Analysis of the Global AI in Clinical Trials Industry, 2023 to 2035 - Product/Technology Utilization and Integration Agreements Lead the Way in Partnerships

2023-08-25
PRNewswire
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DUBLIN, Aug. 25, 2023 /PRNewswire/ -- The "Global AI in Clinical Trials Market: Trends and Forecasts 2023-2035" report has been added to
ResearchAndMarkets.com's offering.
The global AI in clinical trials market is estimated to be worth $ 1.4 billion in 2023 and expected to grow at compounded annual growth rate (CAGR) of 16% during the forecast period.
The process of successfully developing a novel therapeutic intervention is both time and cost intensive. In fact, it is estimated that a drug requires around 10 years and over $ 2.5 billion capital investment, before reaching the market. In this process, clinical trials play a crucial role for assessing the drug's efficacy and safety in humans. These trials account for nearly 50% of the time and capital expenditure during drug development. However, sponsors face financial burdens and significant delays in marketing drugs due to unsuccessful clinical trials.
Over the past few decades, the success rate of a drug candidate advancing the clinical trials to obtaining marketing approval has remained relatively constant at approximately 10% - 20%. This can be attributed to the factors contributing to clinical stage intervention failure, including inadequate study design, incomplete patient recruitment, improper subject stratification and high rate of clinical trial participant attrition.
In order to overcome these challenges and streamline the clinical trial processes, stakeholders in the pharmaceutical industry are exploring innovative solutions and strategies. One such innovative strategy involves integrating AI in drug development, which has the potential to revolutionize traditional methods, particularly in clinical trials. It is worth noting that artificial intelligence in clinical trials can help integrate and analyze large volumes of data, enabling trial sponsors to optimize future research initiatives. Additionally, by addressing issues related to trial design, patient recruitment and retention, site selection, data interpretation, and treatment evaluation, AI has the potential to enhance and refine the entire process of clinical drug development.
Moreover, in the first nine months of 2021, more than $20 billion was invested into artificial intelligence companies focused on healthcare, exceeding the prior investment, which was around $15 billion in 2020. Therefore, with the rising interest of investors in this field, we anticipate the AI in clinical trials market to witness healthy growth during the forecast period.
Key Market Insights
The report features an extensive study of the current market landscape, market size and future opportunities associated with the AI in clinical trials market, during the given forecast period. Further, the report highlights the efforts of several stakeholders engaged in this rapidly emerging segment of the pharmaceutical industry. Key takeaways of the AI in clinical trials market report are briefly discussed below.
Benefits and Growing Demand for Artificial Intelligence Solutions for Patient Recruitment and Clinical Data Analysis
AI solutions have emerged as a promising tool in the drug development process. These AI tools help companies improve the accuracy and efficiency of testing, accelerate drug development and optimize clinical trial outcomes. In addition, leveraging AI software in clinical trials helps increasing patient recruitment and retention, reduces trial time and cost, and provides more accurate clinical data analysis, personalized medicine, trial design and real-time patient monitoring.
It is worth highlighting that the ability of AI to automate and streamline labor-intensive tasks, improve decision-making processes, and identify patterns and trends in complex datasets has garnered significant attention and interest from stakeholders in the pharmaceutical industry. In May 2023, US based Owkin received letter of support from the European Medicines Agency (EMA) for the use of proprietary deep learning models for oncology clinical trial analysis; the company believes that this can reduce the clinical trial failure rates in randomized clinical trial. Further several artificial intelligence companies have developed AI-powered platforms that optimize patient identification for clinical trials. Additionally, AI algorithms can be trained to analyze large amounts of data in electronic health records to identify eligible participants.
Owing to these applications and recognition of the immense potential of AI by researchers and sponsors, the demand for AI clinical trials is likely to continue to grow and transform the landscape of drug development by improving patient outcomes in clinical trials.
Current Market Landscape of AI in Clinical Trials: AI Software and Service Providers
The AI in clinical trials market landscape features a mix of large, mid-sized and small companies. Currently, around 130 players have the required expertise to offer various software and services to streamline clinical studies. Notably, at present, around 80% of these AI in clinical trials software and service providers are focusing on leveraging machine learning and deep learning algorithms, as they minimize data-based errors by accessing various data points simultaneously. Recent developments in this field indicate that the artificial intelligence companies in clinical trials are upgrading their capabilities to accommodate the current and anticipated demand for these software and services.
