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Global AI-based Clinical Trials Solution Provider Market to reach USD XX million by 2028.

Global AI-based Clinical Trials Solution Provider Market Size study, By Clinical Trial Phase (Phase-I, Phase-II, Phase-III), By Application (Oncology, Cardiovascular Diseases, Neurological Diseases or Conditions, Infectious Diseases, Others), By End-use (Pharmaceutical Companies, Academia, Others), and Regional Forecasts 2022-2028

Product Code: HLSHIT-61393212
Publish Date: 15-06-2022
Page: 200

Global AI-based Clinical Trials Solution Provider Market is valued at approximately USD XX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2028. The emergence of artificial intelligence (AI) in the research and development activities in clinical trials aids in improving operational competence, minimizing costs, and boosting drug discovery. AI technology integrated with big data helps in solving various key clinical trial challenges, which is leading the market growth. Factors such as the increase in the number of clinical studies, and growing penetration of the AI-based platforms for enhancing efficiency and productivity of trials at many stages, coupled with the development of the pharmaceutical and CROs sector are impelling the growth of the global market. For instance, as per a Statista report, in 2018, the total number of registered clinical studies worldwide was recorded at 293,259 and the figure is constantly rising and reach 409,300 studies by 2022. Accordingly, the rising clinical studies are positively influencing the growth of the AI-based Clinical Trials Solution Provider market across the globe. However, the lack of AI accuracy in clinical practices and the imposition of several stringent regulations on the approval of AI-based clinical trials hinders the growth of the market over the forecast period of 2022-2028. Also, rising R&D investments in various therapeutic areas and growing awareness and diversified applications of artificial intelligence (AI) in the field of clinical trials are anticipated to act as catalyzing factors for the market demand during the forecast period.

The key regions considered for the global AI-based Clinical Trials Solution Provider Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the availability of favorable government policies and the rising presence of a number of AI-based start-ups. Whereas, Asia-Pacific is anticipated to exhibit the highest CAGR over the forecast period 2022-2028. Factors such as the growing adoption of AI-based tools, rising patient pool, as well as, increasing prevalence of various diseases, would create lucrative growth prospects for the AI-based Clinical Trials Solution Provider Market across the Asia-Pacific region.

Major market players included in this report are:
Unlearn.AI, Inc.
Saama Technologies
Antidote Technologies, Inc.
Innoplexus
Mendel.ai
Median Technologies
Symphony AI
BioAge Labs, Inc.
AiCure, LLC
Halo Health Systems

