trials Market Outlook, By Application (2021-2030) ($MN)
19 Global AI in Clinical Trials Market Outlook, By Neurological (2021-2030) ($MN)
20 Global AI in Clinical Trials Market Outlook, By Cardiovascular (2021-2030) ($MN)
21 Global AI in Clinical Trials Market Outlook, By Metabolic (2021-2030) ($MN)
22 Global AI in Clinical Trials Market Outlook, By Oncology (2021-2030) ($MN)
23 Global AI in Clinical Trials Market Outlook, By Infectious Diseases (2021-2030) ($MN)
24 Global AI in Clinical Trials Market Outlook, By Immunology Diseases (2021-2030) ($MN)
25 Global AI in Clinical Trials Market Outlook, By Other Applications (2021-2030) ($MN)
26 Global AI in Clinical Trials Market Outlook, By End User (2021-2030) ($MN)
27 Global AI in Clinical Trials Market Outlook, By Pharmaceutical & Biotechnology Companies (2021-2030) ($MN)
28 Global AI in Clinical Trials Market Outlook, By Contract Research Organizations (2021-2030) ($MN)
29 Global AI in Clinical Trials Market Outlook, By Academic Institutions (2021-2030) ($MN)
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.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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