Artificial Intelligence (AI) in Clinical Trials Market by Offering (Software, Services), Technology (Machine Learning, Deep Learning, Supervised), Application (Cardiovascular, Metabolic, Oncology), End User (Pharma, Biotech,CROs) - Global Forecasts to 2027
The AI in clinical trials Market is projected to reach $4.8 billion by 2027 from $1.5 billion in 2022, at a CAGR of 25.6% during the forecast period. The growing need to curb clinical trials costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of artificial intelligence in clinical trials market.
However, shortage of AI workforce and ambiguous regulatory guidelines for medical software and lack of data sets in this field are some of the factors expected to restrain the growth of AI in clinical trials market in the coming years.
Artificial Intelligence in Clinical trials Market Trend
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AI in Clinical Trials Market Size, Share and Dynamics
Role of AI in clinical trails:
Clinical trials are the backbone of medical research and help pharmaceutical and biopharmaceutical companies develop and commercialize new products. The majority of clinical trails are involved in the investigation of the safety and efficacy of a drug molecule. It takes more than ten years and billions of dollars in research and development to bring a single drug into the market. Atypically the success rate of these lengthy clinical trials is less than 10%. Clinical trials are the area of drug research that has most recently acknowledged and allowed beneficial disruption from AI. Clinical trial designs, patient cohort selection and recruitment, study site, investigator selection, patient monitoring, protocol adherence, and the outsourcing of necessary skills and talents are the critical elements for the success of any clinical trial. Through a greater range of data sources, such as electronic and medical health records, AI can automatically enable effective patient selection. It helps biopharma companies to identify qualified investigators as well in patient management by automated data capture and sharing data across systems. As more and more data are electronically available, it is natural that AI will play an increasingly important role in mining the data efficiently. AI has the potential to significantly improve a number of R&D domains, including the discovery of novel targets, the selection of drug candidates, the analysis of biometric data from wearable devices, and the prediction of the effects of drugs in patients with disease.
How and why AI workforce shortage is important retraining factor holding back the growth of the market?
AI is a complex system, and companies require a workforce with specific skill sets to design, manage, and implement AI systems. Personnel dealing with AI systems should be familiar and aware of technologies such as machine intelligence, deep learning, and other AI technologies. Additionally, integrating AI technologies into existing systems is a challenging task that necessitates substantial data processing in order to replicate human brain behavior. Even slight errors might cause system failure and have a negative impact on the desired outcome. The absence of professional standards and certifications in AI/ML technologies is restraining the growth of AI
What are the emerging markets for AI in clinical trials?
Emerging economies such as India, China, and countries in the Middle East are expected to offer potential growth opportunities for players operating in the AI in clinical trials market. In most of these countries, the demand for pharmaceuticals is expected to increase significantly, owing to the rising incidence of chronic and infectious diseases, increasing income levels, and improving healthcare infrastructure. As a result, these markets are very attractive for companies whose profit margins are affected by stagnation in mature markets, the patent expiration of drugs, and increasing regulatory hurdles.
“Deep learning technology segment accounted for the largest share of the global AI in clinical trials market for machine learning technology”
Based on type, the machine learning technology segment further segmented into deep learning, supervised learning. and other machine learning technologies. Deep learning segment accounted for the largest share of the market in 2021, and this segment also expected to grow at the highest CAGR during the forecast period. Deep learning helps in managing data in a consistent manner, saves time, reduces the chances of errors in the clinical trials process, and reduces the workload for end users are some of the key factors for the market growth of this segment.
“Services segment expected to hold the largest share of this market in 2022”
Based on offering, the AI in clinical trials market is segmented into software and services. The services segment expected to account for the largest market share of the global AI in clinical trials services market in 2022, and also expected to grow at the highest CAGR from 2022 to 2027. The benefits associated with AI services and the strong demand for AI services among end users are the key factors driving the growth of this market segment.
