The global clinical trials matching software market was surpassed at USD 132.86 million in 2021 and is expected to hit around USD 397.3 million by 2030, growing at a CAGR of 12.94% from 2022 to 2030
Report Highlights
The significant increase in the number of ongoing clinical trials is likely to drive the market. In addition, the growing adoption of the clinical trial matching software catering to the clinical trials, along with the increased demand for virtual trials and automation in the healthcare sector are some of the key factors contributing to the market growth. The matching software help in effective and fast patient matching with patient-centric approaches.
In clinical trials, patient recruitment or matching can be time-consuming, and finding the right match can be a hurdle. Screening or locating prospective respondents who are qualified, considering all elements of the trials, verifying awareness, and getting informed consent to participate are the factors taken into consideration while recruiting patients. Enlisting the individuals in accordance with the qualifying requirements is crucial, hence the trial matching technology has been proved to be useful, especially in the COVID-19 scenario.
The software helps not only to find the right match but also saves the R&D-related costs, enabling smoother operations without human intervention. The software providers are introducing new innovative techniques to strengthen their market position. For instance, in February 2022, the CTMA expanded CT-SCOUT technology offering in rheumatology.
Scope of The Report
Report Coverage | Details |
Market Size in 2021 | USD 132.86 million |
Revenue Forecast by 2030 | USD 397.3 million |
Growth rate from 2022 to 2030 | CAGR of 12.94% |
Base Year | 2021 |
Forecast Period | 2022 to 2030 |
Segmentation | Deployment mode, end use, region |
Companies Covered | IBM Clinical development; Antidote Technologies, Inc.; Clinical Trials Mobile Application; SSS International Clinical Research; Advarra; Aris Global |
Deployment Mode Insights
In 2021, the web and cloud-based segment dominated the market with a revenue share of over 90.06% owing to the cloud computing model, which is easier to maintain with no upkeep charges. As in-house server infrastructure is not required, development costs are reduced. The integration time is significantly reduced and it may be accessed from any location. Data sharing is convenient and allows collaboration on different projects.
The on-premise model requires in-house infrastructure, software licensing, IT support, and lengthier integration times. Therefore, this model is costlier and less preferred. On the other hand, organizations with highly confidential data, including government and financial institutions, require an on-premises environment's security and privacy. Based on the deployment model, the market for clinical trials matching software is segmented into web and cloud-based, and on-premise.
End-use Insights
In 2021, the pharmaceutical and biotechnology companies segment dominated the market with a revenue share of over 40.11% due to the large number of clinical trials required for product launches. Based on end-use, the market is segmented into pharmaceutical and biotechnology companies, CROs, and medical device firms.
The CROs segment is anticipated to expand at the fastest CAGR of 13.76% over the forecast period. CROs offer drug development through commercialization, pharmacovigilance, and post-approval services to manufacturing organizations with low R&D budgets. A sponsor (the entity wishing to research the safety and efficacy of the products) contracts a CRO, a project-by-project basis for clinical trials. The organizations that are unable to afford to conduct extensive clinical trials prefer to outsource these services. Hence, the demand for CROs is growing rapidly.
Regional Insights
In 2021, North America held the largest revenue share of over 50.2% owing to the growth in the adoption of the clinical trials matching software by the pharmaceutical and biotechnology companies in the U.S. In addition, the supportive government initiatives toward IT and AI-based solutions and the higher adoption of CTMS and patient matching software are contributing to the market growth in the region.
Asia Pacific is likely to register the fastest CAGR over the forecast period owing to the availability of a large patient pool in the region, enabling easier patient recruitment procedures. A large number of organizations are aiming to set up their R&D activities in the Asia Pacific, contributing to the market growth in the region. This growth can be attributed to the increase in the number of IT healthcare projects, booming economy, and overall improving healthcare infrastructure, especially in developing Asian countries, such as China and India.
Key Players
Market Segmentation
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 Clinical Trials Matching Software Market
5.1. COVID-19 Landscape: Clinical Trials Matching Software 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 Clinical Trials Matching Software Market, By Deployment Mode
8.1. Clinical Trials Matching Software Market, by Deployment Mode, 2022-2030
8.1.1. Web & Cloud Based
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. On-premise
8.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Clinical Trials Matching Software Market, By End-use
9.1. Clinical Trials Matching Software Market, by End-use, 2022-2030
9.1.1. Pharmaceutical & Biotechnology Companies
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. CROs
9.1.2.1. Market Revenue and Forecast (2017-2030)
9.1.3. Medical Device Firms
9.1.3.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Clinical Trials Matching Software Market, Regional Estimates and Trend Forecast
10.1. North America
10.1.1. Market Revenue and Forecast, by Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (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 Deployment Mode (2017-2030)
10.5.4.2. Market Revenue and Forecast, by End-use (2017-2030)
Chapter 11. Company Profiles
11.1. IBM Clinical development
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. Clinical Trials Mobile Application
11.3.1. Company Overview
11.3.2. Product Offerings
11.3.3. Financial Performance
11.3.4. Recent Initiatives
11.4. SSS International Clinical Research
11.4.1. Company Overview
11.4.2. Product Offerings
11.4.3. Financial Performance
11.4.4. LTE Scientific
11.5. Advarra
11.5.1. Company Overview
11.5.2. Product Offerings
11.5.3. Financial Performance
11.5.4. Recent Initiatives
11.6. Aris Global
11.6.1. Company Overview
11.6.2. Product Offerings
11.6.3. Financial Performance
11.6.4. 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