Partnership and Collaboration Trends in the AI in Clinical Trials Market
In recent years, several artificial intelligence companies have inked partnerships related to AI in clinical trials domain with other industry / non-industry players. It is worth highlighting that, since 2018, a significant number of strategic partnerships have been inked in the AI in clinical trials industry. It is worth highlighting that product / technology utilization and integration agreements are the most common types of partnerships inked by stakeholders in the AI clinical trials field.
Owing to several advantages of artificial intelligence in clinical trials, stakeholders are acquiring other industry players offering AI solutions / AI software for different clinical trial applications in order to expand their capabilities and build a comprehensive product / service portfolio. In February 2023, ZS acquired Trials.ai, an intelligent study design company, to enhance its end-to-end solutions to reimagine study design for its clients. In addition, several big pharma companies, such as Bristol Myers Squibb, GlaxoSmithKline (GSK), Johnson & Johnson, Merck, Pfizer and Roche, have also taken partnership initiatives related to AI in clinical trials, indicating the promise and benefits that AI technology holds in clinical trials.
Key Trends in the AI in Clinical Trials Market
In the past six years, around 600 completed / ongoing clinical trials utilized AI tools and technologies for evaluating drugs / therapies for different therapeutic areas, indicating the substantial efforts made by researchers engaged in this domain. Further, most of the clinical studies were designed for the purpose of diagnostics and treatment. It is worth noting that the University of California, the National Institute of Allergy and Infectious DiseasesInfectious Diseases, and Mayo Clinic are among the most active sponsors of completed / ongoing clinical trials involving AI solutions.
Rise in Investment in AI in Clinical Trials Market
The heightened interest in the AI in clinical trials market can be validated by the fact that, in the last five years, close to $2.5 billion has been invested in companies engaged in providing AI software and services for clinical trials by several investors based across the globe. The majority of the funds have been raised through venture rounds, followed by seed financing rounds. In addition, several big pharma players, such as Bristol Myers Squibb, Merck, Novartis, Pfizer and Sanofi have also invested in AI software and service providers for clinical trials. In June 2021, Antidote Technologies raised $23 million to expand its digital patient engagement programs and clinical trial recruitment services.
AI in Clinical Trials Market Size
Driven by the rising demand for artificial intelligence in clinical trials, lucrative opportunities are expected to emerge for players offering AI technology for clinical studies. The global market for AI in clinical trials is anticipated to grow at a significant pace, with a CAGR of 16% during the forecast period. Among the therapeutic areas for which AI tools are leveraged in clinical trials, oncological disorders are most likely to adopt these AI solutions for streamlining processes, such as patient recruitment and retention, trial design, site selection, clinical data analysis, patient monitoring and personalized treatment. In terms of end-users, biotechnology and pharmaceutical companies are likely to hold the majority share (75%) of the AI in clinical trials market.
Key Artificial Intelligence Companies Supporting Clinical Trials
Examples of the key companies engaged in the AI in clinical trials domain (the complete list of players is available in the full report) include (in alphabetic order) Acclinate, AiCure, Aidar Health, Aitia, A.I. VALI, Ancora.ai, Antidote Technologies, Beacon Biosignals, BUDDI.AI, ConcertAI, Curify, Deep 6 AI, ICON, Innoplexus, Massive Bio, Median Technologies, Novadiscovery, Owkin, PHASTAR, SiteRx and Viz.ai. This market report also includes an easily searchable excel database of all the AI software / AI solutions and service providers for clinical trials worldwide.
Scope of the Report
The market report presents an in-depth analysis of the various firms / organizations that are engaged in this market, across different segments. The research report presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this market, across different geographies. The opinions and insights presented in the report were influenced by discussions held with stakeholders in this industry.
The report also features detailed transcripts of interviews held with various industry stakeholders:
Danielle Ralic (Co-Founder, Chief Executive Officer and Chief Technology Officer, Ancora.ai)
Wout Brusselaers (Founder and Chief Executive Officer, Deep 6 AI)
Dimitrios Skaltsas (Co-Founder and Executive Director, Intelligencia)
R. A. Bavasso (Founder and Chief Executive Officer, nQ Medical)
Grazia Mohren (Head of Marketing), Michael Shipton (Chief Commercial Officer), Darcy Forman (Chief Delivery Officer), Troy Bryenton (Chief Technology Officer, Science 37)
All actual figures have been sourced and analyzed from publicly available information forums and primary research discussions.