The infectious disease segment expected to grow at the highest CAGR during the forecast period”
On the basis of application, the AI in clinical trials market is segmented into neurological diseases and condition, cardiovascular diseases, metabolic diseases, infectious disease, immunology diseases, and other applications. Informtious disease segment form the fastest-growing application segment in this market, owing to the increasing number of clinical trails for vaccine and drugs for covid-19 and other infectious disease and rising investment in R&D for infectious diseases. On the other hand, The oncology segment accounted for the largest share of the market in 2021, owing to the increasing demand for effective cancer drugs and a large number of drug trials in the field of oncology is contributing to the adoption of AI-enabled technologies in this application area. Also, many players are developing and adopting oncology-based AI tools for clinical trials, thus impelling the segment growth.
North America accounted for the largest share of the global AI in clinical trials market in 2021.
The AI in clinical trials market is segmented into four key regions—North America, Europe, APAC, and the Rest of the World (RoW). North America, being the early adopter of advanced technologies, has captured the largest share of the AI in clinical trials market in 2021, followed by Europe and APAC. It is also projected to register the highest CAGR. Currently, North America is home to a number of prominent AI technology providers as well as leading start-up firms. Other market drivers include the well-established pharmaceutical industry, high investments in the biosimilars and biologics segment, increasing R&D expenditure, the large pool of clinical trial service providers in the region, and the strong presence of leading pharmaceutical companies such as Pfizer (US), Abbott Laboratories (US), and Johnson & Johnson (US) in the region.
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Some of the key players are IBM corporation, Exscientia, Saama Technologies, Unlearn.AI, Inc., BioSymetrics, Euretos, Trials.Ai, Insilico Medicine, Ardigen, Pharmaseal, Koninklijke Philips N.V., Intel, Numerate, AiCure, LLC., Envisagenics, NURITAs, BioAge Labs, Inc., Symphony AI., Median Technologies, Innoplexus, Antidote Technologies, Inc., GNS Healthcare, Koneksa Health, Halo Health Systems, and DEEP LENS AI. These players are increasingly focusing on collaboration, partnership, acquisition and product/services upgrade to expand their product offerings and presence in the global market.
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Report Metric |
Details |
Market size available for years |
2020-2027 |
Base year considered |
2021 |
Forecast period |
2022–2027 |
Forecast units |
Value (USD Million/Billion) |
Segments covered |
Offering, Technology, Application, End User,And Region |
Geographies covered |
North America (US, and Canada), Europe (Germany, France, UK, Italy, and the RoE), Asia Pacific (Japan, China, India, and RoAPAC), and RoW |
Companies covered |
IBM corporation, Exscientia, Saama Technologies, Unlearn.AI, Inc., BioSymetrics, Euretos, Trials.Ai, Insilico Medicine, Ardigen, Pharmaseal, Koninklijke Philips N.V., Intel, Numerate, AiCure, LLC., Envisagenics, NURITAs, BioAge Labs, Inc., Symphony AI., Median Technologies, Innoplexus, Antidote Technologies, Inc., GNS Healthcare, Koneksa Health, Halo Health Systems, and DEEP LENS AI |
The study categorizes the AI in clinical trials market into the following segments and subsegments:
AI in clinical trials market, By Offering
- Software
- Phase I
- Phase II
- Phase III
- Services
- Phase I
- Phase II
- Phase III
AI in clinical trials market, By Technology
- Machine Learning
- Deep Learning
- Supervised Learning
- Other Machine Learning Technologies
- Other Technologies
AI in clinical trials market, by Application
- Oncology
- Nuerological disease and condition
- Cardiovascular diseases
- Metabolic diseases
- Infecstious disease
- Immunology disease
- Other Applications
AI in clinical trials market, By End User
- Pharmaceutical & biotechnology companies
- Contract research organizations
- Other end users
AI in clinical trials Market, By Region,
- North America
- US
- Canada
- Europe
- Germany
- France
- UK
- Rest of Europe
- Asia Pacific
- Japan
- China
- India
- Rest of Asia Pacific
- ROW
Recent Developments:
- In September 2020, Parexel International acquired the Natural Language Processing (NLP) technology assets. It transferred key personnel of Roam Analytics, Inc., a healthcare software company, thereby strengthening Parexel’s commitment to leveraging Artificial Intelligence (AI) and Machine Learning (ML) to drive new drug development.
