The global AI-based clinical trial solutions for patient matching market size was exhibited at USD 294.05 million in 2022 and is projected to hit around USD 3,159.46 million by 2032, growing at a CAGR of 26.8% during the forecast period 2023 to 2032.
Key Pointers:
AI-based Clinical Trial Solutions For Patient Matching Market Report Scope
Report Coverage |
Details |
Market Size in 2023 |
USD 3,159.46 million |
Market Size by 2032 |
USD 3,159.46 million |
Growth Rate from 2023 to 2032 |
CAGR of xx% |
Base year |
2022 |
Forecast period |
2023 to 2032 |
Segments covered |
Therapeutic Application, End-use |
Regional scope |
North America; Europe; Asia Pacific; Central and South America; the Middle East and Africa |
Key companies profiled |
Unlearn.AI, Inc.; Antidote Technologies; Inc.; Deep6.ai; Mendel.ai; Aris Global; Deep Lens; AmerisourceBergen Corporation; Koneksa; Microsoft Corporation; GNS Healthcare |
The market growth is largely attributed to the inclusion of AI-powered solutions in conducting and managing clinical trials that can be beneficial for reducing clinical trial cycle time which further reduces the cost and also increases accuracy along with the productivity of the trial development. Increasing initiatives by the government, to promote the adoption of artificial intelligence (AI) technologies in the healthcare sector along with rising awareness about AI-based technology further fuels the market growth.
Adoption of the digitization in clinical and biomedical research is opening opportunities for AI-based clinical trials solution for the patient matching market. Key pharma companies are including advanced technological solutions for enhanced patient management and clinical trial results. AI-based clinical trial solutions increase patient recruitment by decreasing their population heterogeneity by harmonizing a large volumes of health information data from a wide array of sources and platforms such as medical imaging, electronic medical records (EMRs), and omics data.
These platforms allow selecting the groups of most appropriate patient population who have the highest chances of responding to the trial and higher likelihood of giving a quantifiable & measurable clinical endpoint. AI-based solution and systems can be utilized in examining patient health information records & clinical trial eligibility criteria and match them with recruiting clinical trial studies. AI-based solutions include natural language processing (NLP) algorithms which enhance the rate of matching between clinical trials and patient enrollment.
COVID-19 has transformed the perception of clinical trials. It has increased the penetration rate and utilization of these AI-based platforms for decreasing cost& time. Therefore, these factors are rising the adoption rate of artificial intelligence in pharmaceutical companies. For instance, major pharmaceutical players like Sanofi, Novartis, Johnson & Johnson, Pfizer, and Bayer are focusing on strategic alliances for the inclusion of AI-based solutions in medicine discovery & development and clinical trials process.
Government organizations of developed nations like the U.S. and Europe are providing funds and are simultaneously laying out a stringent regulatory framework to drive the adoption of AI-based solutions designed for clinical trial studies. Moreover, governments of the developing nations are also spreading awareness about AI-based clinical trial solutions amongst stakeholders to focus on discovering new medicines and accelerating patient recruitment as this will improve patient engagement & monitoring.
The increasing number of startups providing solutions for the AI-based recruiting patients, intended for the life science organizations in favor of their clinical studies are positively impacting the growth of the market. A large number of medicine manufacturers have to invest a substantial amount in the development of medicines to expand their product pipelines as many big vendors go off patent, which is one of the key factors for the growth of the clinical trials market.
Furthermore, growing initiatives by the public and private organization to support the adoption of AI-powered technological solutions in clinical trial studies is propelling the market growth. Pharma and biotech organizations are rapidly implementing AI-based platforms and solutions for supporting their clinical research studies. Corporations are adopting these solutions for enhancing recruitment, identification, engagement, and real-time monitoring of patients.
In developed countries, expenditure of healthcare IT holds a large share of healthcare expenses. Nations are incorporating AI-based tools to reduce costs and improve efficiency. For instance, NIH, in September 2022, launched the Bridge2AI program that will include members from diverse communities that will focus on generating different tools, resources, and data for building an AI approach.
Therapeutic Application Insights
In 2022, based on therapeutic applications, oncology accounted for the highest revenue share of 24.9%. The growing incidence rate of cancer throughout the world is leading to an increase in the number of clinical trials and is thus, impacting the market positively. Moreover, leading pharma companies are teaming up with AI developing companies to adopt AI-based oncology tools designed for the development process of medicines. For instance, in January 2022, Deep Lens and Hematology-Oncology Associates of Central New York came into a partnership that will focus on the clinical trial program expansion of the medical trial program. The VIPER by Deep Lens will be utilized to classify the eligible patients for clinical trials by pre-screening all patients.
The development of new technologies further fuels segment growth. For instance, in June 2022, Survivor Net launched an AI-based clinical trial finder that connects patients who are in need with groundbreaking cancer research.