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Clinical Trial Phase:
Phase-I
Phase-II
Phase-III
By Application:
Oncology
Cardiovascular Diseases
Neurological Diseases or Conditions
Infectious Diseases
Others
By End-use:
Pharmaceutical Companies
Academia
Others
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global AI-based Clinical Trials Solution Provider Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Million)
1.2.1. AI-based Clinical Trials Solution Provider Market, by Region, 2020-2028 (USD Million)
1.2.2. AI-based Clinical Trials Solution Provider Market, by Clinical Trial Phase, 2020-2028 (USD Million)
1.2.3. AI-based Clinical Trials Solution Provider Market, by Application, 2020-2028 (USD Million)
1.2.4. AI-based Clinical Trials Solution Provider Market, by End-use, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global AI-based Clinical Trials Solution Provider Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global AI-based Clinical Trials Solution Provider Market Dynamics
3.1. AI-based Clinical Trials Solution Provider Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Increase in the number of clinical studies
3.1.1.2. Growing penetration of the AI-based platforms for enhancing efficiency and productivity of trials at many stages
3.1.2. Market Challenges
3.1.2.1. Lack of AI accuracy in clinical practices
3.1.2.2. Imposition of several stringent regulations on the approval of AI-based clinical trials hinders
3.1.3. Market Opportunities
3.1.3.1. Rising R&D investments in various therapeutic areas
3.1.3.2. Growing awareness and diversified applications of artificial intelligence (AI) in the field of clinical trials
Chapter 4. Global AI-based Clinical Trials Solution Provider Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global AI-based Clinical Trials Solution Provider Market, by Clinical Trial Phase
6.1. Market Snapshot
6.2. Global AI-based Clinical Trials Solution Provider Market by Clinical Trial Phase, Performance – Potential Analysis
6.3. Global AI-based Clinical Trials Solution Provider Market Estimates & Forecasts by Clinical Trial Phase, 2018-2028 (USD Million)
6.4. AI-based Clinical Trials Solution Provider Market, Sub Segment Analysis
6.4.1. Phase-I
6.4.2. Phase-II
6.4.3. Phase-III
Chapter 7. Global AI-based Clinical Trials Solution Provider Market, by Application
7.1. Market Snapshot
7.2. Global AI-based Clinical Trials Solution Provider Market by Application, Performance – Potential Analysis
7.3. Global AI-based Clinical Trials Solution Provider Market Estimates & Forecasts by Application, 2018-2028 (USD Million)
7.4. AI-based Clinical Trials Solution Provider Market, Sub Segment Analysis
7.4.1. Oncology
7.4.2. Cardiovascular Diseases
7.4.3. Neurological Diseases or Conditions
7.4.4. Infectious Diseases
7.4.5. Others
Chapter 8. Global AI-based Clinical Trials Solution Provider Market, by End-use
8.1. Market Snapshot
8.2. Global AI-based Clinical Trials Solution Provider Market by End-use, Performance – Potential Analysis
8.3. Global AI-based Clinical Trials Solution Provider Market Estimates & Forecasts by End-use, 2018-2028 (USD Million)
8.4. AI-based Clinical Trials Solution Provider Market, Sub Segment Analysis
8.4.1. Pharmaceutical Companies
8.4.2. Academia
8.4.3. Others
Chapter 9. Global AI-based Clinical Trials Solution Provider Market, Regional Analysis
9.1. AI-based Clinical Trials Solution Provider Market, Regional Market Snapshot
9.2. North America AI-based Clinical Trials Solution Provider Market
9.2.1. U.S. AI-based Clinical Trials Solution Provider Market
9.2.1.1. Clinical Trial Phase breakdown estimates & forecasts, 2018-2028
9.2.1.2. Application breakdown estimates & forecasts, 2018-2028
9.2.1.3. End-use breakdown estimates & forecasts, 2018-2028
9.2.2. Canada AI-based Clinical Trials Solution Provider Market
9.3. Europe AI-based Clinical Trials Solution Provider Market Snapshot
9.3.1. U.K. AI-based Clinical Trials Solution Provider Market
9.3.2. Germany AI-based Clinical Trials Solution Provider Market
9.3.3. France AI-based Clinical Trials Solution Provider Market
9.3.4. Spain AI-based Clinical Trials Solution Provider Market
9.3.5. Italy AI-based Clinical Trials Solution Provider Market
9.3.6. Rest of Europe AI-based Clinical Trials Solution Provider Market
9.4. Asia-Pacific AI-based Clinical Trials Solution Provider Market Snapshot
9.4.1. China AI-based Clinical Trials Solution Provider Market
9.4.2. India AI-based Clinical Trials Solution Provider Market
9.4.3. Japan AI-based Clinical Trials Solution Provider Market
9.4.4. Australia AI-based Clinical Trials Solution Provider Market
9.4.5. South Korea AI-based Clinical Trials Solution Provider Market
9.4.6. Rest of Asia Pacific AI-based Clinical Trials Solution Provider Market
9.5. Latin America AI-based Clinical Trials Solution Provider Market Snapshot
9.5.1. Brazil AI-based Clinical Trials Solution Provider Market
9.5.2. Mexico AI-based Clinical Trials Solution Provider Market
9.6. Rest of The World AI-based Clinical Trials Solution Provider Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Unlearn.AI, Inc.
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. Saama Technologies
10.2.3. Antidote Technologies, Inc.
10.2.4. Innoplexus
10.2.5. Mendel.ai
10.2.6. Median Technologies
10.2.7. Symphony AI
10.2.8. BioAge Labs, Inc.
10.2.9. AiCure, LLC
10.2.10. Halo Health Systems
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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