AI in Clinical Trials Market: Growth, Size, Share, and Trends

Report Code HIT 9229
Published in Dec, 2024, By MarketsandMarkets™
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AI in Clinical Trials Market by Function (Patient Recruitment, Site Optimization, Data Management, Quality, Regulatory), Phase (I, II, III), Indication (Cancer, CNS, CVS), Tool, End-User (Pharma/Biotech, CRO, Hospitals) & Region - Global Forecast to 2030

Overview

The global AI in clinical trials market, valued at US$1.20 billion in 2023, is forecasted to grow at a robust CAGR of 12.4%, reaching US$1.35 billion in 2024 and an impressive US$2.74 billion by 2029. The AI in clinical trials market is experiencing significant growth driven by increasing demand for patient-centred and patient-driven situated trials, where AI improves remote monitoring of patients along with improving retention and recruitment of patients. The increasing trend in personalized treatment is also a contributing factor to the growth of artificial intelligence in healthcare, as it facilitates the scrutinization of DNA information for treatment orientation. Moreover, the need for AI in the management of research-related data, and study data for the design of processes and making decisions with high precision has a positive impact on growth. Further, the growing elaborate nature of clinical data and its processing for trial purposes is dependent on AI advanced analytics to handle massive volumes of data and provide insights for trial progress.

AI in Clinical Trials Market

Attractive Opportunities in the AI in Clinical Trials Market

Asia Pacific

The Asia Pacific AI in clinical trials market is experiencing significant growth driven by rising R&D investments and a growing burden of chronic diseases. Budget constraints push healthcare providers to adopt cost-effective solutions, while the region's expanding biotechnology sector is further enhancing the demand for AI in clinical trials services.

Growth in precision medicine, partnerships between tech and pharma companies, expanding trials in emerging markets to drive the market significantly.

Emerging applications of AI in clinical trials in precision medicine, biopharmaceuticals, and toxicology are expected to provide lucrative opportunities for market players.

The North America market is expected to grow at a substantial growth rate during the forecast period.

Integration complexity with traditional frameworks, lack of standardization across platforms poses a challenge for collaboration and scalability, limiting market growth opportunities.

Global AI in Clinical Trials Market Dynamics

DRIVER: Increasing Demand for Clinical Trials

Clinical studies are the backbone of drug development and help pharmaceutical and biotechnology companies launch new products. Over the past decade, demand for clinical studies globally has followed a sharp rise; according to current medical needs, the need to come up with new therapeutics has also surged. According to ClinicalTrials.gov, as of August 2023, nearly 461,614 clinical studies were recorded worldwide, showing a great increase from 5,475 in the year 2000.

An increased number of clinical trials in the global market will stimulate clinical trials in that region, hence leading to growth in the market. The World Health Organization's clinical trials registry in December 2022 reported that the most clinical trials happening were in North America and Europe. The numbers of clinical trials performed is the highest in the US with ~23%, followed by China, Japan, India, and Germany. The country's very well-established pharmaceutical and biotechnology industry in the US also accounts for the success in leading the race in this area along with the continually increasing R&D expenditure and the large numbers of CROS.

RESTRAINT: Shortage Of Skilled Professionals for Clinical Trials

CROS faces difficulties in attracting and retaining highly skilled professionals since they offer the same services as the pharmaceutical and biotechnology companies and academic & research institutions to qualified and experienced scientists. These aspects will force the firms to provide more compensations and other fringe benefits which tend to influence finances and results, mainly for small-scale analytical testing providers. This shortage of skilled professionals may hinder the adoption of new technologies and methodologies and restrain the growth of the clinical trials market in the years to come. According to the Global Workforce Intelligence (GWI) Project, by 2025, there will be an astronomical demand-supply gap of 2.1 million healthcare workers, with one in three roles going unfilled. CareerBuilder estimates that, according to September 2022 statistics, only 5.7 million people were available for recruitment in the US, with 6.6 million clinical research positions available. Furthermore, there are seven positions listed for every CRC looking for employment. According to the Association of Clinical Research Organizations, an acute shortage has been noted specifically in the areas of clinical trial associates (CTA) and clinical research associates (CRA). This decade-long crisis has been mounting because the training of graduates is not appropriate by pharmaceutical companies and CROs in skills to meet the requirements of research from the industry.

