Chapter 2 is an executive summary of the insights captured in our research. It offers a high-level view on the likely evolution of the real world evidence market in the mid to long term.
Chapter 3 is an introductory chapter that presents a general overview of investment required for developing new medical products, along with information on the limitations associated with RCTs. Further, it features a detailed discussion on the growing importance of real world evidence and its potential to complement RCTs in healthcare decision-making. It also features a description of the process of generating real world evidence from the raw, unstructured data, along with details on different sources of data, and the potential applications of real world evidence. Further, the chapter features a discussion on the key growth drivers and roadblocks related to real world evidence, and the novel technologies that are likely to have a notable impact on the industry’s evolution over the coming decade.
Chapter 4 provides a detailed description on the primary elements of data governance and regulatory framework related to real world evidence across various geographies, namely North America (the US and Canada), Europe (the UK, Germany, France, Spain and Italy), and Asia-Pacific (Australia, China and Japan).
Chapter 5 provides a comprehensive overview of the industry players that are actively involved in providing real world evidence solutions. The chapter presents analysis of these players on the basis of their year of establishment, geographical location, size of the company, type of offering (real world data, analytics, and services), real world data sources used (medical claims, clinical trials, clinical setting, pharmacy, patient-powered and others), and intended application areas (early stage research, clinical development, regulatory submission / reimbursement / market access, and post-approval studies).
Chapter 6 provides a detailed analysis of close to 500 research articles related to real world evidence that have been published since 2016. The analysis takes into consideration several parameters, such as the year of publication, key focus areas, types of real world datasets utilized, indications, active stakeholders, geographical distribution of the authors and the journals. The chapter also highlights the various attempts that are being made to add value to the ongoing R&D efforts within this domain.
Chapter 7 provides a comprehensive clinical trial analysis of completed, ongoing and planned studies, assessing the real world impact of pharmacologic / non-pharmacologic treatment on patients. For the purpose of this analysis, we looked at the clinical studies that have been last updated since 2013, and analyzed them on the basis of various parameters, such as current trial status, trial registration year, geographical distribution and enrolled patient population across different geographies, type of study, leading industry and non-industry players, grid mapping of key therapeutic areas, and trial benchmarking for leading industry players.
Chapter 8 provides insights on the popularity of real world evidence on the social media platform, Twitter. The chapter highlights the yearly distribution of tweets posted on the platform in the period between January 2013 and June 2018, and the most significant events responsible for increase in the volume of tweets each year. Additionally, the chapter showcases the most frequently mentioned keywords, real world data sources, applications, therapeutic areas and players, on the social media platform. It elucidates the most prolific authors and presents a bubble analysis of the most influential authors related to real world evidence on Twitter.
Chapter 9 features insights obtained from an in-depth analysis of the global real world evidence events organized for stakeholders in this domain. For the purpose of this analysis, we looked at the summits, forums, conferences, and annual meetings that have been organized since 2017 and analyzed these events on the basis of various parameters, such as event type, location, event agendas, organizers, and industry and non-industry participants. The chapter also highlights the evolution of discussion topics related to real world evidence.
Chapter 10 provides details on the key parameters and trends that are likely to influence the future of the real world evidence market, under a comprehensive SWOT framework. The chapter also features a schematic Harvey ball analysis to highlight the relative impact of each SWOT parameter on the overall real world evidence market.
Chapter 11 presents information on the needs of different stakeholders (manufacturers, regulators, payers, providers and patients) involved in this domain. The chapter qualitatively assesses the real world evidence related needs of each stakeholder group and the relative importance of their expectations within this domain.
