Artificial Intelligence (AI)-Driven Rare Disease Patient Finder Market Report 2025

The artificial intelligence (AI)-driven rare disease patient finder market size has grown exponentially in recent years. It will grow from $1.25 billion in 2024 to $1.62 billion in 2025 at a compound annual growth rate (CAGR) of 30.1%. The growth in the historic period can be attributed to increasing adoption of genomic sequencing, rising utilization of electronic health records, growing collaborations between pharmaceutical companies and artificial intelligence (AI) startups, heightened focus on early disease detection, and increasing availability of real-world evidence.

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 $4.6 billion in 2029 at a compound annual growth rate (CAGR) of 29.7%. The growth in the forecast period can be attributed to increasing integration of multimodal data analytics, rising adoption of AI-powered clinical decision support systems, growing use of wearable and remote monitoring devices, increasing investment in patient-centric healthcare platforms, and rising emphasis on predictive analytics for rare disease detection. Major trends in the forecast period include advancements in natural language processing for unstructured medical data, integration of federated learning for secure patient data sharing, technology-enabled multiomics data analysis, developments in synthetic data generation for rare disease modeling, and innovations in AI-driven digital biomarkers.

The growing acceptance of digital health and telemedicine is expected to drive the expansion of the artificial intelligence (AI)-driven rare disease patient finder market. Digital health involves using technology, software, and electronic tools to monitor and improve health, while telemedicine delivers healthcare services remotely through technologies such as video calls, mobile apps, and online platforms. This shift toward digital health and telemedicine is driven by the desire for more convenient, accessible, and time-saving healthcare options from both patients and healthcare providers. AI-driven rare disease patient finders support these services by accurately identifying patients, facilitating remote monitoring, and enabling timely virtual consultations with personalized care. For example, a 2023 survey by Rock Health revealed that 76% of individuals over 55 years old had used telemedicine, and 80% of all respondents had accessed telemedicine at some point, up from 72% in 2021. This increasing acceptance is contributing to the growth of the artificial intelligence (AI)-driven rare disease patient finder market.

Companies in the artificial intelligence (AI)-driven rare disease patient finder market are focusing on developing precision patient recruitment solutions, which use advanced algorithms and real-world data to identify and recruit eligible patients more quickly. These solutions aim to reduce recruitment timelines and enhance the success rates of clinical trials. For instance, Citeline, a U.S.-based business intelligence company, launched Citeline PatientMatch in April 2024. This platform uses sophisticated algorithms combined with real-world data, such as lab results, biomarkers, and electronic medical records from over 400 hospitals, to help sponsors and researchers identify suitable patients for clinical trials. This technology streamlines the enrollment process and supports diverse study protocols in multiple therapeutic areas.

In November 2022, Norstella, a U.S.-based life sciences technology company specializing in AI-assisted clinical trial planning for difficult-to-recruit patient populations such as those with rare diseases, merged with Citeline for $5 billion. The merger aims to enhance Norstella’s global presence by integrating Citeline’s clinical trial intelligence and patient recruitment capabilities. Citeline is known for its AI-driven tools, including the NorstellaLinQ product, which is specifically designed to target and identify rare disease patient populations, further supporting drug development and commercialization.

Major players 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., and RareSum Inc.

North America was the largest region in the artificial intelligence (AI)-driven rare disease patient finder market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in artificial intelligence (AI)-driven rare disease patient finder report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and 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, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The sudden escalation of U.S. tariffs and the consequent trade frictions in spring 2025 are severely impacting the healthcare sector, particularly in the supply of critical medical devices, diagnostic equipment, and pharmaceuticals. Hospitals and healthcare providers are facing higher costs for imported surgical instruments, imaging equipment, and consumables such as syringes and catheters, many of which have limited domestic alternatives. These increased costs are straining healthcare budgets, leading some providers to delay equipment upgrades or pass on expenses to patients. Additionally, tariffs on raw materials and components are disrupting the production of essential drugs and devices, causing supply chain bottlenecks. In response, the industry is diversifying sourcing strategies, boosting local manufacturing where possible, and advocating for tariff exemptions on life-saving medical products.

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

The main components of the AI-driven rare disease patient finder are software and services. The software includes programs and algorithms that process health and genomic data to generate actionable insights. Deployment modes include cloud-based and on-premises solutions. These platforms are applied across hospitals, clinics, research institutes, and pharmaceutical companies, serving end-users such as healthcare providers, life sciences companies, payers, and other stakeholders in rare disease management.

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 the artificial intelligence (AI)-driven rare disease patient finder industry global market size, regional shares, competitors with the 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 scenarios of the industry.

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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