Big Data: Embracing Data to Transform Healthcare and Pharma Commercial Strategy - Featuring Expert Panel Views from Industry Survey 2016

  • ID: 4035232
  • Report
  • Region: Global
  • 75 Pages
  • CBR Pharma Insights
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Understand the Views of 73 Organizations Within the Industry on Big Data, and Assess Real-World Case Studies

FEATURED COMPANIES

  • Allergan
  • AstraZeneca
  • Medtronic
  • Novartis
  • Novo Nordisk
  • Pfizer
  • MORE

Data generation is growing at an exponential rate, so much so that 90% of the data in the world today was created in the last two years (IBM, 2016a). Big Data refers to any data set that is too large to store, process or analyze using traditional database software and hardware. As with many other fields, the pharmaceutical and overall healthcare sector is becoming increasingly data-driven, with information being collected from a wide variety of sources. Big Data has a significant impact on all aspects of the pharmaceutical and healthcare sector, and companies are making large investments in technologies to leverage it more effectively.

Big Data and its place within healthcare is set to address problems within the industry, such as the rising costs of developing a single drug, which is currently estimated at USD2.6 Billion (Tufts CSDD, 2014), and the USD1 Trillion of healthcare spending in the US that has been labeled as ‘waste’ (Sahni et al., 2015).

Big Data is no longer an abstract concept that could provide benefits in the future. It exists now, and is already providing competitive advantages for a variety of organizations. As such, companies that ignore its potential risk falling behind their peers in our increasingly data-intensive world. This is demonstrated by results from our proprietary industry survey, which showed that 73% of organizations are set to begin investing in, or increase investment in Big Data within the next five years.

Furthermore, the our industry survey highlighted that the top three areas where organizations are currently implementing Big Data are clinical trials, real-world evidence, and sales, marketing and commercial. However, as mentioned, Big Data can be implemented within virtually every aspect of the healthcare industry, and the survey results show that even organizations already making use of it have a lot of room to grow.

The report “Big Data: Embracing Data to Transform Healthcare and Pharma Commercial Strategy - Featuring Expert Panel Views from Industry Survey 2016” provides an introduction to Big Data, defining its properties and its place within the healthcare landscape and examination of the multitude of data sources within healthcare that can be inputted into Big Data systems.

In particular, it provides the following analysis:

  • Provides an analytical review of the most important needs and trends driving the use of Big Data in the healthcare market.
  • Explores how different combinations of Big Data sources and analytical techniques could be used to provide direct benefits for pharmaceutical companies, healthcare institutions and patients.
  • Provides a detailed analysis of the various challenges associated with the use of Big Data.
  • Provides an examination of various real-world case studies of the use of Big Data within pharmaceutical companies and healthcare institutions to achieve a competitive advantage.
  • Examines the underlying architecture of Big Data systems, with an overview of popular platforms and tools used in the healthcare context.
  • Provides strategic considerations for the effective implementation of Big Data solutions in healthcare based on the totality of our industry survey results and a range of secondary and internal research.
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FEATURED COMPANIES

  • Allergan
  • AstraZeneca
  • Medtronic
  • Novartis
  • Novo Nordisk
  • Pfizer
  • MORE

1 Table of Contents
1.1 List of Tables
1.2 List of Figures

2 Big Data Overview
2.1 What is Big Data?
2.2 The ‘Three Vs’ of Big Data: Volume, Velocity and Variety
2.3 The Sources of Big Data in Healthcare
2.4 Big Data Lifecycle
2.5 How Prevalent is the use Big Data in Healthcare? Results from our Industry-Wide Survey

3 Drivers of Big Data in Healthcare
3.1 Advances in Technology: Explosion in Data Generation
3.1.1 Next-Generation Sequencing Technologies: Outpacing Moore’s Law
3.1.2 Proteomic Databases: ProteomicsDB Designed with Big Data Analytics in Mind
3.1.3 Electronic Health Records: A Form of Big Data
3.1.4 Social Media: Information That Cannot Be Found Anywhere Else
3.1.5 Devices: Smartphones, Wearables and Telemedicine Devices Represent a Continuous Source of Big Data
3.1.6 Cloud Technologies: Often Integral to Big Data
3.2 Needs and Trends Driving the Use of Big Data in Healthcare
3.2.1 Real-World Evidence: Data Outside of Clinical Trials
3.2.2 Value-Based Healthcare: Emphasizing Quality over Quantity
3.2.3 Personalized Medicine and Targeted Therapies: Transforming Healthcare
3.2.4 The R&D Productivity Gap
3.2.5 The Need to Increase Operational Efficiency and Reduce Operational Costs
3.3 What Are the Most Important Drivers? How Do Opinions Differ Between Different Groups and Regions? Results from Our Industry-Wide Survey