Chapter 12 provides a comprehensive list of notable real world evidence use cases of pharmaceutical / medical device companies in the recent past (since 2016). The chapter highlights how these companies leveraged real world evidence to support their regulatory decisions, advance disease understanding and clinical guidelines, and assist outcome-based reimbursement decisions. In addition, the chapter presents an insightful opportunity analysis, estimating the existing market size and potential growth opportunities of real world evidence across different applications (early stage research, clinical development, regulatory approval, pricing / reimbursement, and post-approval studies). Based on multiple parameters, such as number of pre- or post-approval studies conducted annually, investment associated with these studies, and the likely cost and time saving opportunities, we have provided an informed estimate on the likely evolution of the market over the period 2018-2030. In addition, the report provides detailed market segmentation on the basis of type of real world data sources (medical claims, clinical trials, clinical setting, pharmacy, patient-powered and other data sources), therapeutic area (cardiovascular disorders, infectious diseases, metabolic disorders, neurological / psychiatric disorders, oncological disorders, and other disorders), and the geographical distribution of the market (North America, Europe, Asia-Pacific, and Rest of the World).
Chapter 13 presents the insights generated from a detailed survey, wherein we invited multiple stakeholders involved in the real world evidence domain. The participants, who were primarily Directors / CXO level representatives of their respective companies, helped us develop a deeper understanding on the nature of their offerings and the associated commercial potential.
Chapter 14 is a collection of transcripts of interviews conducted with various key stakeholders during the course of this study. We have presented the details of our discussions with Jane Reed (Head of Life Science Strategy, Linguamatics), Jonathan Moshinsky (Head of Market Strategy, uMotif) and Anonymous (Vice President, Big Pharmaceutical Company).
Chapter 15 is an appendix, which provides tabulated data and numbers for all the figures included in the report.
Chapter 16 is an appendix, which contains the list of companies and organizations mentioned in the report.
Table of Contents
1. PREFACE
1.1. Scope of the Report
1.2. Research Methodology
1.3. Chapter Outlines
2. EXECUTIVE SUMMARY
3. INTRODUCTION
3.1. Need for Real World Evidence
3.1.1. Growing Crisis of Chronic Disorders
3.1.2. High Investment Involved in Drug Development
3.1.2.1. Role of Randomized Clinical Trials
3.1.2.2. Limitations of Randomized Clinical Trials
3.1.3. Increasing Shift from Volume- to Value-based Care
3.2. An Overview of Real World Evidence
3.2.1. Sources of Real World Data
3.2.1.1. Medical Claims Data
3.2.1.2. Clinical Trial Data
3.2.1.3. Clinical Settings Data
3.2.1.4. Patient-Powered Data
3.2.1.5. Pharmacy Data
3.2.1.6. Other Real World Data Sources
3.2.2. Comparison of Randomized Clinical Trials and Real World Evidence
3.2.3. Advantages and Limitations of Real World Evidence
3.2.4. Potential Applications of Real World Evidence
3.2.5. Growth Drivers and Challenges
3.3. Role of Advanced Techniques in Real World Data Management
4. DATA GOVERNANCE AND REGULATORY FRAMEWORK FOR REAL WORLD EVIDENCE
4.1. Chapter Overview
4.2. Primary Elements of Data Governance for Real World Evidence
4.3. Importance of Regulatory Framework for Real World Evidence