 

OPPORTUNITY: Rising Demand for Specialized Testing Services

Traditionally, pharmaceutical, biotechnology, and medical device businesses kept early-phase development projects and problem-solving activities in-house, outsourcing primarily late-phase drug development and routine processes. However, in recent years, an increasing number of companies have partnered earlier in the drug development process to improve efficiency.

Companies are increasingly outsourcing specialised testing services such as liquid chromatography-mass spectrometry (LC/MS), RNA sequencing, gene expression analysis, wet chemistry analysis of compendia raw materials, and trace metal analysis using inductively coupled mass spectrometry (ICP-MS) much earlier in the API process development cycle. These specialised services are mostly used for impurity structural elucidation, solvent removal (class I and II), hazard analysis, column chromatography removal, and efforts to reduce overall costs and improve process efficiency. The tests necessitate high-end equipment and trained technicians. Pharmaceutical and biotechnology businesses want to outsource their specialised testing services to CROS in order to save money on equipment and labour. For example, firms such as Pfizer, Merck, and Roche have lowered their in-house testing services in order to fuel their R&D pipelines and fulfil the growing demand for new drug compounds in a variety of therapeutic areas.

Many pharmaceutical and biotechnology businesses are focused on diversifying their product portfolios and creating novel small and big molecules. Companies are developing combination treatments, delivery devices, and reformulated or re-engineered medications to address unmet requirements. The clinical research sector works closely with clients. It has more technical depth to grasp product intricacies and propose new creative solutions to accelerate the delivery of critical clinical medicines. Other reasons why large organisations outsource analytical testing include cost savings, increased efficiency, and ideal personnel. Thus, as the therapeutic pipeline becomes more complicated, pharmaceutical companies are choosing to outsource services to CROS in order to obtain access to novel technologies that speed compound development along the product pipeline.

CHALLENGES: Concerns Regarding Patient Privacy

Data integration highlights the growing issue of patient privacy; with an increasing number of databases among research institutions, CROS, partners, and software businesses, the dangers of data breaches increase. According to the 2009 Health Information Technology for Economic and Clinical Health Act (HITECH Act), covered entities are required to secure individual health records and other identifiable health information by acquiring sufficient privacy safeguards. As a result, applying electronics tools to patient databases raises worries about the privacy of patient records, posing another significant barrier for pharmaceutical companies in complying with privacy policies while employing AI in clinical trials software.

Global AI in Clinical Trials Market Ecosystem Analysis

The AI in clinical trials ecosystem consists of the players such as technology providers, pharma, CROs, regulators, data providers, healthcare institutions and patient advocacy organizations. Technology providers like Medidata have developed AI software to help with analysis of data and patient recruitment respectively, while CROs like IQVIA implement these tools in the conduct of studies. Pharmaceutical and biotechnology companies are also exploring how AI can optimize the drug development process, although outcomes are regulated by authorities such as the FDA to make sure they are legal and ethical. Data providers like Flatiron Health have important datasets, while healthcare organizations, and universities provide their research talent. Patient advocates promote justice and tackle discrimination which allows for the existence of a productive and growth oriented clinical AI innovation ecosystem.

AI in Clinical Trials Market
 

By function, the patient recruitment segment accounted for the largest share of the AI in clinical trials market in 2023.

By function, the AI in clinical trials market is segmented into patient recruitment, trial design optimization, data management and quality control, adverse event prediction & detection, drug repurposing and regulatory compliance. Patient recruitment accounted for the largest share in the AI in clinical trials market, by function. One of the most significant difficulties to performing clinical research is recruiting and retaining competent patients, with about 30% of trials failing due to recruitment issues. AI-guided systems may quickly filter through numerous elements such as EHRs, social networking sites, and databases for genes and identify the best individuals for a certain study, improving recruiting accuracy and speed. As a result, making significant modifications to recruitment timetables along the way helps to streamline the entire trial process, lowering costs and even resources. Furthermore, the fact that AI promotes patient participation in the treatment process through approaches such as personalised messaging and predictive analytics lowers dropout rates, increasing the trial's chances of success. The demand for patient recruitment-focused AI-based development is significant in both big pharma businesses and macro-driven factors, which explains why there is a good likelihood that patient recruitment will be an investment emphasis, resulting in a market share of AI in clinical trials.

