Artificial Intelligence (AI) in Clinical Trials Market

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

Report Code: UC 5970 Jul, 2024, by marketsandmarkets.com

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

Artificial Intelligence in Clinical Trials Market

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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.

Artificial Intelligence (AI) in Clinical Trials Market by 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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Scope of the Report

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):

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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.

Artificial Intelligence (AI) in Clinical Trials Market Size, and Share

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:

  • The key players in the industry and markets have been identified through extensive secondary research.
  • The revenue generated from the sale of AI in clinical trials products by leading players has been determined through primary and secondary research.
  • All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.

Data Triangulation

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

Report Objectives

  • To define, describe, and forecast the global AI in clinical trials market based on offering, application, technology, end user, and region
  • To provide detailed information regarding the major factors (such as drivers, restraints, opportunities, and challenges) influencing the market growth
  • To strategically analyze micromarkets1 with respect to individual growth trends, prospects, and contributions to the overall AI in clinical trials market
  • To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders
  • To strategically analyze the market structure and profile the key players of the AI in clinical trials market and comprehensively analyze their core competencies2
  • To forecast the size of the market segments with respect to four regions, namely, North America, Europe, Asia Pacific, and the Rest of the World (Latin America and the Middle East & Africa)
  • To track and analyze competitive developments such as product launches, acquisitions, partnerships, agreements, and collaborations in the AI in clinical trials market during the forecast period

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