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Market Research Report

Pharmaceutical and Life Sciences Real World Evidence: Market Landscape and Competitive Insights, 2018-2030

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Pharmaceutical and Life Sciences Real World Evidence: Market Landscape and Competitive Insights, 2018-2030
Published: October 5, 2018 Content info: 226 Pages
Description

The process of developing new and disruptive medical products involves heavy investments, both in terms of time and cost. Estimates suggest that each prescription drug requires an average of about 10 years and over USD 2.5 billion in working capital before it gets commercialized. In order to gain regulatory approval and establish standards for the safety and efficacy of these products, randomized clinical trials (RCTs) are conducted; these account for a staggering 40% of the pharmaceutical industry's budget. In addition to excessive R&D costs, these trials are fraught with various other challenges, such as prolonged delays and risk of failure / termination. It is also worth highlighting that most clinical trials are conducted under controlled conditions and involve a fairly homogenous patient population; however, when such products are approved, there are a variety of factors (both genetic and environmental) that need to be considered while treating individual patients. Data generated from real world applications of drug / therapy products partly addresses the aforementioned complexities and serves to complement the insights derived from controlled RCTs.

Real world evidence has demonstrated the potential to validate the therapeutic value of pharmaceutical products and help customize product development in a more patient centric manner. In December 2016, the 21st Century Cures Act was passed directing the FDA to evaluate the applications of real world evidence in supporting healthcare decision-making. Its numerous applications have further encouraged pharmaceutical companies and health economists to utilize it in the evaluation of product candidates targeting even the rarest of medical conditions. In fact, it is estimated that, on an average, a big pharmaceutical company spends nearly USD 20 million annually for generating real world evidence-based insights. The growing importance of real world evidence in healthcare decision-making is also evident from the number of tweets (~4,400) posted on the social media platform, Twitter, in recent years. It is also worth noting that, since 2017, close to 75 global events (which include summits, forums, conferences and annual meetings) have been organized to discuss different aspects of real world evidence. Further, in the past few years, more than 1,000 studies have been initiated by stakeholders in real world setting to assess the impact of pharmacologic / non-pharmacologic treatment on patients and healthcare systems. Various initiatives are underway to further explore the potential of real world evidence in different stages of drug development. We believe that such efforts are likely to boost the overall growth of this market in the coming years.

Synopsis:

The ‘Real World Evidence: Market Landscape and Competitive Insights, 2018-2030’ report features an extensive study on the industry players that are offering real world data / analytics / services to the pharmaceutical and life sciences industries. Amongst other elements, the report features:

  • An overview of the current status of the market with respect to the companies providing real world evidence related solutions. It features information on their year of establishment, geographical location, size of the company, type of offering (real world data, analytics, and services), real world data sources (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).
  • An elaborate discussion on data governance and the existing 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).
  • A detailed publication analysis of close to 500 articles that have been published since 2016, highlighting the key focus areas of ongoing real world evidence-based research activity in the pharmaceutical and life sciences industries. The analysis also highlights the key prevalent trends associated with these publications, including information on the types of real world data sources utilized, leading indications, active stakeholders, and the most popular journals within this domain.
  • A comprehensive analysis of completed, ongoing and planned studies conducted in the real world setting. For the purpose of this analysis, we considered only those studies that have been last updated since 2013, and analyzed them on the basis of various parameters, such as current trial status, regional distribution, type of sponsor, target indications, and enrolled patient population across different geographies.
  • An analysis depicting the prevalent and emerging trends related to this domain as represented on the social media platform, Twitter. In addition to providing information on yearly trends related to the volume of tweets since 2013, the analysis highlights the most frequently talked about real world data sources, applications, therapeutic areas, active players, and influential authors.
  • An in-depth analysis of recent events (summits / forums / conferences / annual meetings) that were organized for stakeholders in this domain, highlighting the evolution of discussion topics related to real world evidence. The analysis also provides details on event type, regional distribution, emerging agendas, popular organizers, active industry and non-industry players, and a schematic mapping of upcoming planned events.
  • A discussion on affiliated trends, key drivers and challenges, under a SWOT framework, featuring a Harvey ball analysis, highlighting the relative impact of each SWOT parameter on the overall real world evidence market.
  • A comparative analysis of the needs of different stakeholders (manufacturers, regulators, payers, providers and patients) involved in this domain.
  • A list of recent use cases where real world evidence was leveraged by pharmaceutical / medical device companies, highlighting the ways in which companies have utilized such information to support regulatory decisions, advance disease understanding, and develop outcome-based reimbursement model.
  • An insightful opportunity analysis, estimating the existing market size and potential growth opportunities across different applications (early stage research, clinical development, regulatory approval, pricing / reimbursement, and post-approval studies) of real world evidence. 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.