Key Topics Covered
1. PREFACE
1.1. Introduction
1.2. Key Market Insights
1.3. Scope of the Report
1.4. Research Methodology
1.5. Frequently Asked Questions
1.6. Chapter Outlines
2. EXECUTIVE SUMMARY
3. INTRODUCTION
3.1. Chapter Overview
3.2. Overview of Artificial Intelligence (AI)
3.3. Subfields of AI
3.4. Applications of AI in Healthcare
3.4.1. Drug Discovery
3.4.2. Drug Manufacturing
3.4.3. Marketing
3.4.4. Diagnosis and Treatment
3.4.5. Clinical Trials
3.5. Applications of AI in Clinical Trials
3.6. Challenges Associated with the Adoption of AI
3.7. Future Perspective
4. MARKET LANDSCAPE
4.1. Chapter Overview
4.2. AI in Clinical Trials: AI Software and Service Providers Landscape
4.2.1. Analysis by Year of Establishment
4.2.2. Analysis by Company Size
4.2.3. Analysis by Location of Headquarters
4.2.4. Analysis by Company Size and Location of Headquarters (Region)
4.2.5. Analysis by Key Offering(s)
4.2.6. Analysis by Business Model(s)
4.2.7. Analysis by Deployment Option(s)
4.2.8. Analysis by Type of AI Technology
4.2.9. Analysis by Application Area(s)
4.2.10. Analysis by Potential End-user(s)
5. COMPANY PROFILES
5.1. Chapter Overview
5.2. AiCure
5.3. Antidote Technologies
5.4. Deep 6 AI
5.5. Innoplexus
5.6. IQVIA
5.8. Medidata
5.10. Phesi
5.12. Signant Health
5.13. Trials.ai
6. CLINICAL TRIAL ANALYSIS
6.1. Chapter Overview
6.2. Scope and Methodology
6.3. AI in Clinical Trials
6.3.1. Analysis by Trial Registration Year
6.3.2. Analysis by Number of Patients Enrolled
6.3.3. Analysis by Trial Phase
6.3.4. Analysis by Trial Status
6.3.5. Analysis by Trial Registration Year and Status
6.3.6. Analysis by Type of Sponsor
6.3.7. Analysis by Patient Gender
6.3.8. Analysis by Patient Age
6.3.9. Word Cloud Analysis: Emerging Focus Areas
6.3.10. Analysis by Target Therapeutic Area
6.3.11. Analysis by Study Design
6.3.12. Most Active Players: Analysis by Number of Clinical Trials
6.3.13. Analysis of Clinical Trials by Geography
6.3.14. Analysis of Clinical Trials by Geography and Trial Status
6.3.15. Analysis of Patients Enrolled by Geography and Trial Registration Year
6.3.16. Analysis of Patients Enrolled by Geography and Trial Status
7. PARTNERSHIPS AND COLLABORATIONS
7.1. Chapter Overview
7.2. Partnership Models
7.3. AI in Clinical Trials: List of Partnerships and Collaborations
7.3.1. Analysis by Year of Partnership
7.3.2. Analysis by Type of Partnership
7.3.3. Analysis by Year and Type of Partnership
7.3.4. Analysis by Application Area
7.3.5. Analysis by Target Therapeutic Area
7.3.6. Analysis by Type of Partner
7.3.7. Most Active Players: Analysis by Number of Partnerships
7.3.8. Analysis by Geography
8. FUNDING AND INVESTMENT ANALYSIS
8.1. Chapter Overview
8.2. Types of Funding
8.3. AI in Clinical Trials: List of Funding and Investments
8.3.1. Analysis by Year of Funding
8.3.2. Analysis by Amount Invested
8.3.3. Analysis by Type of Funding
8.3.4. Analysis by Type of Funding and Amount Invested
8.3.5. Most Active Players: Analysis by Amount Raised and Number of Funding Instances
8.3.6. Leading Investors: Analysis by Number of Funding Instances
8.3.7. Analysis of Amount Invested by Geography
8.3.8. Analysis of Number of Funding Instances by Geography