Cell & gene therapy segment to register highest growth rate during the forecast period in the AI in clinical trials market, by application

Based on application, the AI in clinical trials market is segmented into biomarkers, cell & gene therapy, regenerative medicine, and medical devices & diagnostics. Cell & gene therapy segment to register highest growth rate during the forecast period. This is one of the sectors that have advanced even further the personalization of medicine, and this means that therapy will mostly take into account an individual’s genetic makeup, something that thrives on a lot of data and insights specific to the patient. The use of technology such as AI however makes it easier to manage and analyze the genetic and clinical data, improves the design of the trial, and also helps in the selection of patients thereby facilitating the advancement of cell and gene therapy. Several factors have also fostered investment in artificial intelligence in these clinical trials including the regulatory inclination towards precision medicine and the massive need for drugs aimed at the rare diseases. With respect to increasing effectiveness, safety, and correctness, the contribution of AI solutions in governing the straightforward issues regarding cell and gene therapies is sufficient to advocate for rapid growth of this segment through the adoption of AI.

North America accounted for the largest share of the AI in clincal trials market in 2023.

The AI in clinical trials market is segmented into North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa. In 2023, North America accounted for the highest share of the AI in clinical trials market. Numerous factors have contributed to North America’s largest market share in the AI in clinical trials. These includes the advanced technology of the region, high expenditure on health care research and development as well as the existing supportive clinical research environment. The market landscape in the United States is characterized by numerous leading pharmaceutical and biotechnology brands such as Pfizer, Johnson & Johnson, and Amgen which pour in resources into AI tool development for drug synthesis, shortening turnarounds in drug designs, and clinical trials. Also, North America is recognized as an epicentre of AI technology with companies like IBM, Google and Microsoft working on development of healthcare-based AI systems.

The region’s effective health care framework, coupled with the high level of electronic health records (EHR) embrace makes it easy for AI systems to aid in recruitment of subjects as well as doing analysis of data collected, hence, creating a very good base for carrying out clinical trials geared by AI technologies. In addition, regulators in North America such as the Food and Drug Administration have been proactive on the development of AI and other technologies in clinical trials by providing recommendations and guidance on the use of these tools, which helps to promote usage by making sure the relevant sector is regulated and patients are safe.

HIGHEST CAGR MARKET IN 2023
US FASTEST GROWING MARKET IN THE REGION
AI in Clinical Trials Market

Recent Developments of AI in Clinical Trials Market

  • In November 2024, Bioforum (Israel) and Medidata (France) took their collaboration a step further providing Bioforum's clientele in the field of biotechnology with greater access to Medidata's Al-based technologies. Apart from Medidata Rave EDC and RTSM, Bioforum shall employ Medidata Clinical Data Studio and Medidata eConsent in order to enhance data transfer, quality and regulation of clinical trials.
  • In April 2024, IQVIA (US) partnered with Salesforce (US) to accelerate the life sciences cloud development for customer engagement.
  • In February 2024, Saama (US) collaborated with Pfizer Inc. (US) to expand multi-year agreement to scale Smart Data Quality (SDQ), leveraging AI to streamline and accelerate data review processes across Pfizer’s global clinical research portfolio.
  • In October 2023, Saama (US) signed a multiyear agreement with AstraZeneca (UK) to streamline clinical data management and medical review processes using Saama's Al-enabled technology platform. The agreement was designed to hasten the process of drug development incorporating Smart Data Quality (SDQ), Data Hub and Patient Insights solutions thereby facilitating faster data lock and efficient reviews of the data.

Key Market Players

KEY PLAYERS IN THE AI IN CLINICAL TRIALS MARKET INCLUDE

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Scope of the Report

Report Metric Details
Market size available for years 2022-2030
Base Year Considered 2023
Forecast period 2024-2030
Forecast units Million/Billion (USD) include
Segments covered Offering, Function, Phase, Deployment Mode, Indication, Technology, Application, End User
Geographies covered North America, Europe, Asia Pacific, Latin America, and Middle East Africa.