4.4. Data Governance and Regulatory Framework in North America
4.4.1. The US Scenario
4.4.1.1. Data Governance
4.4.1.2. Regulatory Framework
4.4.1.3. Future Recommendations
4.4.2. The Canadian Scenario
4.4.2.1. Data Governance
4.4.2.2. Regulatory Framework
4.4.2.3. Future Recommendations
4.5. Data Governance and Regulatory Framework in Europe
4.5.1. The UK Scenario
4.5.1.1. Data Governance
4.5.1.2. Regulatory Framework
4.5.1.3. Future Recommendations
4.5.2. The German Scenario
4.5.2.1. Data Governance
4.5.2.2. Regulatory Framework
4.5.2.3. Future Recommendations
4.5.3. The French Scenario
4.5.3.1. Data Governance
4.5.3.2. Regulatory Framework
4.5.3.3. Future Recommendations
4.5.4. The Spanish Scenario
4.5.4.1. Data Governance
4.5.4.2. Regulatory Framework
4.5.4.3. Future Recommendations
4.5.5. The Italian Scenario
4.5.5.1. Data Governance
4.5.5.2. Regulatory Framework
4.5.5.3. Future Recommendations
4.6. Data Governance and Regulatory Framework in Asia-Pacific
4.6.1. The Australian Scenario
4.6.1.1. Data Governance
4.6.1.2. Regulatory Framework
4.6.1.3. Future Recommendations
4.6.2. The Chinese Scenario
4.6.2.1. Data Governance
4.6.2.2. Regulatory Framework
4.6.2.3. Future Recommendations
4.6.3. The Japanese Scenario
4.6.3.1. Data Governance
4.6.3.2. Regulatory Framework
4.6.3.3. Future Recommendations
5. CURRENT MARKET LANDSCAPE
5.1. Chapter Overview
5.2. List of Real World Evidence Solution Providers
5.2.1. Analysis by Year of Establishment
5.2.2. Analysis by Geographical Location
5.2.3. Analysis by Company Size
5.2.4. Analysis by Type of Offering
5.2.5. Analysis by Real World Data Sources
5.2.6. Analysis by Applications of Real World Evidence
6. PUBLICATION ANALYSIS
6.1. Chapter Overview
6.2. Scope and Methodology
6.3. Real World Evidence: Publication Analysis
6.3.1. Analysis by Publication Year
6.3.2. Analysis by Key Focus Areas
6.3.3. Analysis by Real World Data Sources
6.3.4. Analysis by Key Indications Examined
6.3.5. Leading Players in Terms of Number of Published Studies
6.3.6. Analysis by Geographical Location of Leading Players
6.3.7. Key Journals
7. CLINICAL TRIAL ANALYSIS
7.1. Chapter Overview
7.2. Scope and Methodology
7.3. Real World Evidence: Clinical Trial Analysis
7.3.1. Analysis by Trial Registration Year
7.3.2. Analysis by Geography and Number of Clinical Trials
7.3.3. Analysis by Geography and Enrolled Patient Population
7.3.4. Analysis by Trial Recruitment Status
7.3.5. Analysis by Type of Study
7.3.6. Analysis by Type of Sponsors / Collaborators
7.3.7. Most Active Players in Terms of Number of Trials
7.3.8. Analysis by Focus Areas
7.3.9. Analysis by Target Therapeutic Areas
7.3.10. Grid Analysis of Key Therapeutic Areas, 2013-2018
7.3.11. Benchmark Analysis of Key Industry Players
8. EMERGING TRENDS ON SOCIAL MEDIA
8.1. Chapter Overview
8.2. Scope and Methodology
8.3. Real World Evidence: Trends on Twitter
8.3.1. Historical Trends in Volume of Tweets
8.3.2. Popular Keywords
8.3.3. Popular Sources of Real World Data
8.3.4. Popular Applications of Real World Evidence
8.3.5. Popular Therapeutic Areas
8.3.6. Popular Stakeholders
8.3.7. Most Prolific Contributors
8.3.8. Most Influential Contributors
9. GLOBAL EVENTS ANALYSIS
9.1. Chapter Overview
9.2. Scope and Methodology
9.3. Real World Evidence: Global Events Analysis
9.3.1. Analysis by Year of Occurrence
9.3.2. Analysis by Geography
9.3.3. Analysis by Type of Event
9.3.4. Analysis by Key Focus Area / Event Agenda
9.3.5. Most Active Event Organizers
9.3.6. Most Active Players in Terms of Event Participation
9.3.7. Analysis by Seniority Level of Participants
9.3.8. Geographical Mapping of Upcoming Events