8.4. Concluding Remarks
9. BIG PHARMA INITIATIVES
9.1. Chapter Overview
9.2. Scope and Methodology
9.3. Analysis by Year of Initiative
9.4. Analysis by Type of Initiative
9.5. Analysis by Application Area of AI
9.6. Analysis by Target Therapeutic Area
9.7. Benchmarking Analysis: Big Pharma Players
10. AI IN CLINICAL TRIALS: USE CASES
10.1. Chapter Overview
10.2. Use Case 1: Collaboration between Roche and AiCure
10.3. Use Case 2: Collaboration between Takeda and AiCure
10.4. Use Case 3: Collaboration between Teva Pharmaceuticals and Intel
10.5. Use Case 4: Collaboration between Unnamed Pharmaceutical Company and Antidote
10.6. Use Case 5: Collaboration between Unnamed Pharmaceutical Company and Cognizant
10.7. Use Case 6: Collaboration between Cedars-Sinai Medical Center and Deep 6 AI
10.8. Use Case 7: Collaboration between GlaxoSmithKline (GSK) and PathAI
10.9. Use Case 8: Collaboration between Bristol Myers Squibb (BMS) and Concert AI
11. VALUE CREATION FRAMEWORK: A STRATEGIC GUIDE TO ADDRESS UNMET NEEDS IN CLINICAL TRIALS
11.1. Chapter Overview
11.2. Unmet Needs in Clinical Trials
11.3. Key Assumptions and Methodology
11.4. Key Tools / Technologies
11.4.1. Blockchain
11.4.2. Big Data Analytics
11.4.3. Real-world Evidence
11.4.4. Digital Twins
11.4.5. Cloud Computing
11.4.6. Internet of Things (IoT)
11.5. Trends in Research Activity
11.6. Trends in Intellectual Capital
11.7. Extent of Innovation versus Associated Risks
11.8. Results and Discussion
11.9. Summary
12. COST SAVING ANALYSIS
12.1. Chapter Overview
12.2. Key Assumptions and Methodology
12.3. Overall Cost Saving Potential of AI in Clinical Trials, 2023-2035
12.3.1. Cost Saving Potential in Phase I Clinical Trials, 2023-2035
12.3.2. Cost Saving Potential in Phase II Clinical Trials, 2023-2035
12.3.3. Cost Saving Potential in Phase III Clinical Trials, 2023-2035
12.3.4. Cost Saving Potential in Patient Recruitment, 2023-2035
12.3.5. Cost Saving Potential in Patient Retention, 2023-2035
12.3.6. Cost Saving Potential in Staffing and Administration, 2023-2035
12.3.7. Cost Saving Potential in Site Monitoring, 2023-2035
12.3.8. Cost Saving Potential in Source Data Verification, 2023-2035
12.3.9. Cost Saving Potential in Other Procedures, 2023-2035
13. MARKET SIZING AND OPPORTUNITY ANALYSIS
13.1. Chapter Overview
13.2. Forecast Methodology and Key Assumptions
13.3. Global AI in Clinical Trials Market, 2023-2035
13.3.1. AI in Clinical Trials Market: Distribution by Trial Phase, 2023 and 2035
13.3.2. AI in Clinical Trials Market: Distribution by Target Therapeutic Area, 2023 and 2035
13.3.3. AI in Clinical Trials Market: Distribution by End-user, 2023 and 2035
13.3.4. AI in Clinical Trials Market: Distribution by Key Geographical Regions, 2023 and 2035
14. CONCLUSION
15. EXECUTIVE INSIGHTS
16. APPENDIX I: TABULATED DATA
17. APPENDIX II: LIST OF COMPANIES AND ORGANIZATIONS
Companies Mentioned
Accelmed
Accenture
Acclinate
Agent Health
A.I. VALI
Aidar Health
AITIA
AKESOgen
Alexandria Venture Investments
Alira Health
AliveCor
Alliance for Clinical Trials in Oncology
Allucent
Alpha MD
ALS Association
Amadeus Capital Partners
Amber Specialty Pharmacy
American Society of Clinical Oncology (ASCO)
Ancora.ai
Anthem
