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

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

INTRODUCTION
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.

SCOPE OF THE REPORT
The ‘Pharmaceutical and Life Sciences 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)
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 (40%) and real world datasets (15%). 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 135 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 125) 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 150 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 (~67%), regulatory approval / reimbursement / market access (~59%), and early stage research (~57%).

4. The current market landscape is characterized by the presence large companies (more than 500 employees, 26%), mid-sized companies (50-500 employees, 31%), 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 14.6% 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 40% 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, 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.

LIST OF COMPANIES AND ORGANIZATIONS

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. RTI Health Solutions
218. RWE Genesys
219. RxAnte
220. S3 Connected Health
221. Saama Technologies
222. Sanofi
223. SAS Institute
224. Savana
225. Sciensus
226. Sciformix
227. Self Care Catalysts
228. Sentry Data Systems
229. SHYFT Analytics
230. Society of Thoracic Surgeons
231. Sprim Advanced Life Sciences
232. SQN Clinical
233. St. Jude Medical
234. Stanford University
235. StatFinn
236. Sutter Health
237. SVMPharma
238. Symphony Health Solutions
239. Syneos Health
240. Synergus
241. Syntel
242. Takeda Pharmaceutical
243. Talking Medicines
244. TCD Outcomes Research
245. Techtrials International
246. Tempus
247. Terrapinn Holdings
248. TFS
249. TransMed Systems
250. TriAxia Health
251. TriNetX
252. Truven Health Analytics
253. T-Systems
254. Turacoz Healthcare Solutions
255. uMotif
256. United BioSource
257. University of Alabama
258. University of California
259. University of Louisville
260. University of North Carolina
261. University of Pennsylvania
262. University of Pittsburgh
263. University of Texas
264. US Department of Defense
265. VA Office of Research and Development
266. Validic
267. Vector Oncology
268. Verana Health
269. Vestrum Health
270. Vitaccess
271. Vital Statistics Consulting
272. Washington University School of Medicine
273. Wellframe
274. West Monroe Partners
275. Wipro
276. World Congress
277. Worldwide Clinical Trials
278. Xcenda
279. Yale University
280. Zeblok
281. ZEINCRO
282. Zephyr Health
283. ZS Associates


