AI-based Clinical Trial Solutions For Patient Matching Market (2026 - 2033)

AI-based Clinical Trial Solutions For Patient Matching Market Summary

The global AI-based clinical trial solutions for patient matching market size was valued at USD 595.4 million in 2025 and is projected to grow from USD 754.4 million in 2026 to USD 4,228.6 million by 2033, at a CAGR of 27.9% from 2026 to 2033. North America dominated the market, accounting for the largest revenue share of 45.0% in 2025. The growth is largely attributed to the inclusion of AI-powered solutions for conducting and managing clinical trials, which can help reduce clinical trial cycle time, further reducing costs and increasing accuracy and productivity in trial development.

Government initiatives to promote the adoption of artificial intelligence (AI) technologies in the healthcare sector, along with rising awareness of AI, further fuel market growth. The adoption of digitization in clinical and biomedical research is opening opportunities for the market. Key pharma companies are incorporating advanced technological solutions to enhance patient management and clinical trial outcomes. AI-based clinical trial solutions increase patient recruitment by reducing population heterogeneity through the harmonization of large volumes of health information from a wide array of sources and platforms, such as medical imaging, electronic medical records (EMRs), and omics data.

Source: Grand View Research, IR Documents, Primary Interviews, Paid Databases

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These platforms allow selecting the groups of patients most likely to respond to the trial and to provide a quantifiable & measurable clinical endpoint. AI-based solutions and systems can be used to examine patient health information records & clinical trial eligibility criteria, and to 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.

Government organizations in developed nations such as the U.S. and Europe are providing funding and establishing stringent regulatory frameworks to drive the adoption of AI-based solutions in clinical trials. Moreover, governments in developing nations are raising awareness of AI-based clinical trial solutions among stakeholders to accelerate drug discovery and patient recruitment, thereby improving patient engagement & monitoring.

The increasing number of startups providing AI-based patient recruitment solutions for life science organizations supporting their clinical studies is positively impacting market growth. A large number of pharmaceutical manufacturers have to invest substantial sums in developing medicines to expand their product pipelines, as many big vendors go off patent, a key driver of growth in the clinical trials market.

Furthermore, growing initiatives by public and private organizations to support the adoption of AI-powered technological solutions in clinical trials are propelling market growth. Pharma and biotech organizations are rapidly implementing AI-based platforms and solutions to support their clinical research studies. Corporations are adopting these solutions for enhancing recruitment, identification, engagement, and real-time monitoring of patients.

However, data privacy risks may hamper the market in the coming years. Adoption of AI-based technologies requires protecting the privacy and confidentiality of large volumes of trial-related datasets. Most healthcare organizations are moving to the cloud to store and manage petabytes of sensitive data. The cloud model allows users to access data from anywhere and at any time, enabling more users to access the website and increasing the likelihood of cybersecurity attacks.

Analyst Perspective

The industry is gaining importance as pharmaceutical companies and research organizations seek to improve trial efficiency and accelerate patient recruitment. Traditional recruitment methods are often time-consuming and lead to delays, making AI-driven platforms increasingly valuable for identifying eligible participants in large, diverse datasets. By combining electronic health records, genomic data, and clinical information, these solutions can help improve matching accuracy while reducing recruitment timelines. Companies with strong AI capabilities, robust data integration platforms, and expertise in regulatory compliance are likely to strengthen their market position. As clinical trials become more personalized and decentralized, demand is expected to shift toward intelligent platforms that enable faster enrollment, broaden patient diversity, and improve trial outcomes. Long-term success will depend on algorithm accuracy, interoperability, data security, and seamless integration into existing clinical research workflows.

Therapeutic Application Insights

The oncology segment accounted for the largest share of around 25.0% in 2025, driven by the high global burden of cancer and the growing complexity of oncology clinical trials. Precision oncology studies require identifying patients based on genomic, biomarker, and clinical characteristics, making AI-powered patient matching an essential tool for improving recruitment efficiency and shortening trial timelines. Pharmaceutical companies are accelerating the integration of AI into oncology research and clinical development. For instance, in January 2026, AstraZeneca acquired Modella AI to incorporate foundation AI models into oncology research, biomarker discovery, clinical development, and patient selection workflows.

The cardiovascular disease (CVD) segment is expected to register the fastest CAGR during the forecast period, supported by the increasing global prevalence of cardiovascular disorders and the growing number of clinical studies evaluating novel therapeutics and medical devices. AI-based patient-matching solutions are helping researchers identify eligible participants more efficiently by analyzing electronic health records, imaging data, laboratory results, and other real-world clinical data. The expanding use of AI in cardiovascular research is reflected in ongoing industry developments. For instance, in March 2025, Tempus AI presented four cardiovascular research abstracts at the American College of Cardiology Annual Meeting, demonstrating AI-enabled approaches for disease identification, risk stratification, and patient cohort analysis to support clinical research.

End-use Insights

The pharmaceutical companies segment accounted for the largest share of around 65.0% in 2025. The segment is driven by increasing adoption of artificial intelligence to accelerate patient recruitment, optimize protocol design, identify biomarkers, and improve clinical trial efficiency. AI-powered platforms enable sponsors to analyze electronic health records, genomic datasets, medical imaging, and real-world evidence to identify eligible participants more accurately and reduce enrollment timelines. The growing focus on precision medicine and biomarker-driven therapies continues to strengthen demand for AI-enabled patient matching solutions. Companies such as IQVIA have expanded AI-powered natural language processing and clinical data analytics capabilities to support drug development and clinical research workflows.