Besides, the cardiovascular disease (CVD) segment is expected to reveal the highest CAGR during the forecast period owing to the rising prevalence of CVD throughout the world. As per the data of NIH’s, “New global data analysis highlights”, February 2021, the increasing percentage of the global population and geriatric population has led to substantial growth of CVD cases. This has resulted in major companies focusing on the development of new clinical solutions for cardiovascular diseases.
AI is highly being adopted for R&D purposes and improving clinical trial solutions for the analysis of CVD with a better approach. Thus, driving the segment’s growth. In June 2022, Bristol Myers Squibb signed a deal of USD 80.0 million with AI developer Owkin to design and optimize their CVD medicine trials. The partnership will emphasize adopting ML technologies to optimize their clinical trial process.
End-Use Insights
In 2022, based on end-use, pharmaceutical companies accounted for the highest revenue share of 67.9% owing to the growing focus on better development of the bio-markers and diagnostics using AI-based technologies to identify the new medicine target and simplify the process of development. For instance, Linguamatics offered by IQVIA is NLP-based software that provides text mining solutions for pharma companies.
The growing pharmaceutical industry due to the increasing penetration of chronic diseases and the growing demand for personalized medicine is further fueling the market growth. In addition, a collaboration between pharmaceutical giants and AI vendors for implementing AI technology intended for the overall medicine discovery process is further impacting the market positively.
However, the others segment is projected to have the fastest CAGR in the forecast period. The growth can be attributed to the rising adoption of AI-based solutions by government agencies and CROs as these solutions reduce the cost of clinical trials by enhancing the quality of data, increasing compliance & retention of patients, and identifying the effectiveness of the treatment more efficiently. Furthermore, growing investment by the government and non-government agencies for the development of drugs and technology-driven clinical trials is further driving market growth.
Regional Insights
North America dominated the global AI-based clinical trial solutions for patient matching market and accounted for a revenue share of 44.9% in 2022. The growth of the market can be largely attributed to the presence of key players within the region and a growing number of AI-based startups. The region also has a large number of registered clinical trials which impacts the market positively.
As per the data of the World Health Organization (WHO), from 1999-2021 U.S. conducted the highest number of clinical trials, i.e. about 157,618 trials. The growing interest in AI-based technologies and rising government initiatives for the adoption of AI-based technologies further fuel the region’s growth.
However, in the Asia Pacific, the market is expected to show the fastest CAGR during the forecast period owing to increasing penetration of AI-based clinical technologies and supportive government initiatives for adopting AI. A growing number of clinical trials within the region also impacts the market positively. As per the 2019’s data of NIH, Asia Pacific is becoming the hub for conducting cost-effective clinical trials. During the past 10 years, there has been a 7-fold increase in the registration of clinical trials. This is mainly due to the availability of highly skilled talents at lower cost, the presence of a large patient population, and the availability of competitive recruitment rates.
Some of the prominent players in the AI-based Clinical Trial Solutions For Patient Matching Market include:
Segments Covered in the Report
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2032. For this study, Nova one advisor, Inc. has segmented the global AI-based Clinical Trial Solutions For Patient Matching market.
By Therapeutic Application
By End-use
By Region
Chapter 1 Research Methodology & Scope
1.1 Market Segmentation and Scope
1.2 Market Definition
1.3 Research Methodology
1.3.1 Information Procurement
1.3.1.1 Purchased database
1.3.1.2 nova one advisor’s internal database
1.3.2 Primary Research
1.4 Research Scope and Assumptions
1.5 List of Data Sources
Chapter 2 Executive Summary
2.1 Market Outlook
2.2 Segment Outlook
Chapter 3 Global AI-based Clinical Trial Solutions for Patient Matching Market Variables, Trends, & Scope
3.1 Penetration and Growth Prospect Mapping
3.2 Market Dynamics
3.2.1 Market Driver Analysis
3.2.2 Market Restraint Analysis
3.3 Global AI-based Clinical Trial Solutions for Patient Matching Market Analysis Tools
3.3.1 Industry Analysis - Porter’s
3.3.1.1 Bargaining power of the suppliers
3.3.1.2 Bargaining power of the buyers
3.3.1.3 Threats of substitution
3.3.1.4 Threats from new entrants
3.3.1.5 Competitive rivalry
3.4. PESTEL Analysis
3.4.1 Political landscape
3.4.2 Economic and Social landscape
3.4.3 Technology landscape
3.4.4 Legal landscape
3.4.5 Technology landscape
3.5. Major Deals & Strategic Alliances Analysis