- In February 2021, Exscientia (UK) and the University of Oxford collaborated to develop treatments for Alzheimer's disease
- In January 2022, Exscientia (UK) and sanofi (France) establish strategic research collaboration to develop ai-driven pipeline of precision-engineered medicines, leveraging Exscientia’s end-to-end AI-driven platform utilizing actual patient samples. Collaborative efforts aim to accelerate drug discovery and improve clinical success.
Frequently Asked Questions (FAQ):
What is the projected market of the global AI in clinical trials market in 2027?
The projected market of the global AI in clinical trials market is expected to be 4.8 billion in 2027.
Who are the leading and emerging players in the AI in clinical trials market?
Some of the leading players in the AI in clinical trials market include IBM corporation, Exscientia, Saama Technologies, Unlearn.AI, Inc., BioSymetrics, Euretos, Trials.Ai, Insilico Medicine, Ardigen, Pharmaseal, Koninklijke Philips N.V., Intel, Numerate, AiCure, LLC., Envisagenics, NURITAs, BioAge Labs, Inc., Symphony AI., Median Technologies, Innoplexus, Antidote Technologies, Inc., GNS Healthcare, Koneksa Health, Halo Health Systems, and DEEP LENS AI.
Who are the major end-users of the AI in clinical trials market?
Pharmaceutical & biotechnology companies, CROs, and other. Pharmaceutical & biotechnology companies are the largest end user of this market
What are the major Offering/product in the AI in clinical trials market?
Based on offering, the AI in clinical trials market is segmented into software, and services. The services segment accounted for the largest share of the global market
What are the major applications of AI in clinical trials market?
Neurological diseases and condition, cardiovascular diseases, metabolic diseases, infectious disease, immunology diseases, and other applications
What are the major technology in the AI in clinical trials market?
Machine learning and other technology. The machine learning technology further includes deep learning, supervised learning, and other machine learning technologies .
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TABLE OF CONTENTS
1 INTRODUCTION
1.1 OBJECTIVES OF THE STUDY
1.2 MARKET DEFINITION
1.3 MARKET SCOPE
1.3.1 MARKETS COVERED
1.3.2 YEARS CONSIDERED FOR THE STUDY
1.4 CURRENCY
1.5 LIMITATIONS
1.6 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY SOURCES
2.1.1.1 Key data from secondary sources
2.1.2 PRIMARY SOURCES
2.1.2.1 Key data from primary sources
2.1.2.2 Key industry insights
2.2 MARKET SIZE ESTIMATION
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
2.4 ASSUMPTIONS FOR THE STUDY
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Growing number of cross-industry collaborations and partnerships
