The global AI-based clinical trial solutions for patient matching market were valued at USD 253.13 million in 2022 and is expected to grow at a CAGR of 29.2% during the forecast period.The utilization of digitalization in clinical and biological research has opened up new possibilities for AI-based clinical trial solutions in the patient-matching market. Prominent pharmaceutical corporations are leveraging cutting-edge technology to enhance their clinical trial processes. By harnessing artificial intelligence (AI), these solutions improve patient enrollment by addressing population heterogeneity and integrating extensive health information data from various sources, such as electronic medical records (EMRs), medical imaging, and omics data.
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The market for AI-based clinical trial solutions is witnessing significant growth due to the increasing efforts from both public and commercial sectors to promote adopting AI-powered technology in clinical research. Pharma and biotech companies rapidly embrace these platforms and solutions to support their investigative studies. These technologies offer valuable patient recruitment, identification, engagement, and real-time monitoring benefits.
Furthermore, concerns regarding data privacy pose potential limitations for the industry in the coming years. The vast databases of trial-related data must be safeguarded and kept confidential to implement AI-based solutions successfully. Healthcare organizations typically store and manage large amounts of sensitive data on the cloud, enabling convenient access anywhere and anytime. However, this accessibility also increases the risk of cybersecurity threats as more individuals can access the data. This aspect may hinder the market's expansion in the near future.
AI-based clinical trial solutions have emerged as valuable tools in the COVID-19 pandemic, providing significant advantages for patient matching in related clinical trials. These solutions utilize artificial intelligence to streamline the process of identifying suitable participants by analyzing extensive patient data from various sources. By automating and optimizing the patient matching process, AI-based solutions enhance the efficiency of clinical trials, especially in the rapidly evolving landscape of COVID-19 research.
Furthermore, AI algorithms can identify patients at higher risk or more likely to benefit from specific interventions, improving trial outcomes and resource allocation. Real-time monitoring and data analysis capabilities contribute to informed decision-making and more accurate results.
Growth Drivers
The AI-based clinical trial solutions for patient matching market are poised for significant growth due to the advancements in AI and machine learning technologies that have paved the way for sophisticated algorithms and tools to analyze large datasets to identify suitable patients for clinical trials. By leveraging factors like demographics, medical history, genetic profiles, and lifestyle information, AI-based solutions can match patients with specific trial criteria accurately and efficiently.
The increasing demand for personalized medicine is driving the growth of the patient-matching market. Personalized medicine aims to provide tailored treatments based on individual characteristics. Clinical trials play a crucial role in developing such therapies. AI-based patient matching solutions can swiftly identify patients with the traits or biomarkers required for a particular trial, aligning with the demand for personalized medicine and accelerating the development of targeted treatments.
The need for efficient patient recruitment and enrollment in clinical trials is a significant driver. Traditional recruitment methods are often time-consuming and expensive. AI-based solutions streamline the process by utilizing data analytics and predictive modeling to identify potential participants who meet the trial criteria. These solutions improve patient engagement and retention throughout the trial and enhance the overall efficiency of the recruitment and enrollment process.
Moreover, the rising prevalence of chronic diseases further fuels the growth of AI-based patient-matching solutions. With conditions like cancer, diabetes, and cardiovascular disorders rising globally, clinical trials are crucial for developing new therapies. AI-based solutions can effectively identify patients who meet the specific criteria for these trials, allowing researchers and pharmaceutical companies to expedite drug development and bring innovative treatments to market more rapidly.
The market is primarily segmented based on therapeutic application, end-use, and region.
By Therapeutic Application |
By End-Use |
By Region |
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The oncology segment emerged as the dominant revenue-generating field in 2022, primarily driven by the escalating global cancer incidence. Consequently, the industry has witnessed a notable increase in clinical trials, reflecting a positive trend.