3.6 COVID-19 Impact on the market
Chapter 4 AI-based Clinical Trial Solutions for Patient Matching Market: Therapeutic Application Estimates & Trend Analysis
4.1 Definitions & Scope
4.2 Global AI-based Clinical Trial Solutions for Patient Matching Market: Therapeutic Application Market Share Analysis, 2023 and 2032
4.3 Oncology
4.3.1 Oncology analysis Market Estimates and Forecasts, 2020 - 2032
4.4 Cardiovascular Diseases
4.4.1 Cardiovascular Diseases Analysis Market Estimates and Forecasts, 2020 - 2032
4.5 Neurological Diseases or Conditions
4.5.1 Neurological Diseases or Conditions Analysis Market Estimates and Forecasts, 2020 - 2032
4.6 Metabolic Diseases
4.6.1 Metabolic Diseases Analysis Market Estimates and Forecasts, 2020 - 2032
4.7 Infectious Diseases
4.7.1 Infectious Diseases Analysis Market Estimates and Forecasts, 2020 - 2032
4.8 Others
4.8.1 Others analysis Market Estimates and Forecasts, 2020 - 2032
Chapter 5 AI-based Clinical Trial Solutions for Patient Matching Market: End-Use Estimates & Trend Analysis
5.1 Definitions & Scope
5.2 Global AI-based Clinical Trial Solutions for Patient Matching Market: End-Use Market Share Analysis, 2020 and 2032
5.3 Pharmaceutical Companies
5.3.1 Pharmaceutical Companies Analysis Market Estimates and Forecasts, 2020 - 2032
5.4 Academia
5.4.1 Academia analysis Market Estimates and Forecasts, 2020 - 2032
5.5 Others
5.5.1 Others analysis Market Estimates and Forecasts, 2020 - 2032
Chapter 6 AI-based Clinical Trial Solutions for Patient Matching Market: Regional Estimates & Trend Analysis, By Therapeutic Application & End-Use
6.1 Global AI-based Clinical Trial Solutions for Patient Matching Market: Regional Movement Analysis
6.2 North America
6.2.1 North America AI-based Clinical Trial Solutions for Patient Matching Market Estimates and Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.2.2 U.S.
6.2.2.1 U.S. AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.2.3 Canada
6.2.3.1 Canada AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.3 Europe
6.3.1 Europe AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.3.2 U.K.
6.3.2.1 U.K. AI-based Clinical Trial Solutions for Patient Matching Market Estimates and Forecasts by Therapeutic Application, and End-Use, 2020 - 2032
6.3.3 Germany
6.3.3.1 Germany AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.3.4 Spain
6.3.4.1 Spain AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.3.5 France
6.3.5.1 France AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.3.6 Italy
6.3.6.1 Italy AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.3.7 Russia
6.3.7.1 Russia AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.4 Asia Pacific
6.4.1 Asia Pacific AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.4.2 China
6.4.2.1 China AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.4.3 Japan
6.4.3.1 Japan AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.4.4 India
6.4.4.1 India AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.4.5 South Korea
6.4.5.1 South Korea AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.4.6 Australia
6.4.6.1 Australia AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.5 Latin America
6.5.1 Latin America AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.5.2 Brazil
6.5.2.1 Brazil AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.5.3 Mexico
6.5.3.1 Mexico AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.5.4 Argentina
6.5.4.1 Argentina AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.6 MEA
6.6.1 MEA AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.6.2 South Africa
6.6.2.1 South Africa AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.6.3 Saudi Arabia
6.6.3.1 Saudi Arabia AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
6.6.4 UAE
6.6.4.1 UAE AI-based Clinical Trial Solutions for Patient Matching Market Estimates And Forecasts By Therapeutic Application, and End-Use, 2020 - 2032
Chapter 7 Company Profiles
7.1 Unlearn.AI, Inc.
7.1.1 Company Overview
7.1.2 Financial Performance
7.1.3 Product Benchmarking
7.1.4 Strategic Initiatives
7.2 Antidote Technologies, Inc.
7.2.1 Company Overview
7.2.2 Financial Performance
7.2.3 Product Benchmarking
7.2.4 Strategic Initiatives
7.3 Deep6.ai
7.3.1 Company Overview
7.3.2 Financial Performance
7.3.3 Product Benchmarking
7.3.4 Strategic Initiatives
7.4 Mendel.ai
7.4.1 Company Overview
7.4.2 Financial Performance
7.4.3 Product Benchmarking
7.4.4 Strategic Initiatives
7.5 Aris Global
7.5.1 Company Overview
7.5.2 Financial Performance
7.5.3 Product Benchmarking
7.5.4 Strategic Initiatives
7.6 Deep Lens AI
7.6.1 Company Overview
7.6.2 Financial Performance
7.6.3 Product Benchmarking
7.6.4 Strategic Initiatives
7.7 AmeriSourceBergen Corporation
7.7.1 Company Overview
7.7.2 Financial Performance
7.7.3 Product Benchmarking
7.7.4 Strategic Initiatives
7.8 Koneksa
7.8.1 Company Overview
7.8.2 Financial Performance
7.8.3 Product Benchmarking
7.8.4 Strategic Initiatives
7.9 Microsoft Corporation
7.9.1 Company Overview
7.9.2 Financial Performance
7.9.3 Product Benchmarking
7.9.4 Strategic Initiatives
7.10 GNS Healthcare
7.10.1 Company Overview
7.10.2 Financial Performance
7.10.3 Product Benchmarking
7.10.4 Strategic Initiatives