The segment is also benefiting from increasing collaborations between pharmaceutical companies and AI technology providers to improve trial success rates, reduce development costs, and accelerate the delivery of new therapies. Growing investments in oncology, rare diseases, immunology, and other precision medicine areas are expected to support market expansion further.

The others segment is projected to register the fastest growth during the forecast period. These organizations are adopting AI-based patient matching platforms to improve recruitment efficiency, enhance data quality, increase protocol compliance, and reduce overall clinical trial costs. Rising public and private investments in decentralized clinical trials, real-world evidence generation, and digitally enabled clinical research are expected to accelerate further the adoption of AI-powered patient-matching solutions among these end users.

Regional Insights

The North America AI-based clinical trial solutions for patient matching market led in 2025, accounting for a revenue share of approximately 45.0%, driven by the region's advanced healthcare infrastructure, high concentration of pharmaceutical and biotechnology companies, and strong adoption of artificial intelligence across clinical research. The presence of leading AI technology providers, contract research organizations, academic medical centers, and a large volume of registered clinical trials continues to support market growth. In addition, increasing investments in precision medicine, digital health, and real-world evidence are accelerating the integration of AI into patient recruitment and trial management workflows.

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Healthcare organizations across North America are actively deploying AI-enabled platforms to improve patient identification, optimize recruitment, and shorten clinical trial timelines. For instance, in August 2025, the Cleveland Clinic expanded the deployment of Dyania Health's AI platform across its research enterprise to accelerate patient identification and clinical trial recruitment. The region is expected to maintain its leadership position throughout the forecast period, supported by continued innovation in AI technologies, favorable regulatory initiatives for digital health, and sustained investments in clinical research.

Asia Pacific AI-based Clinical Trial Solutions For Patient Matching Market Trends

The AI-based clinical trial solutions for patient matching market in Asia Pacific is expected to register the fastest growth during the forecast period. The region is witnessing rapid adoption of artificial intelligence across healthcare and clinical research, supported by growing investments in digital health infrastructure, expanding pharmaceutical and biotechnology industries, and favorable government initiatives that promote AI innovation. In addition, the growing number of clinical trials conducted across countries such as China, Japan, India, South Korea, and Australia is driving demand for AI-enabled patient recruitment and matching solutions.

Healthcare organizations and technology providers are collaborating to accelerate the adoption of AI in clinical research. For instance, in April 2025, NVIDIA and IQVIA expanded their collaboration across the Asia Pacific region to deploy AI technologies to support clinical research, patient identification, and clinical trial optimization. Rising investments in precision medicine, real-world data analytics, and decentralized clinical trials are expected to further strengthen market growth across the region during the forecast period.

Key AI-based Clinical Trial Solutions For Patient Matching Company Insights

The AI-based clinical trial solutions for patient matching market is characterized by rapid technological innovation and increasing collaboration among pharmaceutical companies, healthcare providers, contract research organizations, and AI technology vendors. Growing awareness of AI-enabled patient recruitment platforms, coupled with rising demand for faster and more accurate participant identification, has accelerated investment in new technologies and encouraged the entry of innovative startups. Reflecting this trend, in January 2025, Lindus Health acquired outpatient recruitment specialist Citruslabs to strengthen its AI-enabled clinical trial platform and enhance patient recruitment and matching capabilities.

Market participants are actively pursuing strategic initiatives, including mergers and acquisitions, partnerships, product launches, and investments in advanced artificial intelligence and machine learning technologies, to strengthen their competitive positions. These collaborations are focused on improving recruitment efficiency, integrating real-world data and electronic health records, enabling biomarker-driven patient selection, and supporting decentralized clinical trials. As AI adoption continues to expand across the clinical development ecosystem, strategic partnerships and continued research and development are expected to remain key drivers of market growth throughout the forecast period.

Key AI-based Clinical Trial Solutions For Patient Matching Companies

The following key companies have been profiled for this study on the AI-based clinical trial solutions for patient matching market.

• Unlearn AI, Inc.

• Antidote Technologies, Inc.

• Deep 6 AI (Tempus AI, Inc.)

• Mendel AI

• ArisGlobal

• Deep Lens

• Cencora, Inc.

• Koneksa Health

• Microsoft Corporation

• GNS Healthcare, Inc.

Recent Developments

• In March 2025, Tempus AI completed the acquisition of Deep 6 AI, a provider of artificial intelligence solutions for clinical trial patient matching. The acquisition expands Tempus AI's access to electronic health record datasets and provider networks, strengthening automated patient identification capabilities and improving clinical trial enrollment efficiency.

Global AI-based Clinical Trial Solutions For Patient Matching Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2021 to 2033. For the purpose of this study, Grand View Research has segmented the global AI-based clinical trial solutions for patient matching market report based on therapeutic application, end-use, and region:

• Therapeutic Application Outlook (Revenue, USD Million, 2021 - 2033)

  • Oncology

  • Cardiovascular Diseases

  • Neurological Diseases or Conditions

  • Metabolic Diseases

  • Infectious Diseases

  • Others

• End-use Outlook (Revenue, USD Million, 2021 - 2033)

  • Pharmaceutical Companies

  • Academia

  • Others

• Regional Outlook (Revenue, USD Million, 2021 - 2033)

  • North America

    • U.S.

    • Canada

  • Europe

    • Germany

    • UK

    • France

    • Italy

    • Spain

    • Russia

  • Asia Pacific

    • Japan

    • China

    • India

    • Australia

    • South Korea

  • Latin America

    • Brazil

    • Mexico

    • Argentina

  • MEA

    • South Africa

    • UAE

    • Saudi Arabia