 

Key Questions Addressed by the Report

What are the major market players covered in the report?
The key players in the AI in clinical trials market are IQVIA Inc. (US), Dassault Systèmes (Medidata) (France), Tempus AI, Inc. (US), Insilico Medicine (US), ConcertAI (US), AiCure (US), PathAI, Inc. (US), among others.
Define AI in clinical trials market.
The AI in clinical trials market refers to the utilization of artificial intelligence-based tools to improve various phases of clinical research, such as trial development, patient enrolment, data management, and therapeutic monitoring. AI automates data collection, enhances patient matching efficiency, and improves trial outcome prediction, reducing costs and timelines. It allows clearer understanding of large datasets, such as patient charts or genomic information, which aids in decision-making. The integration of AI technologies in clinical trials improves efficiency, reduces waiting time, and increases success rates in drug development.
Which region is expected to have the largest market share in the AI in clinical trials market?
North America is expected to hold the largest share of the AI in clinical trials market during the forecast period.
Which end-user segments have been included in the AI in clinical trials market report?
The report contains the following end-user segments: - Pharmaceutical & Biotechnology Companies - Research Institutes & Labs - Healthcare Providers - Contract Research Organizations (CROs) - Medical Device Manufacturers
How big is the global AI in clinical trials market today?
The global AI in clinical trials market is projected to grow from USD 1.35 billion in 2024 to USD 2.74 billion by 2030, at a CAGR of 12.4% from 2024 to 2030.

 

