AI Based Clinical Trials Solution Market Size Report by Clinical Trial Phase (Phase-I, Phase-II, Phase-III), Therapeutic Application (Oncology, Cardiovascular Diseases, Neurological Diseases or Conditions, Metabolic Diseases, Infectious Diseases), End-User (Pharmaceutical Companies, Academia) - Global Industry Demand Forecast to 2030

Market Overview

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.

Adoption of Technology-Based Drug Development Approach Drives Market

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.

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North America Makes Largest Contribution to Global Revenue Generation

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.

AI-Based Solutions Majorly Used for Phase II Clinical Trials

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.

Key Players in AI-Based Clinical Trials Solution Market Are:

• Exscientia plc
• nference Inc.
• Verily Life Sciences LLC
• GNS Healthcare
• Deep Lens Inc.
• Trials.ai
• Median Technologies SA
• Mendel.ai
• Deep6 ai
• Antidote Technologies Inc.

Market Size Breakdown by Segment

The report offers a comprehensive market segmentation analysis along with revenue estimation for the period 2017-2030.

Based on Clinical Trial Phase

• Phase-I
• Phase-II
• Phase-III

Based on Therapeutic Application

• Oncology
• Cardiovascular Diseases
• Neurological Diseases or Conditions
• Metabolic Diseases
• Infectious Diseases

Based on End-user

• Pharmaceutical Companies
• Academia

Geographical Analysis

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • U.K.
  • France
  • Italy
  • Spain
• Asia-Pacific (APAC)
  • Japan
  • China
  • India
  • South Korea
  • Australia
• Latin America
  • Brazil
  • Mexico
• Middle East and Africa
  • Saudi Arabia
  • South Africa
  • U.A.E.