10. SWOT ANALYSIS
10.1. Chapter Overview
10.2. Comparison of SWOT Factors
11. STAKEHOLDER NEEDS ANALYSIS
11.1. Chapter Overview
11.2. Real World Evidence: Needs of Stakeholders
11.2.1. Comparison of Needs of Stakeholders
12. REAL WORLD EVIDENCE USE CASES AND OPPORTUNITY ASSESSMENT
12.1. Chapter Overview
12.2. Real World Evidence Use Cases
12.3. Real World Evidence Market Opportunity Assessment
12.3.1 Methodology and Key Assumptions
12.3.2. Global Real World Evidence Market Opportunity, 2018-2030
12.3.3. Global Real World Evidence Market Opportunity by Type of Datasets
12.3.3.1.Real World Evidence Market Opportunity from Medical Claims Data, 2018-2030
12.3.3.2. Real World Evidence Market Opportunity from Clinical Trials Data, 2018-2030
12.3.3.3. Real World Evidence Market Opportunity from Clinical Settings Data, 2018-2030
12.3.3.4. Real World Evidence Market Opportunity from Patient-Powered Data, 2018-2030
12.3.3.5. Real World Evidence Market Opportunity from Pharmacy Data, 2018-2030
12.3.3.6. Real World Evidence Market Opportunity from Other Types of Data, 2018-2030
12.3.4. Global Real World Evidence Market Opportunity by Therapeutic Areas
12.3.4.1.Real World Evidence Market Opportunity in Cardiovascular Disorders, 2018-2030
12.3.4.2.Real World Evidence Market Opportunity in Infectious Diseases, 2018-2030
12.3.4.3.Real World Evidence Market Opportunity in Metabolic Disorders, 2018-2030
12.3.4.4.Real World Evidence Market Opportunity in Neurological / Psychiatric Disorders, 2018-2030
12.3.4.5.Real World Evidence Market Opportunity in Oncological Disorders, 2018-2030
12.3.4.6.Real World Evidence Market Opportunity in Other Types of Disorders, 2018-2030
12.3.5. Global Real World Evidence Market Opportunity by Applications
12.3.5.1.Real World Evidence Market Opportunity in Early Stage Research, 2018-2030
12.3.5.2.Real World Evidence Market Opportunity in Clinical Development, 2018-2030
12.3.5.3.Real World Evidence Market Opportunity in Regulatory Approval, 2018-2030
12.3.5.4.Real World Evidence Market Opportunity in Pricing / Reimbursement, 2018-2030
12.3.5.5.Real World Evidence Market Opportunity in Post-Approval Studies, 2018-2030
12.3.6. Regional Market Opportunities for Real World Evidence
12.3.6.1.Real World Evidence Market Opportunity in North America, 2018-2030
12.3.6.2.Real World Evidence Market Opportunity in Europe, 2018-2030
12.3.6.3.Real World Evidence Market Opportunity in Asia-Pacific, 2018-2030
12.3.6.4.Real World Evidence Market Opportunity in Rest of the World, 2018-2030
13. SURVEY INSIGHTS
13.1. Chapter Overview
13.2. Seniority Level of Respondents
13.3. Type of Offering
13.4. Real World Data Sources
13.5. Applications of Real World Evidence
13.6. Key Challenges in Generating Real World Evidence
13.7. Extent of Outsourcing
13.8. Current Market Opportunity
14. INTERVIEW TRANSCRIPTS
14.1. Chapter Overview
14.2. Jane Reed, Head of Life Science Strategy, Linguamatics
14.3. Jonathan Moshinsky, Head of Market Strategy, uMotif
14.4. Anonymous, Vice President, Big Pharmaceutical Company
15. APPENDIX 1: TABULATED DATA
16. APPENDIX 2: LIST OF COMPANIES AND ORGANIZATIONS
List of Figures
Figure 3.1. Common Types of Chronic Disorders
Figure 3.2. Drug Development Costs: Year-wise Trend, 2000-2017 (USD Million)
Figure 3.3. Limitations of Randomized Clinical Trials
Figure 3.4. Process of Generating Evidence from Real World Data
Figure 3.5. Real World Data Sources
Figure 3.6. Potential Applications of Real World Evidence
Figure 3.7. Growth Drivers and Potential Roadblocks
Figure 4.1. Primary Elements of Data Governance for Real World Evidence