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Table of Contents

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TITLE
PAGE NO
INTRODUCTION
1
RESEARCH METHODOLOGY
15
EXECUTIVE SUMMARY
27
PREMIUM INSIGHTS
56
MARKET OVERVIEW
78
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    KEY MARKET DRIVERS
    MARKET RESTRAINTS
    MARKET OPPORTUNITIES
    MARKET CHALLENGES
  • 5.3 INDUSTRY TRENDS
  • 5.4 ECOSYSTEM ANALYSIS
  • 5.5 CASE STUDY ANALYSIS
  • 5.6 VALUE CHAIN ANALYSIS
  • 5.7 PORTER'S FIVE FORCES ANALYSIS
    BARGAINING POWER OF SUPPLIERS
    BARGAINING POWER OF BUYERS
    THREAT OF SUBSTITUTES
    THREAT OF NEW ENTRANTS
    INTENSITY OF COMPETITIVE RIVALRY
  • 5.8 REGULATORY ANALYSIS
    REGULATORY LANDSCAPE
    - North America
    - Europe
    - Asia Pacific
    - Latin America
    - Middle East & Africa
    REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.9 PATENT ANALYSIS
    PATENT PUBLICATION TRENDS FOR AI IN CLINICAL TRIALS
    JURISDICTION AND TOP APPLICANT ANALYSIS
  • 5.10 TECHNOLOGY ANALYSIS
    KEY TECHNOLOGIES
    - MACHINE LEARNING (ML)
    - NATURAL LANGUAGE PROCESSING (NLP)
    - COMPUTER VISION
    COMPLEMENTARY TECHNOLOGIES
    - INTERNET OF THINGS (IOT)
    - CLOUD COMPUTING
    ADJACENT TECHNOLOGIES
    - ADVANCED GENOMICS
  • 5.11 INDUSTRY TRENDS
  • 5.12 PRICING ANALYSIS (QUALITATIVE)
    INDICATIVE PRICE OF KEY OFFERINGS, 2023
    INDICATIVE PRICE OF KEY OFFERINGS, BY REGION, 2023
  • 5.13 KEY CONFERENCES & EVENTS, 2024–2025
  • 5.14 KEY STAKEHOLDERS & BUYING CRITERIA
    KEY STAKEHOLDERS IN THE BUYING PROCESS
    BUYING CRITERIA
  • 5.15 TRENDS & DISRUPTIONS IMPACTING CUSTOMERS’ BUSINESSES
  • 5.16 END-USER ANALYSIS
    UNMET NEEDS
    END-USER EXPECTATIONS
  • 5.17 AI IN CLINICAL TRIALS MARKET: INVESTMENT & FUNDING SCENARIO
  • 5.18 AI IN CLINICAL TRIALS MARKET: BUSINESS MODEL
  • 5.19 IMPACT OF AI/GEN AI ON AI IN CLINICAL TRIALS MARKET
AI IN CLINICAL TRIALS MARKET, BY OFFERING
97
  • 6.1 INTRODUCTION
  • 6.2 END-TO-END SOLUTIONS
  • 6.3 NICHE SOLUTIONS
  • 6.4 TECHNOLOGY PROVIDERS
  • 6.5 SERVICES
    CONSULTING SERVICES
    IMPLEMENTATION SERVICES & ONGOING IT SUPPORT
    TRAINING & EDUCATION SERVICES
    POST-SALES & MAINTENANCE SERVICES
AI IN CLINICAL TRIALS MARKET, BY FUNCTION
115
  • 7.1 INTRODUCTION
  • 7.2 PATIENT RECRUITMENT
    PATIENT IDENTIFICATION & SCREENING
    PATIENT ENGAGEMENT & RETENTION
    SITE OPTIMIZATION
  • 7.3 TRIAL DESIGN OPTIMIZATION
    WORKFLOW MANAGEMENT
    PREDICTIVE MODELING
    RISK MANAGEMENT
  • 7.4 DATA MANAGEMENT & QUALITY CONTROL
  • 7.5 ADVERSE EVENT PREDICTION & DETECTION
  • 7.6 DRUG REPURPOSING
  • 7.7 REGULATORY COMPLIANCE
AI IN CLINICAL TRIALS MARKET, BY PHASE
135
  • 8.1 PHASE I
  • 8.2 PHASE II
  • 8.3 PHASE III
  • 8.4 PHASE IV
AI IN CLINICAL TRIALS MARKET, BY DEPLOYMENT MODE
148
  • 9.1 INTRODUCTION
  • 9.2 CLOUD-BASED SOLUTIONS
    PUBLIC CLOUD
    PRIVATE CLOUD
    MULTI-CLOUD
    HYBRID CLOUD
  • 9.3 ON-PREMISE SOLUTIONS
AI IN CLINICAL TRIALS MARKET, BY INDICATION
155
  • 10.1 INTRODUCTION
  • 10.2 ONCOLOGY
  • 10.3 NEUROLOGICAL DISEASES
  • 10.4 CARDIOVASCULAR DISEASES
  • 10.5 METABOLIC DISEASES
  • 10.6 INFECTIOUS DISEASES
  • 10.7 IMMUNOLOGY DISEASES
  • 10.8 OTHERS (GASTROINTESTINAL, RESPIRATORY & REPRODUCTIVE)
