AI-Driven Rare Disease Patient Finder Market Report 2026

The artificial intelligence (AI)-driven rare disease patient finder market size has grown exponentially in recent years. It will grow from $1.62 billion in 2025 to $2.11 billion in 2026 at a compound annual growth rate (CAGR) of 29.9%. The growth in the historic period can be attributed to increasing availability of electronic health records, early adoption of data analytics in clinical research, expansion of genomic databases, rising focus on orphan diseases, initial use of ai in trial recruitment.

The artificial intelligence (AI)-driven rare disease patient finder market size is expected to see exponential growth in the next few years. It will grow to $5.95 billion in 2030 at a compound annual growth rate (CAGR) of 29.6%. The growth in the forecast period can be attributed to increasing investments in precision medicine research, rising demand for faster clinical trial enrollment, expansion of real-world evidence analytics, growing collaboration between healthcare and life sciences firms, increasing regulatory support for rare disease innovation. Major trends in the forecast period include increasing use of AI-based patient identification algorithms, rising integration of multi-source health data, growing automation of clinical trial recruitment, expansion of precision patient matching platforms, enhanced focus on rare disease research enablement.

The growing acceptance of digital health and telemedicine is expected to drive the growth of the artificial intelligence (AI)-driven rare disease patient finder market in the coming years. Digital health involves the use of technology, software, and electronic tools to monitor, manage, and improve health and wellness. Telemedicine refers to delivering healthcare services remotely through telecommunications technologies such as video calls, mobile apps, and online platforms. Adoption is increasing as patients and providers seek convenient, time-saving, and accessible healthcare solutions. AI-driven rare disease patient finders support these approaches by accurately identifying patients, enabling remote monitoring, facilitating timely virtual consultations, and delivering personalized care. For example, according to the Organisation for Economic Co-operation and Development (OECD), OECD countries made progress in expanding access to electronic health records (EHRs), with the average availability of online digital health services reaching 82% in 2024, up from 79% in 2023. Therefore, the rising acceptance of digital health and telemedicine is fueling the growth of the AI-driven rare disease patient finder market.

Key players in the AI-driven rare disease patient finder market are focusing on technological innovations, such as precision patient recruitment solutions, to improve the accuracy, speed, and efficiency of identifying eligible patients for rare disease clinical trials while shortening recruitment timelines and enhancing trial success rates. Precision patient recruitment solutions use advanced algorithms and real-world data to accurately locate and engage patients who meet specific clinical trial eligibility criteria. For instance, in April 2024, Citeline, a US-based business intelligence and data analytics company, launched Citeline PatientMatch. This platform integrates advanced algorithms with comprehensive real-world datasets - including lab results, biomarkers, and electronic medical records from over 400 hospitals and health systems - to help sponsors and investigators identify eligible patients efficiently, streamline enrollment, and support complex study protocols across multiple therapeutic areas.

In September 2025, SeqOne, a France-based provider of AI-powered genomic analysis and clinical decision-support tools, acquired Congenica for an undisclosed amount. This acquisition allows SeqOne to combine its AI-driven next-generation sequencing platform with Congenica’s clinical interpretation technology, strengthening capabilities in rare-disease and oncology diagnostics, expanding global reach, and positioning the company as a unified software-centric genomics leader. Congenica, based in the UK, provides clinical genomics software services, including scalable genomic data interpretation, clinical variant classification, and support for rare and inherited disease diagnostics.

Major companies operating in the artificial intelligence (AI)-driven rare disease patient finder market are UnitedHealth Group Incorporated, Dassault Systèmes SE, GeneDx Holdings Corp., HealthVerity Inc., ConcertAI Inc., Komodo Health Inc., Unlearn.AI Inc., Antidote Technologies Inc., Healx Ltd., FDNA Inc., Saventic Health Sp. z o.o., Digital Pharma Lab SAS, AnnieGuard Ltd., Rapid Innovation Labs Inc., Sqilline EOOD, TrialX Inc., enGenome Srl, EveryCure Inc., ThinkGenetic Inc., RareSum Inc.

North America was the largest region in the artificial intelligence (AI)-driven rare disease patient finder market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI)-driven rare disease patient finder market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (AI)-driven rare disease patient finder market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Tariffs are influencing the AI-driven rare disease patient finder market by increasing costs related to imported data servers, cybersecurity infrastructure, analytics platforms, and specialized IT hardware. Life sciences companies and research organizations in North America and Europe are most affected due to reliance on imported digital infrastructure, while Asia-Pacific faces cost pressures on platform deployment. These tariffs are increasing operational expenses and slowing system scaling. However, they are also promoting regional data infrastructure development, localized hosting solutions, and innovation in cloud-native patient identification platforms.

The artificial intelligence (AI)-driven rare disease patient finder market research report is one of a series of new reports that provides artificial intelligence (AI)-driven rare disease patient finder market statistics, including artificial intelligence (AI)-driven rare disease patient finder industry global market size, regional shares, competitors with a artificial intelligence (AI)-driven rare disease patient finder market share, detailed artificial intelligence (AI)-driven rare disease patient finder market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (AI)-driven rare disease patient finder industry. This artificial intelligence (AI)-driven rare disease patient finder market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

An artificial intelligence (AI)-driven rare disease patient finder is a technology platform that utilizes AI algorithms to identify and match patients with rare diseases for clinical trials, research studies, and personalized treatments. It analyzes a variety of datasets, including medical records, genetic information, and real-world health data, to accurately pinpoint potential patients. By improving the efficiency of patient identification, this technology accelerates research, supports clinical trial recruitment, and facilitates the development of targeted therapies.

The key components of an AI-driven rare disease patient finder include software and services. The software consists of programs, instructions, and data that enable computers or digital devices to perform specific tasks and functions. Deployment can be cloud-based or on-premises. The technology finds applications in hospitals, clinics, research institutes, pharmaceutical companies, and similar settings, serving end users such as healthcare providers, life sciences organizations, payers, and others.

The artificial intelligence (AI)-driven rare disease patient finder market consists of revenues earned by entities by providing services such as clinical trial recruitment, patient identification, electronic health record (EHR) data mining, natural language processing (NLP), and real-world evidence (RWE) analytics. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI)-driven rare disease patient finder market also includes sales of predictive analytics tools, natural language processing engines, machine learning models, data integration platforms, electronic health record connectors, genomic data analyzers, patient matching engines, clinical decision support tools, and real-world data aggregators. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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