Figure 4.2. Ideal Regulatory Framework for Real World Evidence
Figure 5.1. Real World Evidence Solution Providers: Distribution by Year of Establishment
Figure 5.2. Real World Evidence Solution Providers: Distribution by Geography
Figure 5.3. Real World Evidence Solution Providers: Distribution by Company Size
Figure 5.4. Real World Evidence Solution Providers: Distribution by Type of Offering
Figure 5.5. Real World Evidence Solution Providers: Distribution by Real World Data Sources
Figure 5.6. Real World Evidence Solution Providers: Distribution by Applications
Figure 6.1. Publications: Historical Trends (2016-H1 2018)
Figure 6.2. Publications: Distribution by Key Focus Areas
Figure 6.3. Publications: Word Cloud Analysis of Study Titles
Figure 6.4. Publications: Distribution by Real World Data Sources
Figure 6.5. Publications: Key Indications in Terms of Number of Published Studies
Figure 6.6. Publications: Distribution by Type of Sponsors
Figure 6.7. Publications: Most Active Industry Players in Terms of Number of Published Studies
Figure 6.8. Publications: Geographical Distribution of Authors
Figure 6.9. Publications: Key Journals
Figure 7.1. Clinical Trials: Distribution by Trial Status
Figure 7.2. Clinical Trials: Distribution by Registration Year
Figure 7.3. Clinical Trials: Geographical Distribution by Number of Trials
Figure 7.4. Clinical Trials: Geographical Distribution by Enrolled Patient Population
Figure 7.5. Clinical Trials: Distribution by Registration Year and Enrolled Patient Population
Figure 7.6. Clinical Trials: Dot Plot of Number of Trials and Enrolled Patient Population
Figure 7.7. Clinical Trials: Distribution by Registration Year and Trial Recruitment Status
Figure 7.8. Clinical Trials: Geographical Distribution by Registration Year and Recruitment Status
Figure 7.9. Clinical Trials: Distribution by Type of Study
Figure 7.10. Clinical Trials: Distribution by Registration Year and Type of Study
Figure 7.11. Clinical Trials: Distribution by Type of Sponsors / Collaborators
Figure 7.12. Clinical Trials: Most Active Industry Players in Terms of Number of Trials Conducted
Figure 7.13. Clinical Trials: Most Active Non-Industry Players in Terms of Number of Trials Conducted
Figure 7.14. Clinical Trials: Focus Areas
Figure 7.15. Clinical Trials: Distribution by Therapeutic Areas
Figure 7.16. Clinical Trials: Leading Indications in Terms of Number of Trials Conducted
Figure 7.17. Clinical Trials: Distribution by Registration Year and Key Therapeutic Areas
Figure 7.18. Clinical Trials: Year-wise Trend of Trials Conducted by Leading Industry Players, 2013-2018
Figure 7.19. Clinical Trials: Benchmarking of Leading Industry Players by Number of Trials across Key Therapeutic Areas
Figure 8.1. Trends on Social Media: Historical Activities on Twitter, 2013-2018
Figure 8.2. Trends on Social Media: Year-wise Analysis by Volume, 2013-2018
Figure 8.3. Trends on Social Media: Popular Keywords
Figure 8.4. Trends on Social Media: Popular Real World Data Sources
Figure 8.5. Trends on Social Media: Popular Applications of Real World Evidence
Figure 8.6. Trends on Social Media: Popular Therapeutic Areas
Figure 8.7. Trends on Social Media: Popular Stakeholders
Figure 8.8. Trends on Social Media: Most Prolific Contributors
Figure 8.9. Trends on Social Media: Most Influential Contributors
Figure 9.1. Global Events: Cumulative Quarter-wise Trend, Q1 2017-Q2 2018
Figure 9.2. Global Events: Distribution by Location
Figure 9.3. Global Events: Distribution by Type
Figure 9.4. Global Events: Key Focus Areas
Figure 9.5. Global Events: Historical Trend of Event Agendas, Q1 2017-Q2 2018