AI IN CLINICAL TRIALS MARKET, BY TECHNOLOGY
167
  • 11.1 INTRODUCTION
  • 11.2 MACHINE LEARNING
    DEEP LEARNING
    SUPERVISED LEARNING
    UNSUPERVISED LEARNING
    REINFORCEMENT LEARNING
    OTHER ML TECHNOLOGIES (SEMI-SUPERVISED LEARNING, & SELF-SUPERVISED LEARNING)
  • 11.3 NLP
  • 11.4 COMPUTER VISION
  • 11.5 ROBOTIC PROCESS AUTOMATION
  • 11.6 OTHERS
AI IN CLINICAL TRIALS MARKET, BY APPLICATION
170
  • 12.1 INTRODUCTION
  • 12.2 BIOMARKERS
  • 12.3 CELL & GENE THERAPY
  • 12.4 REGENERATIVE MEDICINE
  • 12.5 MEDICAL DEVICES & DIAGNOSTICS
AI IN CLINICAL TRIALS MARKET, BY END USER
172
  • 13.1 INTRODUCTION
  • 13.2 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES
  • 13.3 RESEARCH INSTITUTES & LABS
  • 13.4 HEALTHCARE PROVIDERS
  • 13.5 CONTRACT RESEARCH ORGANIZATIONS (CROS)
  • 13.6 MEDICAL DEVICE MANUFACTURERS
AI IN CLINICAL TRIALS MARKET, BY REGION
176
  • 14.1 INTRODUCTION
  • 14.2 NORTH AMERICA
    MACROECONOMIC OUTLOOK FOR NORTH AMERICA
    US
    CANADA
  • 14.3 EUROPE
    MACROECONOMIC OUTLOOK FOR EUROPE
    GERMANY
    UK
    FRANCE
    ITALY
    SPAIN
    REST OF EUROPE
  • 14.4 ASIA PACIFIC
    MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
    JAPAN
    CHINA
    INDIA
    SOUTH KOREA
    REST OF ASIA PACIFIC
  • 14.5 LATIN AMERICA
    MACROECONOMIC OUTLOOK FOR LATIN AMERICA
    BRAZIL
    MEXICO
    REST OF LATIN AMERICA
  • 14.6 MIDDLE EAST & AFRICA
    MACROECONOMIC OUTLOOK FOR MIDDLE EAST & AFRICA
    GCC COUNTRIES
    REST OF MIDDLE EAST & AFRICA
COMPETITIVE LANDSCAPE
178
  • 15.1 INTRODUCTION
  • 15.2 STRATEGIES ADOPTED BY KEY PLAYERS
  • 15.3 REVENUE ANALYSIS OF TOP MARKET PLAYERS
  • 15.4 MARKET SHARE ANALYSIS
  • 15.5 BRAND/PRODUCT COMPARATIVE ANALYSIS
  • 15.6 VALUATION AND FINANCIAL METRICS OF KEY AI IN CLINICAL TRIALS VENDORS
  • 15.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
    STARS
    EMERGING LEADERS
    PERVASIVE PLAYERS
    PARTICIPANTS
    COMPANY FOOTPRINT: KEY PLAYERS, 2023
    - Company footprint
    - Offering footprint
    - Application footprint
    - End-user footprint
    - Region footprint
  • 15.8 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023
    PROGRESSIVE COMPANIES
    RESPONSIVE COMPANIES
    DYNAMIC COMPANIES
    STARTING BLOCKS
    COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    - DETAILED LIST OF STARTUPS/SMES
    - COMPETITIVE BENCHMARKING OF KEY STARTUPS/SMES
  • 15.9 COMPANY VALUATION & FINANCIAL METRICS
  • 15.10 BRAND/PRODUCT COMPARISON
  • 15.11 COMPETITIVE SCENARIO
    PRODUCT LAUNCHES & UPGRADES
    DEALS
    EXPANSIONS
COMPANY PROFILES
179
  • 16.1 KEY PLAYERS
    IQVIA INC.
    SAAMA.
    DASSAULT SYSTÈMES (MEDIDATA)
    PHESI
    PATHAL, INC.
    UNLEARN.AI, INC.
    DEEP6.AI
    MICROSOFT
    IBM
    NVIDIA CORPORATION
    INSILICO MEDICINE
    CONCERTAL.
    AICURE.
    MEDIAN TECHNOLOGIES.
    LANTERN PHARMA INC.
    CITELINE, A NORSTELLA COMPANY
    TEMPUS AI, INC.
    TRINETX, LLC
    OTHER PLAYERS
    REVIVEMED INC.
    EURETOS.
    VERISIM LIFE
    TRIOMICS
    ARDIGEN
    QUANTHEALTH LTD.
    DEEP GENOMICS
APPENDIX
180
  • 17.1 DISCUSSION GUIDE
  • 17.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
  • 17.3 CUSTOMIZATION OPTIONS
  • 17.4 RELATED REPORTS
  • 17.5 AUTHOR DETAILS

