Global AI-based Clinical Trial Solutions for Patient Matching Market

Report ID : 1430 | Published : 2022-10-30 | Pages: | Format:

The market size of the global AI-based clinical trial solutions for patient matching market in the year 2021 is valued at 234.53 million and is predicted to reach 2150.40 million by the year 2030 at an 28.27% CAGR during the forecast period.

A network-wide clinical trial matching tool powered by artificial intelligence (AI) called VIPER. AI technology is intended to enable, prioritize, and expedite patient enrollment during the trial recruitment process. The use of AI-powered solutions in controlling and implementing medical testing is responsible for the market’s expansion. These solutions can help shorten the duration of the clinical trial cycle, which lowers costs and improves reliability while also improving the efficiency of trial production. The primary driver of AI-based clinical trial solutions for the patient matching market is that a massive percentage of pharmaceutical companies are forced to make significant investments in new drug development to increase the number of products in their product pipelines. Clinical and biomedical research using digitalization is creating prospects for AI-based clinical trial solutions for the patient-matching market. Leading pharma companies are incorporating cutting-edge technological solutions for improved patient management and clinical outcomes. Government entities in developed nations fund the development of AI-based clinical trial survey technologies while establishing a strong regulatory foundation. Additionally, governments in emerging economies are educating stakeholders about AI-based clinical trial solutions so that they may concentrate on finding novel treatments and expediting patient enrollment, which will increase patient experience and monitoring. However, risks associated with data privacy might constrain AI-based clinical trial solutions for the patient-matching market in the coming years.

Market Segmentation:

The Ai-based clinical trial solutions for the patient matching market are segmented based on therapeutic application and end users. Based on therapeutic applications, the AI-based clinical trial solutions for the patient matching market is segmented as oncology, cardiovascular diseases, neurological diseases or condition, metabolic diseases, infectious diseases, and others. By application, the AI-based clinical trial solutions for the patient matching market are segmented into pharmaceutical companies, academia, and others.

Based on product, the pharmaceutical company’s segment is accounted as a significant contributor in the AI-based clinical trial solutions for the patient matching market.

The pharmaceutical company’s segment is expected to hold a major share in the global AI-based clinical trial solutions for patient matching market in 2021 due to the increased emphasis on creating biomarkers and diagnostics that work better, employing AI-based innovations to find new drug targets and streamlining the application development. The expanding pharmaceutical sector is further fueling the market due to the prevalence of chronic diseases and the rising demand for new treatments. The market is also benefiting from a partnership between major pharmaceutical companies and AI providers to use AI technologies designed for the entire process of discovering new medicines.

The oncology segment witnessed growth at a rapid rate

The oncology segment is projected to grow rapidly in the global AI-based clinical trial solutions for the patient matching market. The number of AI-based clinical trial solutions for patient matching is rising due to the rising incidence rate of cancer worldwide, positively affecting the industry. Leading pharmaceutical corporations are also collaborating with AI development firms to deploy AI-based oncology technologies created for the creation of pharmaceuticals., especially in countries such as the US, Germany, the UK, China, and India.

The North America AI-based clinical trial solutions for patient matching in the region hold a significant revenue share.

The North America AI-based clinical trial solutions for the patient matching market are expected to register the highest market share in revenue soon. The development of a sizable patient population, affordable access to highly skilled labor, and reasonable hiring rates are the fundamental causes of this. The market’s growth is primarily driven by increased usage of AI-based technologies and rising awareness of these solutions. A greater number of startups have emerged due to the growing consumption, which is anticipated to create new prospects for the industry in this region.

In addition, Asia Pacific is projected to grow at a rapid rate in the global AI-based clinical trial solutions for the patient matching market. The growing demand for AI-based technology and the incorporation of government initiatives contribute to the region’s growth. Major market players are also boosting their R&D in AI-based technologies for clinical trials to enhance their market shares. Activities include joint ventures, agreements, affiliations, and other strategic alliances with rival market participants.