5.2.1.2 Increasing adoption of AI based platform to improve productivity and efficiency of clinical trials
5.2.1.3 Growing need to control drug development cost and reduce time involved in drug development
5.2.1.4 Increasing clinical trails
5.2.2 RESTRAINTS
5.2.2.1 Shortage of AI workforce and ambitious regulatory guidelines for medical software
5.2.3 OPPORTUNITIES
5.2.3.1 Need for novel clinical trial designs for complex cell and gene therapies
5.2.3.2 Growth in the drugs and biologics market
5.2.4 CHALLENGE
5.2.3.1 Limited availability of data sets
5.3 VALUE CHAIN ANALYSIS
5.4 ECOSYSTEM ANALYSIS
5.5 PORTER’S FIVE FORCES ANALYSIS
5.6 PRICING ANALYSIS
5.7 TECHNOLOGY ANALYSIS
5.8 REGUALTORY ANALYSIS
5.9 USE CASES
5.10 INDUSTRY TRENDS
6 ARTIFICIAL INTELLIGENCE IN CLINICAL TRIALS MARKET, BY OFFERING (USD MILLION; 2020-2027)
6.1 INTRODUCTION
6.2 SOFTWARE
6.2.1 PHASE I
6.2.2 PHASE II
6.2.3 PHASE III
6.3 SERVICES
6.3.1 PHASE I
6.3.2 PHASE II
6.3.3 PHASE III
7 ARTIFICIAL INTELLIGENCE IN CLINICAL TRIALS MARKET, BY TECHNOLOGY (USD MILLION; 2020-2027)
7.1 INTRODUCTION
7.2 MACHINE LEARNING
7.2.1 DEEP LEARNING
7.2.2 SUPERVISED LEARNING
7.2.3 OTHER MACHINE LEARNING TECHNOLOGIES
7.3 OTHER TECHNOLOGIES
8 ARTIFICIAL INTELLIGENCE IN CLINICAL TRIALS MARKET, BY APPLICATION (USD MILLION; 2020-2027)
8.1 INTRODUCTION
8.2 ONCOLOGY
8.3 NEUROLOGICAL DISEASES AND CONDITIONS
8.4 CARDIOVASCULAR DISEASES
8.5 METABOLIC DISEASES
8.6 INFECTIOUS DISEASES
8.7 IMMUNOLOGY DISEASES
8.8 OTHER APPLICATIONS
9 ARTIFICIAL INTELLIGENCE IN CLINICAL TRIALS MARKET, BY END USER (USD MILLION; 2020-2027)
9.1 INTRODUCTION
9.2 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES
9.3 CONTRACT RESEARCH ORGANIZATIONS
9.4 OTHER END USERS
10 ARTIFICIAL INTELLIGENCE IN CLINICAL TRIALS MARKET, BY REGION (USD MILLION; 2020-2027)
10.1 INTRODUCTION
10.2 NORTH AMERICA
10.2.1 US
10.2.2 CANADA
10.2.3 MEXICO
10.3 EUROPE
10.3.1 UK
10.3.2 GERMANY
10.3.3 FRANCE
10.3.4 REST OF EUROPE
10.4 ASIA PACIFIC
10.4.1 JAPAN
10.4.2 CHINA
10.4.3 INDIA
10.4.4 REST OF ASIA PACIFIC
10.5 REST OF THE WORLD
11 COMPETITIVE LANDSCAPE
11.1 OVERVIEW
11.2 MARKET PLAYER RANKING ANALYSIS, BY KEY PLAYER (2021)
11.3 COMPANY EVALUATION QUADRANT (OVERALL MARKET)
11.3.1 STARS
11.3.2 EMERGING LEADERS
11.3.3 PERVASIVE
11.3.4 PARTICIPANTS
11.4 COMPANY EVALUATION QUADRANT (EMERGING PLAYERS)
11.4.1 PROGRESSIVE COMPANIES
11.4.2 RESPONSIVE COMPANIES
11.4.3 STARTING BLOCKS
11.4.4 DYNAMIC COMPANIES
11.5 COMPETITIVE BENCHMARKING
11.5.1 OVERALL COMPANY FOOTPRINT
11.5.2 COMPANY PRODUCT FOOTPRINT
11.5.3 COMPANY REGION FOOTPRINT
11.6 COMPETITIVE SCENARIO
11.6.1 KEY SERVICE LAUNCHES
11.6.2 KEY PARTNERSHIPS, COLLABORATIONS, ALLIANCES, JOINT VENTURES AND AGREEMENTS
11.6.3 KEY ACQUISITIONS
11.6.4 KEY EXPANSIONS
12 COMPANY PROFILES
(Business Overview, Products Offered, Recent Developments, MnM View)*
12.1 IBM CORPORATION
12.2 EXSCIENTIA
12.3 SAAMA TECHNOLOGIES
12.4 UNLEARN.AI, INC.
12.5 BIOSYMETRICS
12.6 EURETOS
12.7 TRIALS.AI
12.8 INSILICO MEDICINE
12.9 ARDIGEN
12.10 PHARMASEAL
12.11 KONINKLIJKE PHILIPS N.V.,
12.12 INTEL
12.13 NUMERATE
12.14 AICURE, LLC.
12.15 ENVISAGENICS
12.16 NURITAS
12.17 BIOAGE LABS, INC.
12.18 SYMPHONY AI.
12.19 MEDIAN TECHNOLOGIES
12.20 INNOPLEXUS
12.21 ANTIDOTE TECHNOLOGIES, INC.
12.22 GNS HEALTHCARE
12.23 KONEKSA HEALTH
12.24 HALO HEALTH SYSTEMS
12.25 DEEP LENS AI
*Business Overview, Products Offered, Recent Developments, MnM View might not be captured in case of unlisted companies.
13 APPENDIX
Note:
This ToC is tentative and the segmentation given may change slightly depending on research findings.
Under the company profiles section, the list of companies provided is tentative and subject to change as research progresses, key 25 companies in the overall global market will be profiled. Details on business overview, products and services, financials, strategy & development might not be captured in case of unlisted companies.