Anthemis Exponential Ventures
Antidote Technologies
Arondor
Artificial Intelligence in Medicine (AIM) (a subsidiary of Inspirata)
ArtiQ
Arvinas
Aspen Insights
Assistance Publique Hopitaux de Paris
AV8 Ventures
Avalanche Venture Capital
Avident Health
Avon
Baird Capital
BEPATIENT
Beyond Celiac
Big Pi Ventures
Bioforum
Bioinfogate (acquired by Clarivate)
Biomatics Capital
Blue Heron Capital
Boehringer Ingelheim Venture Fund (BIVF)
Bold Capital Partners
Bolton NHS Foundation Trust
BootstrapLabs
Brainpan Innvovations
Brite Health
Bronze Valley
BUDDI.AI
BullFrog AI
Cambridge Cognition
Canary Speech
Carebox
Carenity (acquired by EvidentIQ)
Carlyle
Casdin Capital
Cavendish Impact Foundation (CIF)
CellCarta
Central Ohio Primary Care Physicians (COPC)
The Centre for Aging + Brain Health Innovation (CABHI )
Chainlink
Charterhouse Capital Partners
Chartline Capital Partners
Citeline ( a subsidiary of Norstella)
Clario
Clarivate
ClearPoint Investment Partners
Clinerion
Clinevo Technologies
clinicalAI
CliniOps
Clinithink
ClinScape
Cognizant
Community Health Network
ConcertAI
Constant Companion
Creadev
Crestle.ai (acquired by Doc.ai)
Crista Galli Ventures
Cumulus Neuroscience
Curenetics
Curify.ai
Dassault Systemes
DataON
Datavant
DCM Ventures
Declaration Partners
Deep 6 AI
Deep Lens (acquired by Paradigm)
DeepTrial
Dementia Discovery Fund (DDF)
Department of Veteran Affairs
Deutsche Investitions und Entwicklungsgesellschaft (DEG)
DiA Imaging Analysis
doc.ai (acquired by Sharecare)
EBSCO Information Services
Echo Health Ventures
EDBI
Edison Partners
Eight Roads Ventures
eimageglobal
EIT Health
Elliott Investment Management
Entrepreneur First
Epilepsy Study Consortium
Ergomed
Erlanger Health System
Espresso Capital
Eugene M. Lang Foundation
European Commission
European Investment Bank
Excelra
Experimental Cancer Medicine Centre (ECMC)
Experimind
Faber
fathom it group
FinLab EOS VC Fund
First Trust Capital Partners
Florida Cancer Affiliates
Folklore Ventures
Fosun RZ Capital
General Catalyst
Genoa Ventures
Global Alzheimer's Platform Foundation
Gloucestershire Cancer Alliance (SWAG)
GV (formerly Google Ventures)
Greater Gift
Grey Sky Venture Partners
Guy's and St Thomas' NHS Foundation Trust
H1
H2O.ai
Hambro Perks
Healint
Healthix
HealthMatch
HealthVerity
Hematology-Oncology Associates of Central New York (HOA)
Herefordshire and Worcestershire Health and Care NHS Trust
HCLTech
Human API
IBM
iClusion
ICON
IKJ Capital
iLoF
IMNA Solutions
ImpactAssets
Inato
iNDX.Ai
Innoplexus
Innovaderm
Innovatrix Capital
Insight Partners
Inspirata
Inspire
Intel Capital (a subsidiary of Intel)
Investissement Quebec
Iowa First Capital Fund
Iowa Innovation Acceleration Fund
IQVIA
IXICO
Jianke
Keosys
Khosla Ventures
Kinship
Kognitic
LaunchCapital
LBO France
Leal Health
Legit.Health
Leukemia & Lymphoma Society
Lieber Institute for Brain Development
Life Image (acquired by Intelerad Medical SystemsT )
Lightship
Linguamatics (a subsidiary of IQVIA)
Liquid 2 Ventures
LMK Clinical Research Consulting
Lokavant (a subsidiary of Roivant Sciences)
LSU Health New Orleans
Lunar Ventures
M12 (formerly known as Microsoft Ventures)
MassMutual Ventures
Matrix Capital Management
Matrix Partners
Maxer Consulting
Mayfield Fund