The study involved significant activities to estimate the current size of the AI in clinical trials market. Exhaustive secondary research was done to collect information on the AI in clinical trials market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain using primary research. Different approaches, such as top-down and bottom-up, were employed to estimate the total market size. After that, the market breakup and data triangulation procedures were used to estimate the market size of the segments and subsegments of the AI in clinical trials market.

Secondary Research

This research study involved the wide use of secondary sources, directories, and databases such as Dun & Bradstreet, Bloomberg Businessweek, and Factiva; white papers, annual reports, and companies’ house documents; investor presentations; and the SEC filings of companies. The market for the companies offering AI in clinical trials solutions is arrived at by secondary data available through paid and unpaid sources, analyzing the product portfolios of the major companies in the ecosystem, and rating the companies by their performance and quality. Various sources were referred to in the secondary research process to identify and collect information for this study. The secondary sources include annual reports, press releases, investor presentations of companies, white papers, journals, certified publications, and articles from recognized authors, directories, and databases.

Various secondary sources were referred to in the secondary research process to identify and collect information related to the study. These sources included annual reports, press releases, investor presentations of AI in clinical trials vendors, forums, certified publications, and whitepapers. The secondary research was used to obtain critical information on the industry’s value chain, the total pool of key players, market classification, and segmentation from the market and technology-oriented perspectives.

Primary Research

In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side included industry experts, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), marketing directors, technology and innovation directors, and related key executives from various key companies and organizations operating in the AI in clinical trials market.

After the complete market engineering (calculations for market statistics, market breakdown, market size estimations, market forecasting, and data triangulation), extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. Primary research was also undertaken to identify the segmentation types, industry trends, competitive landscape of AI in clinical trials solutions offered by various market players, and key market dynamics, such as drivers, restraints, opportunities, challenges, industry trends, and key player strategies.

In the complete market engineering process, the top-down and bottom-up approaches and several data triangulation methods were extensively used to perform the market estimation and market forecasting for the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was performed on the complete market engineering process to list the key information/insights throughout the report.

Breakdown of Primary Participants:

AI in Clinical Trials Market

Note 1: Others include sales managers, marketing managers, and product managers.

Note 2: Tiers of companies are defined based on their total revenues in 2023. Tier 1 = >USD 1 billion, Tier 2 = USD 500 million to USD 1 billion, and Tier 3 = < USD 500 million.

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Both top-down and bottom-up approaches were used to estimate and validate the total size of the 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 industry’s supply chain and market size, in terms of value, have been determined through primary and secondary research processes.
  • All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.
AI in Clinical Trials Market

Data Triangulation

After arriving at the overall market size using the market size estimation processes explained above, the market was split into several segments and subsegments. The data triangulation and market breakup procedures were employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment. The data was triangulated by studying various factors and trends from both the demand and supply sides.

Market Definition

The AI in clinical trials market refers to the utilization of artificial intelligence-based tools to improve the different phases as well as steps of clinical research process activity such as trial development, enrolment of patients, data management and analysis and therapeutic monitoring. Al assists in accomplishing such tasks by automating the collection of data, enhancing the efficiency of patient matching and improving prediction of outcomes of trials which in turn helps in reducing the timeline and cost associated with these processes. This allows for a clearer understanding of large amounts of information, for example, within patient charts or genome information, so that the appropriate information is available for making decisions for particular trials. Clinical trials become highly efficient, cheaper, and more precise with the integration of Al technologies into the processes which significantly helps in drug development reducing the waiting time and the success rate improves. With more and more applications of AI in the healthcare sector, this healthcare services market is projected to grow as there will be a rise in the need for improved clinical research within a short turnaround time.

Stakeholders

  • Pharmaceutical and Biotechnology Companies
  • Contract Research Organizations (CROs)
  • Technology and AI Companies
  • Regulatory Authorities
  • Hospitals and Healthcare Providers
  • Patients and Patient Advocacy Groups
  • Clinical Trial Investigators and Site Coordinators
  • Data Management and Analytics Firms
  • Academic Institutions and Research Organizations
  • Investors and Venture Capital Firms
  • Clinical Trial Software Providers
  • Ethics Committees and Institutional Review Boards (IRBs)
  • Insurance Companies

Report Objectives

  • To define, describe, and forecast the AI in clinical trials market based on offering, function, phase, deployment mode, indication, technology, application, end user, and region.
  • To provide detailed information about the major factors (drivers, opportunities, restraints, and challenges) influencing the growth of the market
  • To analyze opportunities for stakeholders by identifying the high-growth segments of the market
  • To forecast the size of the market segments with respect to five main regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
  • To analyze subsegments of the market with respect to individual growth trends, prospects, and contributions to the overall market
  • To profile the key players and comprehensively analyze their market sizes and core competencies.
  • To track and analyze competitive developments such as acquisitions, collaborations, agreements, mergers, product launches & updates, partnerships, expansions, and other recent developments in the market globally.

 

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