The opinions presented in this study were influenced by inputs (through a comprehensive survey) of several key players in this domain. In addition, the report features detailed transcripts of interviews held with the following individuals:

  • Jane Reed (Head of Life Science Strategy, Linguamatics)
  • Jonathan Moshinsky (Head of Market Strategy, uMotif)
  • Mark Cziraky (Vice President of Research, HealthCore)
  • Anonymous (Vice President, Big Pharmaceutical Company)

All actual figures have been sourced and analyzed from publicly available information forums and primary research discussions. Financial figures mentioned in this report are in USD, unless otherwise specified.

Example Highlights:

  • 1. Close to 200 players are actively involved in providing real world evidence-based insights to the pharmaceutical industry. Of these, around 45% offer a range of services for real world evidence generation. Examples of such players include (in alphabetical order, no specific selection criteria) Clinigen Group, HealthCore, ICON, Ingress Health, IQVIA, PAREXEL, pH Associates, Quantzig, and Syneos Health. These are followed by companies that offer analytical platforms (39%) and real world datasets (16%). Examples of such players include (in alphabetical order, no specific selection criteria) Aetion, Flatiron Health, IBM Watson Health, Linguamatics, PatientsLikeMe, RealHealthData, Saama Technologies, SHYFT Analytics, Tempus, TriNetX, and uMotif.
  • 2. More than 120 real world data / analytics / service providers utilize clinical data derived from medical and patient care records, such as electronic health records, clinical registries, genomic data repositories, lab tests results, and pathology data. These are followed by companies (over 100) that claim to use patient experience data for generating actionable insights. Other datasets that are commonly used by stakeholders in this industry include (but not limited to) medical claims data, clinical trials data and pharmacy data.
  • 3. Leveraging the aforementioned data, close to 145 companies are engaged in providing actionable, evidence-based insights for post-approval research. Other key application areas of real world evidence include (in decreasing order of number of companies) clinical development (~65%), regulatory approval / reimbursement / market access (~56%), and early stage research (~54%).
  • 4. The current market landscape is characterized by the presence large companies (more than 500 employees,27%), mid-sized companies (50-500 employees, 30%), and small-sized companies (less than 50 employees, 43%). The majority of these companies (~60%) are located in North America; examples of players based in this region include (in alphabetical order, no specific selection criteria) Allscripts, Cota Healthcare, Decision Resources Group, Ephicacy, Indegene, Knowledgent, MarkLogic, PerkinElmer, Pharmerit, SAS Institute, and Vector Oncology.
  • 5. Extensive research efforts in this domain is reflected in the fact that over 500 scientific articles have been published since 2016. It is worth noting that, in 2018 (till June) alone, close to 180 articles were published related to the ongoing real world data-based research. Industry stakeholders that have made significant contributions to the intellectual capital in this domain include (in decreasing order of number of publications) Merck, IQVIA, GlaxoSmithKline, Eli Lilly, Novartis, PPD (Evidera), Janssen Pharmaceutica, AstraZeneca, Amgen, and Pfizer.
  • 6. More than 1,000 clinical studies, conducted in real world setting, have been registered (completed / ongoing / planned) across different geographies. Based on the number of trials, North America (~460 trials) has emerged as a major research / innovation hub in this domain. It is also worth highlighting that a relatively larger proportion of the trials evaluated patients suffering from oncological disorders, cardiovascular disorders, neurological and psychiatric disorders.
  • 7. The real world evidence solutions market is expected to grow at an annualized rate of 14.1% between 2018 and 2030. While the current opportunity of real world evidence is maximum in post-approval studies, its scope in early stage research and clinical development is anticipated to grow at a relatively faster rate in the forecast period. Further, North America and Europe presently dominate the market and are expected to retain the leading position over the next decade. This is followed by Asia-Pacific and the rest of the world, which currently captures around 10% of the overall market share. We are led to believe that this trend is not likely to change significantly in the foreseen future.

Research Methodology:

The research, analysis and insights presented in this report are backed by a deep understanding of insights gathered from both secondary and primary sources. For all our projects, we conduct interviews with experts in the area (academia, industry and other associations) to solicit their opinions on emerging trends in the market. This is primarily useful for us to draw out our own opinion on how the market will evolve across different regions and technology segments. Where possible, the available data has been checked for accuracy from multiple sources of information.

The secondary sources of information include:

  • Annual reports
  • Investor presentations
  • SEC filings
  • Industry databases
  • News releases from company websites
  • Government policy documents
  • Industry analysts' views

While the focus has been on forecasting the market till 2030, the report also provides our independent view on various non-commercial trends emerging in the industry. This opinion is solely based on our knowledge, research and understanding of the relevant market gathered from various secondary and primary sources of information.

