Published: September 2022 | Report Code: 12469 | Available Format: PDF
The AI-based clinical trials solution market size stood at $1,326.9 million in 2021, and it is expected to grow at a CAGR of 20.4% during 2021–2030, to reach $7,073.9 million by 2030.
The growth can be primarily ascribed to the increasing prevalence of chronic diseases and growing demand for advanced drugs. Amongst the several evolving technologies in the healthcare sector (including treatment and research), artificial intelligence plays a major role in trial designing, patient selection and recruitment, site selection, and patient monitoring, with the ultimate aim to boost the count and success of clinical trials.
Pharmaceutical companies are investing a significant amount to replenish their respective pipelines using AI, which is one of the major reasons for the industry growth. In addition, the growing volume of public and private initiatives to drive the adoption of artificial-intelligence-powered solutions in new medicament efficacy studies, to accelerate drug discovery, is driving the market.
Furthermore, the economic efficiency offered by contract research organizations (CROs) over conducting an in-house study is expected to boost the outsourcing of these drug validation solutions over the forecast period. Countries such as Japan, France, Spain, and the U.S. have gained a strong foothold in the healthcare research space, while the U.K. is focusing on enhancing R&D and supplying technology to other countries.
In the same vein, in Asia-Pacific, the market for AI-based clinical trial solutions is expected to exhibit lucrative growth over the forecast period due to the rising penetration of AI-based tools and favorable government initiatives for their adoption in different healthcare fields. As countries begin to liberalize the laws related to the usage of artificial intelligence in research, this technology is expected to witness an increasing demand. The demand for AI-based solutions is expanding as a result of the increasing use of smart technology in the development of advanced medicinal combinations.
According to studies, patient recruitment delays are witnessed in more than 85% of the trials, while over 305 of such studies are terminated early. Patient eligibility and enrolment are two critical elements for the success of the entire study. Platforms powered by machine learning are helping lower this barrier.
The COVID-19 pandemic also contributed to an increase in the use of smart technologies. One reason for the rise in the use of machine-learning-based research and trial solutions is the increasing use of technologically enhanced drug discovery and development solutions, as well as the need for the effective analysis of recruited patient data. To enhance research results and reduce the cost and time needed for testing the efficacy of new drug candidates, pharmaceutical firms, CROs, and academics have switched their attention away from the conventional process and moved toward AI-based solutions.
Drug discovery is a cost-intensive and time-consuming process. As per studies, the capital investment required for the complete cycle for a medicine to be available can be more than $1.2 billion, and the R&D period could be more than 10 years. The adoption of technologically advanced solutions in the drug development process can be beneficial in reducing the time and cost and increasing the safety and accuracy of new medicinal combinations. For instance, a research collaboration of Exscientia and Sumitomo Dainippon Pharma has combined Exscientia’s AI platform and Sumitomo Dainippon Pharma’s expertise in Monoamine GPCR to discover DSP-1181 in less than 12 months, compared to the average time of 4.5 years, using traditional development practices.
In addition to reducing the time consumed by trials, ML-based solutions can also be beneficial in reducing costs by more than 30%. Owing to all such benefits, as per an article, the number of partnerships or collaborations between major AI-based drug discovery companies and pharmaceutical companies increased by over five times during 2015–2020. Such a growing count of partnership activities further signifies the high potential of the AI-based clinical trials solution market growth in the coming years.
The adoption of AI-enabled technology is being influenced by the rising incidence of cancer worldwide and the enormous number of oncology-related medication trials. Additionally, several firms are creating and using AI solutions for clinical trials of cancer therapies, which will accelerate the category's growth with a CAGR of 19.4% during the forecast period.
Market Size in 2021
Revenue Forecast in 2030
Market Trends, Drivers, and Restraints; Revenue Estimation and Forecast; Segmentation Analysis; Impact of COVID-19; Companies’ Strategic Developments; Market Share Analysis of Key Players; Company Profiling
By Clinical Trial Phase; By Therapeutic Application; By End User; By Region
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North America dominated the artificial-intelligence-based clinical trial solution market with a revenue share of 41% in 2021, owing to the high R&D investments, growing adoption of technologically advanced solutions, presence of global players, and their efforts to come up with newer patents.
With the increasing awareness regarding smart-technology-based tools and the rising adoption of artificial intelligence, numerous startups offering advanced solutions are emerging, to take advantage of the market opportunities. The U.S. leads the list with about 150,000 studies conducted since 2008, because of the prominence and size of its pharmaceutical sector. Within the country, California accounts for the most studies, in part, because of its robust tech industry and desire for innovation.
The U.S. is also on top among the investors in healthcare, due to its sizable population, established network of researchers, and expansive healthcare industry.
For instance, in 2020, Unlearn.AI, a U.S.-based company, received substantial series A funding by 8VC, a venture capital company. This is expected to help Unlearn in expanding its reach and widening its product portfolio. In addition, industry players are making advances in their efforts to decrease timelines, by adopting advanced technologies, which is why the U.S. dominated the industry with 87% share in 2021.
For instance, in March 2019, Bristol-Myers Squibb announced its strategic agreement with Concerto HealthAI for the utilization of Concerto’s AI-based solution for drug research. Other key players in the market for AI-based clinical trial solutions in the country are Deep 6, Symphony, and Phesi.
The phase II category dominated the clinical trial phase segment with a revenue share of 51% in 2021, owing to the large number of registered validation cases active in the second phase. In addition, the category is growing as a result of the booming use of smart technologies for data gathering and the analysis of the immediate results of the study on the desired outcome in this stage.
During the forecast timeframe, the phase I category is set to advance at the quickest rate. The applications of AI in phase I trials generally include patient recruitment and retention and trial design improvement. Additionally, in phase 1 studies, these solutions help in creating distinct patient-centric outcomes and gathering real-world data.
The report offers a comprehensive market segmentation analysis along with revenue estimation for the period 2017-2030.
Based on Clinical Trial Phase
Based on Therapeutic Application
Based on End-user
The market for AI-based clinical trials solutions valued $1,326.9 million in 2021.
The AI-based clinical trials solution industry is driven by the rising chronic disease prevalence, booming geriatric population, technological advancements, and stringent regulations for clinical trials.
Phase II dominates the market for AI-based clinical trials solutions.
CVDs will have the highest AI-based clinical trials solutions industry CAGR.
North America and APAC are lucrative for the providers for AI-based clinical trials solutions.
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