Leading pharmaceutical companies have collaborated with AI development firms to leverage the potential of artificial intelligence (AI) in cancer research. These partnerships aim to harness AI-based technologies specifically designed for pharmaceutical applications. An example of such collaboration occurred in January 2022, when Deep Lens joined forces with Hematology-Oncology Associates of Central New York. Their collaboration focused on expanding the clinical trial program by utilizing Deep Lens' VIPER system to pre-screen patients and identify eligible individuals for participation.
The introduction of innovative technologies further accelerates the growth trajectory of the oncology sector. Survivor Net, for instance, introduced an AI-powered clinical trial finder in June 2022. This platform effectively connects cancer patients with cutting-edge research opportunities, ensuring that those in need are promptly associated with relevant clinical trials.
The pharmaceutical companies segment holds the largest revenue share of the market. This can be attributed to the growing focus on leveraging AI-based technologies to enhance the discovery of novel drug targets, improve biomarker identification, and streamline the drug development process. Pharmaceutical companies have recognized the potential of AI in these areas and are actively embracing its capabilities.
One notable example is IQVIA's Linguamatics, a text mining program that offers natural language processing (NLP) solutions tailored for pharmaceutical firms. This technology assists in extracting valuable insights from vast amounts of textual data, aiding in identifying relevant information for drug discovery and development.
The pharmaceutical industry is experiencing expansion due to the increasing prevalence of chronic diseases and the rising demand for personalized therapies. This creates a favorable market environment for pharmaceutical companies to innovate and cater to specific patient needs.
North America accounted to hold largest market share of the market in 2022 and will continue its significant growth during forecast period. The presence of prominent companies in the region and the increasing number of AI startups contribute to the market expansion. Furthermore, the abundance of registered clinical studies in North America provides a favorable environment for the industry.
According to World Health Organization (WHO) data, the United States conducted the highest number of clinical trials, approximately 157,618 studies, between 1999 and 2021. Government initiatives to adopt AI-based technologies and the growing interest in these technologies further fuel the region's growth.
The Asia Pacific region is projected to experience the fastest compound annual growth rate (CAGR) in the market during the forecast period. This growth can be attributed to the increasing adoption of AI-based clinical technologies and pro-AI government initiatives in the region.
Moreover, the Asia Pacific region has benefited from many clinical studies over the past decade, and clinical trial registration has increased sevenfold in Asia Pacific. The availability of a substantial patient population, affordable access to highly skilled labor, and competitive hiring rates are key factors driving this trend.
Some of the major players operating in the global market include Unlearn.AI, Inc.; Antidote Technologies; Inc.; Deep6.ai; Mendel.ai; Aris Global; Deep Lens; AmerisourceBergen Corporation; Koneksa; Microsoft Corporation; GNS Healthcare.
Report Attributes |
Details |
Market size value in 2023 |
USD 285.88 million |
Revenue forecast in 2032 |
USD 2,876.37 million |
CAGR |
29.2% from 2023 – 2032 |
Base year |
2022 |
Historical data |
2019 – 2021 |
Forecast period |
2023 – 2032 |
Quantitative units |
Revenue in USD million and CAGR from 2023 to 2032 |
Segments Covered |
By Therapeutic Application, By End-Use, By Region |
Regional scope |
North America, Europe, Asia Pacific, Latin America, Middle East & Africa |
Key Companies |
Unlearn.AI, Inc.; Antidote Technologies; Inc.; Deep6.ai; Mendel.ai; Aris Global; Deep Lens; AmerisourceBergen Corporation; Koneksa; Microsoft Corporation; GNS Healthcare. |
The global AI-based clinical trial solutions for patient matching market size is expected to reach USD 2,876.37 million by 2032.
Top market players in the AI-based Clinical Trial Solutions for Patient Matching Market are Unlearn.AI, Inc.; Antidote Technologies; Inc.; Deep6.ai; Mendel.ai; Aris Global; Deep Lens.
North America contribute notably towards the global AI-based Clinical Trial Solutions for Patient Matching Market.
The global AI-based clinical trial solutions for patient matching market expected to grow at a CAGR of 29.2% during the forecast period.
The AI-based Clinical Trial Solutions for Patient Matching Market report covering key are therapeutic application, end-use, and region.