Figure 9.6. Global Events: Most Active Event Organizers
Figure 9.7. Global Events: Most Active Industry Players in Terms of Event Participation
Figure 9.8. Global Events: Most Active Non-Industry Players in Terms of Event Participation
Figure 9.9. Global Events: Distribution by Designations of Event Participants
Figure 9.10. Global Events: Distribution by Affiliated Departments of Event Participants
Figure 9.11. Global Events: Geographical Mapping of Upcoming Events
Figure 10.1. Real World Evidence: SWOT Analysis
Figure 10.2. Comparison of SWOT Factors
Figure 11.1. Real World Evidence: Stakeholder Needs Analysis
Figure 11.2. Comparison of Needs of Stakeholders
Figure 12.1. Global Real World Evidence Market Opportunity, 2018-2030 (USD Million)
Figure 12.2. Real World Evidence Market Opportunity from Medical Claims Data, 2018-2030 (USD Million)
Figure 12.3. Real World Evidence Market Opportunity from Clinical Trials Data, 2018-2030 (USD Million)
Figure 12.4. Real World Evidence Market Opportunity from Clinical Settings Data, 2018-2030 (USD Million)
Figure 12.5. Real World Evidence Market Opportunity from Patient-Powered Data, 2018-2030 (USD Million)
Figure 12.6. Real World Evidence Market Opportunity from Pharmacy Data, 2018-2030 (USD Million)
Figure 12.7. Real World Evidence Market Opportunity from Other Types of Data, 2018-2030 (USD Million)
Figure 12.8. Real World Evidence Market Opportunity in Cardiovascular Disorders, 2018-2030 (USD Million)
Figure 12.9. Real World Evidence Market Opportunity in Infectious Diseases, 2018-2030 (USD Million)
Figure 12.10. Real World Evidence Market Opportunity in Metabolic Disorders, 2018-2030 (USD Million)
Figure 12.11. Real World Evidence Market Opportunity in Neurological / Psychiatric Disorders, 2018-2030 (USD Million)
Figure 12.12. Real World Evidence Market Opportunity in Oncological Disorders, 2018-2030 (USD Million)
Figure 12.13. Real World Evidence Market Opportunity in Other Types of Disorders, 2018-2030 (USD Million)
Figure 12.14. Real World Evidence Market Opportunity in Early Stage Research, 2018-2030 (USD Million)
Figure 12.15. Real World Evidence Market Opportunity in Clinical Development, 2018-2030 (USD Million)
Figure 12.16. Real World Evidence Market Opportunity in Regulatory Approval, 2018-2030 (USD Million)
Figure 12.17. Real World Evidence Market Opportunity in Pricing / Reimbursement, 2018-2030 (USD Million)
Figure 12.18. Real World Evidence Market Opportunity in Post-Approval Studies, 2018-2030 (USD Million)
Figure 12.19. Real World Evidence Market Opportunity in North America, 2018-2030 (USD Million)
Figure 12.20. Real World Evidence Market Opportunity in Europe, 2018-2030 (USD Million)
Figure 12.21. Real World Evidence Market Opportunity in Asia-Pacific, 2018-2030 (USD Million)
Figure 12.22. Real World Evidence Market Opportunity in Rest of the World, 2018-2030 (USD Million)
Figure 13.1. Survey Insights: Distribution by Type of Organization
Figure 13.2. Survey Insights: Distribution by Location of Organization
Figure 13.3. Survey Insights: Distribution by Seniority Level
Figure 13.4. Survey Insights: Distribution by Type of Offering
Figure 13.5. Survey Insights: Distribution by Real World Data Sources
Figure 13.6. Survey Insights: Distribution by Purpose of Real World Evidence Generation
Figure 13.7. Survey Insights: Distribution by Key Challenges
Figure 13.8. Survey Insights: Distribution by Extent of Outsourcing
Figure 13.9. Survey Insights: Distribution by Current Market Opportunity
List of Tables
Table 3.1. Primary Elements of Different Sources of Real World Data