Mayo Clinic
Mayo Clinic Ventures (a subsidiary of Mayo Clinic)
McKesson Ventures (a subsidiary of McKesson)
Medable
Medical Research Network (MRN)
mediri
MEDSOFT
Memorial Sloan Kettering Cancer Center (MSK)
Menlo Ventures
Merck Global Health Innovation Fund (Merck GHI) (a subsidiary of Merck)
Moderna
MSD Global Health Innovation Fund (MGHIF)
MTIP
Mubadala Capital
National Minority Health Association (NMHA)
NEC
NEC OncoImmunity (a subsidiary of NEC)
NetraMark
New Leaf Venture Partners
Nex Cubed
Next Level Ventures
nference
NJF Capital
Nor-Tech
Northpond Ventures
Novoic
Novotech
nQ Medical
Nucleai
Oak HC/FT
Obvious Ventures
Ocala Oncology
Octopus Ventures
Olive Tree
OncoBay Clinical
One Nucleus
Opyl
Oracle
Otium Venture
?URA Health
Overline Venture Capital
Owkin
University of Oxford Innovation Fund (UOIF)
P1vital
P360
P3Life
Paige AI
Palisades Growth Capital
Pancare Foundation
Pangaea Data
Paradigm
Parkwalk Advisors
Passage AI
Patchai (acquired by Alira Health)
PathAI
Patient iP
PatientPoint
PatienTrials
Patiro
Perceiv AI
Perceptive Advisors
Pfizer Ventures (a subsidiary of Pfizer)
Pharmamodelling
Phastar
phaware
Phesi
physIQ
Plug and Play Ventures
Point72 Ventures
Population Health Partners
PPC (merged with Novotech)
Pritzker Group
ProofPilot
Propeller Health
Protocols.io
PWNHealth
Qualcomm Ventures
Quality Cancer Care Alliance Network (QCCA)
Quibim
Quiet Capital
Qure.ai
Qwince
Radical Ventures
RadMD (acquired by Medica Group)
Raylytic
re.Mind Capital
RealTime Software Solutions
Red Abbey Labs
Reify Health
Remarque Systems
Renmin Hospital of Wuhan University
Rev1 Ventures
Revo Capital
Revolution Growth
Risklick
Rural Vitality Fund
Rymedi
Sanofi Ventures (a subsidiary of Sanofi)
Scale Ventures
Science37
Semicrol
sensedat
Sensyne Health
Sequoia India
Serena and Fly Ventures
ServiceNow
Servier
SGInnovate
Sigmasoft
Signant Health
SimBioSys
Singtel Innov8
SiteGround Capital
SiteRx
Sixth Street
Small Business Innovation Research (SBIR)
Smedvig Capital
SoftBank Vision Fund
Somerset
Sopris Capital
SOSV
Sourcia
Southern Oncology Specialists
SpringRock Ventures
Square Peg
Square Peg Capital
Stanford Angels
Stratus
SubjectWell
Sway Ventures
Symphony Clinical Research (acquired by ICON)
SymphonyAI
Synetro
System Applications and Products in Data Processing (SAP)
T. Rowe Price
Taliaz
Talkdesk
Tamarind Hill Fund
Tech Transfer UPV
TEDCO's Seed Fund
Tempus
Tencent Holdings
Tenthpin
TFS Services
The Angels' Forum
ThoughtSphere
THREAD
Tiger Global Management
Timberline Holding
Translational Drug Development (TD2)
TransPerfect Life Sciences
Trialbee
Trials.ai (acquired by ZS Associates)
TrialSense
Tribeca Venture Partners
TT Capital Partners
TTi Health Research & Economics
U.S. Veteran's Affairs
UK Future Fund
Underscore Venture Capital
Unlearn.AI
VeriSIM
VersaTrial
Veterans Prostate Cancer Awareness (VPCa)
Viroclinics-DDL (acquired by Cerba HealthCare)
VirTrial
WallachBeth Capital
WCG Clinical
Wefight
Wiley
Winterlight Labs
Wittington Ventures
Worldwide Clinical Trials
WP Global Partners
XpertPatient
Zola Global Investors
ZS Associates
For more information about this report visit https://www.researchandmarkets.com/r/c67zyz
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