Chapter Outlines:

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), Mark Cziraky (Vice President of Research, HealthCore), 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
Product Code: RA100C02

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. Mark Cziraky, Vice President of Research, HealthCore
  • 14.5. 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

Company Listed:

The following companies / institutes / government bodies and organizations have been mentioned in this report.

  • 1. 23andMe
  • 2. 8KMiles
  • 3. Abbott
  • 4. AbbVie
  • 5. Acceliant
  • 6. Accenture
  • 7. Accsight
  • 8. Adarna Health Data
  • 9. Adelphi Real World
  • 10. Advera Health Analytics
  • 11. Aetion
  • 12. Allscripts
  • 13. Amazon Web Services
  • 14. American College of Cardiology
  • 15. American Diabetes Association
  • 16. Amgen
  • 17. Ana Health
  • 18. Analytica Laser
  • 19. Anthem
  • 20. Apple
  • 21. Arcana Institute
  • 22. Astellas Pharma
  • 23. AstraZeneca
  • 24. Axonal-Biostatem
  • 25. Axtria
  • 26. Bayer
  • 27. BC Platforms
  • 28. Biogen
  • 29. Boehringer Ingelheim
  • 30. Boston Health Economics
  • 31. Boston Scientific
  • 32. Bristol-Myers Squibb
  • 33. Cambridge Healthtech Institute
  • 34. CardioVascular Research Foundation
  • 35. CareFacets
  • 36. Caros Connect
  • 37. CBI
  • 38. Cegedim Strategic Data
  • 39. Centers for Disease Control and Prevention
  • 40. Chinese Academy of Medical Sciences
  • 41. CitiusTech
  • 42. CK Aspire
  • 43. Clarivate Analytics
  • 44. Clinakos
  • 45. ClinaMetrics
  • 46. Clinerion
  • 47. Clinical Trial EndPoint
  • 48. Clinigen Group
  • 49. Cloudera
  • 50. CloudMoyo
  • 51. Cogentia Healthcare Consulting
  • 52. Cognizant
  • 53. Conference Series
  • 54. ConvergeHEALTH
  • 55. Cota Healthcare
  • 56. Crossix Solutions
  • 57. Custodix
  • 58. D Cube Analytics
  • 59. Daichii Sankyo
  • 60. Data2Life
  • 61. Databricks
  • 62. Decision Driver Analytics
  • 63. Decision Resources
  • 64. Defense Intelligence Agency
  • 65. DIGIPHARM
  • 66. Digital Health Labs
  • 67. Drug Intelligence
  • 68. Duke University
  • 69. Dycros
  • 70. Edwards Lifesciences
  • 71. Eli Lilly
  • 72. Elligo Health Research
  • 73. Ephicacy
  • 74. EPID Research
  • 75. ESiOR
  • 76. European Medicines Agency
  • 77. Eurotrials
  • 78. Evidence Based Solutions
  • 79. Evidera
  • 80. evoMetrics
  • 81. Ernst & Young
  • 82. eyeforpharma
  • 83. Flatiron Health
  • 84. Flex
  • 85. Fuzzy Logix
  • 86. Genentech
  • 87. Genospace
  • 88. GNS Healthcare
  • 89. Google
  • 90. GlaxoSmithKline
  • 91. Harvard Medical School
  • 92. Healint
  • 93. Health IQ
  • 94. Health Solutions
  • 95. Healthagen
  • 96. HealthCore
  • 97. Healthing Research
  • 98. HealThink
  • 99. HealthVerity
  • 100. Humana
  • 101. Huron Consulting
  • 102. IBM Watson Health
  • 103. ICON
  • 104. Ignite Data
  • 105. Indegene
  • 106. Infosys
  • 107. Ingress Health
  • 108. InnoWin
  • 109. Inovalon
  • 110. Insight Pharmaceuticals
  • 111. Institute for Quality and Efficiency in Health Care
  • 112. Insys Group
  • 113. Intel
  • 114. International Society for Pharmacoeconomics and Outcomes Research
  • 115. IntrinsiQ Specialty Solutions
  • 116. IQVIA
  • 117. iwantGreatCare
  • 118. Janssen Pharmaceutica
  • 119. Johaus Global
  • 120. Johnson & Johnson
  • 121. Kaiku Health
  • 122. Kantar Health
  • 123. Karolinska Institutet
  • 124. Keedio
  • 125. Keyrus Biopharma
  • 126. Knowledgent
  • 127. Koneksa Health
  • 128. Kx Systems
  • 129. Lifecode Solutions
  • 130. Linguamatics
  • 131. LINK Medical Research
  • 132. Lundbeck
  • 133. LynxCare
  • 134. M2Gen
  • 135. M2S
  • 136. MA Provider
  • 137. MakroCare
  • 138. Mapi Group
  • 139. MarkLogic
  • 140. MarksMan Healthcare Communications