Table 3.2. Real World Evidence Opportunities in Pharmaceutical and Medical Device Industries
Table 3.3. Comparison of Randomized Clinical Trials and Real World Evidence
Table 5.1. List of Real World Evidence Solution Providers
Table 5.2. Real World Evidence Solution Providers: Information on Real World Data Sources and Applications
Table 7.1. List of Leading Clinical Trials by Enrolled Patient Population
Table 7.2. Grid Analysis of Key Therapeutic Areas and Number of Trials, 2013-2018
Table 12.1. Real World Evidence Use Cases, 2016-H1 2018
Table 13.1. Survey Insights: Overview of the Participating Organizations
Table 13.2. Survey Response: Seniority Level of Respondents
Table 13.3. Survey Insights: Type of Offering
Table 13.4. Survey Insights: Sources of Real World Data
Table 13.5. Survey Insights: Purpose of Real World Evidence Generation
Table 13.6. Survey Insights: Key Challenges
Table 13.7. Survey Insights: Extent of Outsourcing
Table 13.8. Survey Insights: Current Market Opportunity
Table 15.1. Drug Development Costs: Year-wise Trend 2000-2017 (USD Million)
Table 15.2. Real World Evidence Solution Providers: Distribution by Year of Establishment
Table 15.3. Real World Evidence Solution Providers: Distribution by Geography
Table 15.4. Real World Evidence Solution Providers: Distribution by Size (Employee Count)
Table 15.5. Real World Evidence Solution Providers: Distribution by Type of Offering
Table 15.6. Real World Evidence Solution Providers: Distribution by Sources of Real World Data
Table 15.7. Real World Evidence Solution Providers: Distribution by Applications
Table 15.8. Publications: Historical Trends (2016-H1 2018)
Table 15.9. Publications: Distribution by Key Focus Areas
Table 15.10. Publications: Distribution by Real World Data Sources
Table 15.11. Publications: Key Indications in Terms of Number of Published Studies
Table 15.12. Publications: Distribution by Type of Sponsors
Table 15.13. Publications: Most Active Industry Players in Terms of Number of Published Studies
Table 15.14. Publications: Geographical Distribution of Authors
Table 15.15. Publications: Key Journals
Table 15.16. Clinical Trials: Distribution by Trial Status
Table 15.17. Clinical Trials: Distribution by Registration Year
Table 15.18. Clinical Trials: Geographical Distribution by Number of Trials
Table 15.19. Clinical Trials: Geographical Distribution by Enrolled Patient Population
Table 15.20. Clinical Trials: Distribution by Registration Year and Enrolled Patient Population
Table 15.21. Clinical Trials: Distribution by Registration Year and Trial Recruitment Status
Table 15.22. Clinical Trials: Geographical Distribution by Registration Year and Recruitment
List of Companies
The following companies / institutes / government bodies and organizations have been mentioned in this report.
- 23andMe
- 8KMiles
- Abbott
- AbbVie
- Acceliant
- Accenture
- Accsight
- Adarna Health Data
- Adelphi Real World
- Advera Health Analytics
- Aetion
- Allscripts
- Amazon Web Services
- American College of Cardiology
- American Diabetes Association
- Amgen
- Ana Health
- Analytica Laser
- Anthem
- Apple
- Arcana Institute
- Astellas Pharma
- AstraZeneca
- Axonal-Biostatem
- Axtria
- Bayer
- BC Platforms
- Biogen
- Boehringer Ingelheim
- Boston Health Economics
- Boston Scientific
- Bristol-Myers Squibb
- Cambridge Healthtech Institute
- CardioVascular Research Foundation
- CareFacets
- Caros Connect
- CBI
- Cegedim Strategic Data
- Centers for Disease Control and Prevention
- Chinese Academy of Medical Sciences
- CitiusTech
- CK Aspire
- Clarivate Analytics
- Clinakos
- ClinaMetrics
- Clinerion