Market information will be provided in terms of value (USD million). Information in terms of volume (installed base) will not be provided at any levels.
This market research study involved the extensive use of secondary sources, directories, and databases to identify and collect information useful for this technical, market-oriented, and financial study of the AI in clinical trials market. In-depth interviews were conducted with various primary respondents, including key industry participants, subject-matter experts (SMEs), C-level executives of key market players, and industry consultants, among other experts, to obtain and verify critical qualitative and quantitative information and to assess market prospects. The size of the AI in clinical trials market was estimated through various secondary research approaches and triangulated with inputs from primary research to arrive at the final market size.
Secondary Research
The secondary sources referred to for this research study include publications from government sources, such as WHO, AAAI, ACRO, CRS, CCRA, AICROS, EurAI, GCAAI. Secondary sources also include corporate and regulatory filings (such as annual reports, SEC filings, investor presentations, and financial statements); business magazines and research journals; press releases; and trade, business, and professional associations. Secondary data was collected and analyzed to arrive at the overall size of the global AI in clinical trials market, which was validated through primary research.
Primary Research
Extensive primary research was conducted after acquiring basic knowledge about the global AI in clinical trials market scenario through secondary research. Several primary interviews were conducted with market experts from both the demand side (Purchase manager, Heads of Artificial Intelligence, Machine Learning, Drug Discovery, clincal trials and Computational Molecular Design, research scientist) and supply-side (such as C-level and D-level executives, technology experts, product managers, marketing and sales managers, distributors, and channel partners, among others) across five major regions—North America, Europe, the Asia Pacific, Latin America, Middle East and the Africa. Approximately 70% and 30% of primary interviews were conducted with supply-side and demand-side participants, respectively. This primary data was collected through questionnaires, e-mails, online surveys, personal interviews, and telephonic interviews.
Note 1: Tiers are defined based on the total revenues of companies. As of 2021, Tier 1 = >USD 1 billion, Tier 2 = USD 500 million to USD 1 billion, and Tier 3 = To know about the assumptions considered for the study, download the pdf brochure Both top-down and bottom-up approaches were used to estimate and validate the total size of the global AI in clinical trials market. These methods were also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following: After arriving at the overall market size, from the market size estimation process explained above, the AI in clinical trials market was split into segments and subsegments. To complete the overall market engineering process and to arrive at the exact statistics for all segments and subsegments, the data triangulation and market breakdown procedures were employed, wherever applicable. The data was triangulated by studying various factors and trends from both the demand and supply sides in the Ai in clinical trials market With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Data Triangulation
Report Objectives
Available Customizations:
Company information
Growth opportunities and latent adjacency in Artificial Intelligence (AI) in Clinical Trials Market