  • 141. Massachusetts General Hospital
  • 142. MaxisIT
  • 143. Mayo Clinic
  • 144. McKesson
  • 145. MDC Partners
  • 146. MeaningCloud
  • 147. Medaffcon
  • 148. Med-eShare
  • 149. MedEngine
  • 150. Medical Wisdom Consulting Group
  • 151. Medidata Solutions
  • 152. Medlior Health Outcomes Research
  • 153. Medpace
  • 154. MedStreaming
  • 155. Medtronic
  • 156. Merck
  • 157. Mercy
  • 158. MyOwnMed
  • 159. mySugr
  • 160. Northern Alberta Clinical Trials and Research Centre
  • 161. National Academies of Sciences, Engineering and Medicine
  • 162. National Cancer Institute
  • 163. National Institutes of Health
  • 164. National Institute of Mental Health
  • 165. National Institute on Drug Abuse
  • 166. National Investigation Agency
  • 167. New England Research Institute
  • 168. New York Heart Association
  • 169. NJ YZ Clinical Trials and Consulting
  • 170. Novartis
  • 171. Novo Nordisk
  • 172. Numerus
  • 173. Observational and Pragmatic Research Institute
  • 174. Odysseus Data Services
  • 175. OKRA Technologies
  • 176. OM1
  • 177. Omega CRO
  • 178. Oncocare Health
  • 179. OncoStats
  • 180. Optra Systems
  • 181. Optum
  • 182. OptumInsight
  • 183. Oracle
  • 184. ORPHA Strategy Consulting
  • 185. OXON Epidemiology
  • 186. Palantir
  • 187. PAREXEL
  • 188. Patient-Centered Outcomes Research Institute
  • 189. PatientsLikeMe
  • 190. PatientSource
  • 191. Peking University
  • 192. Peripharm
  • 193. PerkinElmer
  • 194. Pfizer
  • 195. pH Associates
  • 196. Pharma Intelligence
  • 197. Pharmaceuticals and Medical Devices Agency
  • 198. Pharmerit International
  • 199. PHARMO Institute
  • 200. Pinscriptive
  • 201. Point-of-Care Partners
  • 202. PotentiaMED
  • 203. PRA Health Sciences
  • 204. Precision Digital Health
  • 205. Precision Health AI
  • 206. Premier
  • 207. Qlik
  • 208. Quantify Research
  • 209. Quantzig
  • 210. Raven Biosciences
  • 211. Real Consulting Data
  • 212. Real Life Sciences
  • 213. RealHealthData
  • 214. Revon Systems
  • 215. Roam
  • 216. Roche
  • 217. RxAnte
  • 218. S3 Connected Health
  • 219. Saama Technologies
  • 220. Sanofi
  • 221. SAS Institute
  • 222. Savana
  • 223. Sciensus
  • 224. Sciformix
  • 225. Self Care Catalysts
  • 226. Sentry Data Systems
  • 227. SHYFT Analytics
  • 228. Society of Thoracic Surgeons
  • 229. Sprim Advanced Life Sciences
  • 230. SQN Clinical
  • 231. St. Jude Medical
  • 232. Stanford University
  • 233. StatFinn
  • 234. Sutter Health
  • 235. SVMPharma
  • 236. Symphony Health Solutions
  • 237. Syneos Health
  • 238. Synergus
  • 239. Syntel
  • 240. Takeda Pharmaceutical
  • 241. Talking Medicines
  • 242. TCD Outcomes Research
  • 243. Techtrials International
  • 244. Tempus
  • 245. Terrapinn Holdings
  • 246. TFS
  • 247. TransMed Systems
  • 248. TriAxia Health
  • 249. TriNetX
  • 250. Truven Health Analytics
  • 251. T-Systems
  • 252. Turacoz Healthcare Solutions
  • 253. uMotif
  • 254. United BioSource
  • 255. University of Alabama
  • 256. University of California
  • 257. University of Louisville
  • 258. University of North Carolina
  • 259. University of Pennsylvania
  • 260. University of Pittsburgh
  • 261. University of Texas
  • 262. US Department of Defense
  • 263. VA Office of Research and Development
  • 264. Validic
  • 265. Vector Oncology
  • 266. Verana Health
  • 267. Vestrum Health
  • 268. Vitaccess
  • 269. Vital Statistics Consulting
  • 270. Washington University School of Medicine
  • 271. Wellframe
  • 272. West Monroe Partners
  • 273. Wipro
  • 274. World Congress
  • 275. Worldwide Clinical Trials
  • 276. Xcenda
  • 277. Yale University
  • 278. Zeblok
  • 279. ZEINCRO
  • 280. Zephyr Health
  • 281. ZS Associates
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