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
3.1.3. Role of Randomized Clinical Trials
3.1.4. 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 Trials 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
4.4.2. The Canadian Scenario
4.4.2.1. Data Governance
4.4.2.2. Regulatory Framework
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
4.5.2. The German Scenario
4.5.2.1. Data Governance
4.5.2.2. Regulatory Framework
4.5.3. The French Scenario
4.5.3.1. Data Governance
4.5.3.2. Regulatory Framework
4.5.4. The Spanish Scenario
4.5.5. The Italian Scenario
4.6. Data Governance and Regulatory Framework in Asia-Pacific
4.6.1. The Australian Scenario
4.6.2. The Chinese Scenario
4.6.3. The Japanese Scenario
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 Area
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. Analysis by Focus Areas
6.3.8. 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. Geographical Analysis by Number of Clinical Trials
7.3.3. Geographical Analysis by 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. Real World Evidence: SWOT Analysis
10.2.1. 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 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. Role of Real World Data in Shaping Healthcare Decision-making
Figure 3.2. Common Types of Chronic Disorders and their Rapidly Increasing Prevalence
Figure 3.3. Drug Development Costs: Historical Trend (USD Million)
Figure 3.4. Limitations of Randomized Clinical Trials
Figure 3.5. Traditional Development Model versus Outcomes-based Development Model
Figure 3.6. Process of Generating Evidence from Real World Data
Figure 3.7. Real World Data Sources
Figure 3.8. Different Constituents of Real World Data Sources
Figure 3.9. Comparison of Randomized Clinical Trials and Real World Evidence
Figure 3.10. Potential Applications of Real World Evidence
Figure 3.11. Summary of Potential Applications of Real World Evidence across Different Stages of Drug Development and Commercialization
Figure 3.12. 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 4.3. Emergence of Real World Evidence in China
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 5.7. Real World Evidence Solution Providers, Grid Analysis: Distribution by Company Size, Type of Offering and Applications of Real World Evidence
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: Distribution by Registration Year and Key Therapeutic Areas
Figure 7.17. Clinical Trials: Leading Indications in Terms of Number of Trials Conducted
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, 2013-2017
Figure 8.2. Trends on Social Media: Cumulative 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, H1 2017-H2 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 Other Types of Data, 2018-2030 (USD Million)
Figure 12.7. Real World Evidence Market Opportunity in Cardiovascular Disorders, 2018-2030 (USD Million)
Figure 12.8. Real World Evidence Market Opportunity in Infectious Diseases, 2018-2030 (USD Million)
Figure 12.9. Real World Evidence Market Opportunity in Metabolic Disorders, 2018-2030 (USD Million)
Figure 12.10. Real World Evidence Market Opportunity in Neurological / Psychiatric Disorders, 2018-2030 (USD Million)
Figure 12.11. Real World Evidence Market Opportunity in Oncological Disorders, 2018-2030 (USD Million)
Figure 12.12. Real World Evidence Market Opportunity in Other Types of Disorders, 2018-2030 (USD Million)
Figure 12.13. Real World Evidence Market Opportunity in Early Stage Research, 2018-2030 (USD Million)
Figure 12.14. Real World Evidence Market Opportunity in Clinical Development, 2018-2030 (USD Million)
Figure 12.15. Real World Evidence Market Opportunity in Regulatory Approval, 2018-2030 (USD Million)
Figure 12.16. Real World Evidence Market Opportunity in Pricing / Reimbursement, 2018-2030 (USD Million)
Figure 12.17. Real World Evidence Market Opportunity in Post-Approval Studies, 2018-2030 (USD Million)
Figure 12.18. Real World Evidence Market Opportunity in North America, 2018-2030 (USD Million)
Figure 12.19. Real World Evidence Market Opportunity in Europe, 2018-2030 (USD Million)
Figure 12.20. Real World Evidence Market Opportunity in Asia-Pacific, 2018-2030 (USD Million)
Figure 12.21. 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 Average Budget Allocated by Big Pharmaceutical Companies
LIST OF TABLES
Table 3.1. High Value Real World Data Pools Accumulated by Developed Countries
Table 3.2. Primary Elements of Different Sources of Real World Data
Table 3.3. Overview of Strengths and Limitations of Different Sources of Real World Data
Table 3.4. Real World Evidence Opportunities in Pharmaceutical and Medical Device Industries
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 9.1. List of Global Real World Evidence Events
Table 12.1. Real World Evidence Use Cases, 2016-H1 2018
Table 13.1. Survey Insights: Overview of 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: Average Budget Allocated by Big Pharmaceutical Companies
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
Status
Table 15.23. Clinical Trials: Distribution by Type of Study
Table 15.24. Clinical Trials: Distribution by Registration Year and Type of Study
Table 15.25. Clinical Trials: Distribution by Type of Sponsors / Collaborators
Table 15.26. Clinical Trials: Most Active Industry Players in Terms of Number of Trials Conducted
Table 15.27. Clinical Trials: Most Active Non-Industry Players in Terms of Number of Trials Conducted
Table 15.28. Clinical Trials: Distribution by Therapeutic Areas
Table 15.29. Clinical Trials: Leading Indications in Terms of Number of Trials Conducted
Table 15.30. Clinical Trials: Distribution by Registration Year and Key Therapeutic Areas
Table 15.31. Clinical Trials: Year-wise Trend of Trials Conducted by Leading Industry Players, 2013-2018
Table 15.32. Clinical Trials: Benchmarking of Leading Industry Players by Number of Trials across Key Therapeutic Areas
Table 15.33. Trends on Social Media: Year-wise Analysis by Volume, 2013-2018
Table 15.34. Global Events: Cumulative Quarter-wise Trend, Q1 2017-Q2 2018
Table 15.35. Global Events: Distribution by Location
Table 15.36. Global Events: Distribution by Type
Table 15.37. Global Events: Most Active Event Organizers
Table 15.38. Global Events: Most Active Industry Players in Terms of Event Participation
Table 15.39. Global Events: Most Active Non-Industry Players in Terms of Event Participation
Table 15.40. Global Events: Distribution by Designations of Event Participants
Table 15.41. Global Events: Distribution by Affiliated Departments of Event Participants
Table 15.42. Global Real World Evidence Market Opportunity, 2018-2030 (USD Million)
Table 15.43. Real World Evidence Market Opportunity from Medical Claims Data, 2018-2030 (USD Million)
Table 15.44. Real World Evidence Market Opportunity from Clinical Trials Data, 2018-2030 (USD Million)
Table 15.45. Real World Evidence Market Opportunity from Clinical Settings Data, 2018-2030 (USD Million)
Table 15.46. Real World Evidence Market Opportunity from Patient-Powered Data, 2018-2030 (USD Million)
Table 15.47. Real World Evidence Market Opportunity from Other Types of Data, 2018-2030 (USD Million)
Table 15.48. Real World Evidence Market Opportunity in Cardiovascular Disorders, 2018-2030 (USD Million)
Table 15.49. Real World Evidence Market Opportunity in Infectious Diseases, 2018-2030 (USD Million)
Table 15.50. Real World Evidence Market Opportunity in Metabolic Disorders, 2018-2030 (USD Million)
Table 15.51. Real World Evidence Market Opportunity in Neurological / Psychiatric Disorders, 2018-2030 (USD Million)
Table 15.52. Real World Evidence Market Opportunity in Oncological Disorders, 2018-2030 (USD Million)
Table 15.53. Real World Evidence Market Opportunity in Other Types of Disorders, 2018-2030 (USD Million)
Table 15.54. Real World Evidence Market Opportunity in Early Stage Research, 2018-2030 (USD Million)
Table 15.55. Real World Evidence Market Opportunity in Clinical Development, 2018-2030 (USD Million)
Table 15.56. Real World Evidence Market Opportunity in Regulatory Approval, 2018-2030 (USD Million)
Table 15.57. Real World Evidence Market Opportunity in Pricing / Reimbursement, 2018-2030 (USD Million)
Table 15.58. Real World Evidence Market Opportunity in Post-Approval Studies, 2018-2030 (USD Million)
Table 15.59. Real World Evidence Market Opportunity in North America, 2018-2030 (USD Million)
Table 15.60. Real World Evidence Market Opportunity in Europe, 2018-2030 (USD Million)
Table 15.61. Real World Evidence Market Opportunity in Asia-Pacific, 2018-2030 (USD Million)
Table 15.62. Real World Evidence Market Opportunity in Rest of the World, 2018-2030 (USD Million)
Table 15.63. Survey Insights: Distribution by Type of Organization
Table 15.64. Survey Insights: Distribution by Location of Organization
Table 15.65. Survey Insights: Distribution by Seniority Level
Table 15.66. Survey Insights: Distribution by Type of Offering
Table 15.67. Survey Insights: Distribution by Sources of Real World Data
Table 15.68. Survey Insights: Distribution by Purpose of Real World Evidence Generation
Table 15.69. Survey Insights: Distribution by Key Challenges
Table 15.70. Survey Insights: Distribution by Extent of Outsourcing
Table 15.71. Survey Insights: Distribution by Current Market Opportunity

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