Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Market Research Report
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Market
5.1. COVID-19 Landscape: Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Market, By Therapeutic Application
8.1. Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Market, by Therapeutic Application, 2022-2030
8.1.1. Oncology
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. Cardiovascular Diseases
8.1.2.1. Market Revenue and Forecast (2017-2030)
8.1.3. Neurological Diseases or Conditions
8.1.3.1. Market Revenue and Forecast (2017-2030)
8.1.4. Metabolic Diseases
8.1.4.1. Market Revenue and Forecast (2017-2030)
8.1.5. Infectious Diseases
8.1.5.1. Market Revenue and Forecast (2017-2030)
8.1.6. Others
8.1.6.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Market, By End-Use
9.1. Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Market, by End-Use, 2022-2030
9.1.1. Pharmaceutical Companies
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Academia
9.1.2.1. Market Revenue and Forecast (2017-2030)
9.1.3. Others
9.1.3.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Artificial Intelligence-based Clinical Trial Solutions for Patient Matching Market, Regional Estimates and Trend Forecast
10.1. North America
10.1.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.1.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.1.3. U.S.
10.1.3.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.1.3.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.1.4. Rest of North America
10.1.4.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.1.4.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.2. Europe
10.2.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.2.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.2.3. UK
10.2.3.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.2.3.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.2.4. Germany
10.2.4.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.2.4.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.2.5. France
10.2.5.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.2.5.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.2.6. Rest of Europe
10.2.6.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.2.6.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.3. APAC
10.3.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.3.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.3.3. India
10.3.3.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.3.3.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.3.4. China
10.3.4.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.3.4.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.3.5. Japan
10.3.5.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.3.5.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.3.6. Rest of APAC
10.3.6.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.3.6.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.4. MEA
10.4.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.4.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.4.3. GCC
10.4.3.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.4.3.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.4.4. North Africa
10.4.4.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.4.4.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.4.5. South Africa
10.4.5.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.4.5.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.4.6. Rest of MEA
10.4.6.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.4.6.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.5. Latin America
10.5.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.5.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.5.3. Brazil
10.5.3.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.5.3.2. Market Revenue and Forecast, by End-Use (2017-2030)
10.5.4. Rest of LATAM
10.5.4.1. Market Revenue and Forecast, by Therapeutic Application (2017-2030)
10.5.4.2. Market Revenue and Forecast, by End-Use (2017-2030)
Chapter 11. Company Profiles
11.1. Unlearn.AI, Inc.
11.1.1. Company Overview
11.1.2. Product Offerings
11.1.3. Financial Performance
11.1.4. Recent Initiatives
11.2. Antidote Technologies, Inc.
11.2.1. Company Overview
11.2.2. Product Offerings
11.2.3. Financial Performance
11.2.4. Recent Initiatives
11.3. Deep6.ai
11.3.1. Company Overview
11.3.2. Product Offerings
11.3.3. Financial Performance
11.3.4. Recent Initiatives
11.4. Mendel.ai
11.4.1. Company Overview
11.4.2. Product Offerings
11.4.3. Financial Performance
11.4.4. LTE Scientific
11.5. Aris Global
11.5.1. Company Overview
11.5.2. Product Offerings
11.5.3. Financial Performance
11.5.4. Recent Initiatives
11.6. Deep Lens AI
11.6.1. Company Overview
11.6.2. Product Offerings
11.6.3. Financial Performance
11.6.4. Recent Initiatives
11.7. AmeriSourceBergen Corporation
11.7.1. Company Overview
11.7.2. Product Offerings
11.7.3. Financial Performance
11.7.4. Recent Initiatives
11.8. Koneksa
11.8.1. Company Overview
11.8.2. Product Offerings
11.8.3. Financial Performance
11.8.4. Recent Initiatives
11.9. Microsoft Corporation
11.9.1. Company Overview
11.9.2. Product Offerings
11.9.3. Financial Performance
11.9.4. Recent Initiatives
11.10. GNS Healthcare
11.10.1. Company Overview
11.10.2. Product Offerings
11.10.3. Financial Performance
11.10.4. Recent Initiatives
Chapter 12. Research Methodology
12.1. Primary Research
12.2. Secondary Research
12.3. Assumptions
Chapter 13. Appendix
13.1. About Us
13.2. Glossary of Terms
Cross-segment Market Size and Analysis for
Mentioned Segments
Additional Company Profiles (Upto 5 With No Cost)
Additional Countries (Apart From Mentioned Countries)
Country/Region-specific Report
Go To Market Strategy
Region Specific Market DynamicsRegion Level Market Share Import Export AnalysisProduction AnalysisOthers