- Clinical Trial EndPoint
- Clinigen Group
- Cloudera
- CloudMoyo
- Cogentia Healthcare Consulting
- Cognizant
- Conference Series
- ConvergeHEALTH
- Cota Healthcare
- Crossix Solutions
- Custodix
- D Cube Analytics
- Daichii Sankyo
- Data2Life
- Databricks
- Decision Driver Analytics
- Decision Resources
- Defense Intelligence Agency
- DIGIPHARM
- Digital Health Labs
- Drug Intelligence
- Duke University
- Dycros
- Edwards Lifesciences
- Eli Lilly
- Elligo Health Research
- Ephicacy
- EPID Research
- ESiOR
- European Medicines Agency
- Eurotrials
- Evidence Based Solutions
- Evidera
- evoMetrics
- Ernst & Young
- eyeforpharma
- Flatiron Health
- Flex
- Fuzzy Logix
- Genentech
- Genospace
- GNS Healthcare
- Google
- GlaxoSmithKline
- Harvard Medical School
- Healint
- Health IQ
- Health Solutions
- Healthagen
- HealthCore
- Healthing Research
- HealThink
- HealthVerity
- Humana
- Huron Consulting
- IBM Watson Health
- ICON
- Ignite Data
- Indegene
- Infosys
- Ingress Health
- InnoWin
- Inovalon
- Insight Pharmaceuticals
- Institute for Quality and Efficiency in Health Care
- Insys Group
- Intel
- International Society for Pharmacoeconomics and Outcomes Research
- IntrinsiQ Specialty Solutions
- IQVIA
- iwantGreatCare
- Janssen Pharmaceutica
- Johaus Global
- Johnson & Johnson
- Kaiku Health
- Kantar Health
- Karolinska Institutet
- Keedio
- Keyrus Biopharma
- Knowledgent
- Koneksa Health
- Kx Systems
- Lifecode Solutions
- Linguamatics
- LINK Medical Research
- Lundbeck
- LynxCare
- M2Gen
- M2S
- MA Provider
- MakroCare
- Mapi Group
- MarkLogic
- MarksMan Healthcare Communications
- Massachusetts General Hospital
- MaxisIT
- Mayo Clinic
- McKesson
- MDC Partners
- MeaningCloud
- Medaffcon
- Med-eShare
- MedEngine
- Medical Wisdom Consulting Group
- Medidata Solutions
- Medlior Health Outcomes Research
- Medpace
- MedStreaming
- Medtronic
- Merck
- Mercy
- MyOwnMed
- mySugr
- Northern Alberta Clinical Trials and Research Centre
- National Academies of Sciences, Engineering and Medicine
- National Cancer Institute
- National Institutes of Health
- National Institute of Mental Health
- National Institute on Drug Abuse
- National Investigation Agency
- New England Research Institute
- New York Heart Association
- NJ YZ Clinical Trials and Consulting
- Novartis
- Novo Nordisk
- Numerus
- Observational and Pragmatic Research Institute
- Odysseus Data Services
- OKRA Technologies
- OM1
- Omega CRO
- Oncocare Health
- OncoStats
- Optra Systems
- Optum
- OptumInsight
- Oracle
- ORPHA Strategy Consulting
- OXON Epidemiology
- Palantir
- PAREXEL
- Patient-Centered Outcomes Research Institute
- PatientsLikeMe
- PatientSource
- Peking University
- Peripharm
- PerkinElmer
- Pfizer
- pH Associates
- Pharma Intelligence
- Pharmaceuticals and Medical Devices Agency
- Pharmerit International
- PHARMO Institute
- Pinscriptive
- Point-of-Care Partners
- PotentiaMED
- PRA Health Sciences
- Precision Digital Health
- Precision Health AI
- Premier
- Qlik
- Quantify Research
- Quantzig
- Raven Biosciences
- Real Consulting Data
- Real Life Sciences
- RealHealthData
- Revon Systems
- Roam
- Roche
- RxAnte
- S3 Connected Health
- Saama Technologies
- Sanofi
- SAS Institute
- Savana
- Sciensus
- Sciformix
- Self Care Catalysts
- Sentry Data Systems
- SHYFT Analytics
- Society of Thoracic Surgeons
- Sprim Advanced Life Sciences
- SQN Clinical
- St. Jude Medical
- Stanford University
- StatFinn
- Sutter Health
- SVMPharma
- Symphony Health Solutions
- Syneos Health
- Synergus
- Syntel
- Takeda Pharmaceutical
- Talking Medicines
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