Competitive Landscape

The major key players in the AI-based clinical trial solutions for the patient matching market are “Unlearn.AI, Inc., Antidote Technologies, Inc., Deep6.ai, Mendel.ai, Aris Global, Deep Lens AI, AmerisourceBergen Corporation, Konaks, Microsoft Corporation, GNS Healthcare.

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global AI-Based Clinical Trial Solutions for Patient Matching Market Snapshot

Chapter 4. Global AI-Based Clinical Trial Solutions for Patient Matching Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Therapeutic Application Estimates & Trend Analysis

5.1. by Therapeutic Application & Market Share, 2019 & 2030

5.2. Market Size (Value (US$ Mn) & Volume (no. of units) & Forecasts and Trend Analyses, 2019 to 2030 for the following by Therapeutic Application:

5.2.1. Oncology

5.2.2. Cardiovascular Diseases

5.2.3. Neurological Diseases or Conditions

5.2.4. Metabolic Diseases

5.2.5. Infectious Diseases

5.2.6. Others

Chapter 6. Market Segmentation 2: by End-users Estimates & Trend Analysis

6.1. by End-users & Market Share, 2019 & 2030

6.2. Market Size (Value (US$ Mn) & Volume (no. of units) & Forecasts and Trend Analyses, 2019 to 2030 for the following by End-users:

6.2.1. Pharmaceutical Companies

6.2.2. Academia

6.2.3. Others

Chapter 7. AI-Based Clinical Trial Solutions for Patient Matching Market Segmentation 3: Regional Estimates & Trend Analysis

7.1. North America

7.1.1. North America AI-Based Clinical Trial Solutions for Patient Matching Market Revenue (US$ Million) Estimates and Forecasts by Therapeutic Application, 2019-2030

7.1.2. North America AI-Based Clinical Trial Solutions for Patient Matching Market Revenue (US$ Million) Estimates and Forecasts by End-users, 2019-2030

7.1.3. North America AI-Based Clinical Trial Solutions for Patient Matching Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2030

7.2. Europe

7.2.1. Europe AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by Therapeutic Application, 2019-2030

7.2.2. Europe AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by End-users, 2019-2030

7.2.3. Europe AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by country, 2019-2030

7.3. Asia Pacific

7.3.1. Asia Pacific AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by Therapeutic Application, 2019-2030

7.3.2. Asia Pacific AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by End-users, 2019-2030

7.3.3. Asia Pacific AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by country, 2019-2030

7.4. Latin America

7.4.1. Latin America AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by Therapeutic Application, 2019-2030

7.4.2. Latin America AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by End-users, 2019-2030

7.4.3. Latin America AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by country, 2019-2030

7.5. Middle East & Africa

7.5.1. Middle East & Africa AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by Therapeutic Application, 2019-2030

7.5.2. Middle East & Africa AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by End-users, 2019-2030

7.5.3. Middle East & Africa AI-Based Clinical Trial Solutions for Patient Matching Market revenue (US$ Million) by country, 2019-2030

Chapter 8. Competitive Landscape

8.1. Major Mergers and Acquisitions/Strategic Alliances

8.2. Company Profiles

8.2.1. Unlearn.AI, Inc.

8.2.2. Antidote Technologies, Inc.

8.2.3. Deep6.ai

8.2.4. Mendel.ai

8.2.5. Aris Global

8.2.6. Deep Lens AI

8.2.7. AmerisourceBergen Corporation

8.2.8. Konaks

8.2.9. Microsoft Corporation

8.2.10. GNS Healthcare

8.2.11. Other Prominent Players

By Therapeutic Application

  • Oncology
  • Cardiovascular Diseases
  • Neurological Diseases or Conditions
  • Metabolic Diseases
  • Infectious Diseases
  • Others

By End-use

  • Pharmaceutical Companies
  • Academia
  • Others

By Region-

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • Southeast Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of the Middle East and Africa

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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