4 Commercial Implications of Big Data in Healthcare
4.1 Predictive Modeling: Fundamental Source of Big Data’s Power
4.1.1 Using Big Data for Patient-Specific Modeling: Potential for Huge Healthcare Savings
4.2 Big Data Unlocks the Potential of Personalized Medicine and Targeted Therapies
4.3 Utilizing the Unique Big Data Provided by Wearables and Fitness Trackers
4.4 Big Data for a More Systemic Approach to Drug Repositioning
4.5 Drug Discovery and Pre-Clinical Trials: Big-Data-Guided Drug Development
4.6 Leveraging Big Data to Overhaul the Clinical Trial Process
4.7 Implications for Real-World Evidence, Post-Approval Monitoring, Pharmacovigilance and Value-Based Healthcare
4.8 Actionable Insights for Sales and Marketing Processes
4.9 Improving Manufacturing Processes
4.10 In Which Healthcare Areas Do Organizations Currently Utilize Big Data? How Does This Differ between Regions? Results From Our Industry-Wide Survey
4.11 Where do Organizations Believe Big Data Will Have the Greatest Impact in the Next Five Years? Results From Our Industry Survey

5 Challenges Associated with Big Data in Healthcare
5.1 Data Quality: Analysis Output Can Only Be as Good as the Data Input
5.1.1 Does “Messy” Real-World Data Have a Place in Evidence-Based Medicine?
5.2 Data Silos: Organizations Not Willing to Share
5.3 Privacy, Security and Big Data: An Uneasy Relationship
5.3.1 Shortage of People with Relevant Skills
5.4 Technical and Infrastructure Challenges
5.5 What Are the Biggest Restraints Against the Use of Big Data in Healthcare? Results from Our Industry Survey
5.6 What Are the Particular Reasons Specific Organizations Have Not Implemented Big Data? Results from Our Industry Survey

6 Big Data in Practice: Real-World Case Studies and Technical Details
6.1 Big Pharma and Big Data: Various Technology Partnerships, including Roche, Allergan, AstraZeneca, Sanofi, Novartis, Teva, Medtronic, Novo Nordisk
6.2 Big Data Analytics: Underlying Architecture and Popular Platforms and Tools
6.3 Novartis: Overcoming the Challenge of Interacting with and Integrating Heterogeneous Big Data Sets to Ensure Competitive Advantage
6.4 Pfizer Combines Three Key Sources of Big Data to Create its Precision Medicine Analytics Ecosystem
6.5 Using Big Data to Prevent Pharmaceutical Counterfeiting and Fraud
6.6 Roche: Believes Big Data Presents a Huge Opportunity to Improve Treatments and Innovate
6.7 Advocate Health Care System Utilizes Big Data to Reduce Hospital Re-admissions by 20% within Three Months
6.8 Some 94% of Organizations that Use Big Data Are Likely to Increase their Investment within the Next Five Years According to our Industry-Wide Survey

7 Strategic Considerations for Effective Implementation of Big Data in Healthcare
7.1 Data Considerations when Designing a Big Data System: Focus on Optimizing Inputs
7.1.1 Data Collection: Strategies for Competitive Differentiation
7.1.2 In Summary: A Data Manifesto
7.2 Possible Big Data Ownership Structures within an Organization: Choose the Right One for You
7.3 Big Data Talent Can be both a Competitive Differentiator and Limiting Factor within Organizations
7.4 Treat Big Data Systems as an Ongoing Project that is Never Completed
7.5 Framework for Finding Business Use Cases for Big Data within your Organization
7.6 Big Data Landscape within Healthcare: Different Sectors are in Different Points of Progression
7.7 42% of Organizations Believe Big Data will Revolutionize Healthcare, According to our Industry-Wide Survey
7.8 Conclusion: Organizations that Ignore Big Data Risk Falling Behind

8 Appendix
8.1 Industry Survey: Breakdown of Respondents by General Industry
8.2 Industry Survey: Breakdown of Respondents by Specific Sector
8.3 Industry Survey: Breakdown of Respondents by Region
8.4 Industry Survey: Proportion of Healthcare Organizations that Currently Utilize Big Data
8.5 Industry Survey: Big Data Utilization in Healthcare, Comparison of Expert Panels from Europe, North America and Asia
8.6 Industry Survey: Most Important Factors Promoting the Use of Big Data in Healthcare
8.7 Industry Survey: Most Important Factors Promoting Big Data, Pharmaceutical Expert Panel vs Overall Healthcare Expert Panel
8.8 Industry Survey: Most Important Factors Promoting Big Data, Regional Breakdown
8.9 Industry Survey: Most Common Healthcare Areas for Big Data Implementation
8.10 Industry Survey: Extent of Utilization of Big Data across Organizations
8.11 Industry Survey: The Most Common Healthcare Areas in which Big Data is Currently Implemented, Europe vs North America
8.12 Industry Survey: Areas Where Big Data Will Have the Most Impact over the Next Five Years
8.13 Industry Survey: Most Important Restraints on the use of Big Data in Healthcare
8.14 Industry Survey, Most Important Restraints on Use of Big Data in Healthcare, Breakdown by Region
8.15 Industry Survey: Reasons Preventing Organizations from Implementing Big Data into their Business
8.16 Industry Survey: Likelihood of Organizations that Use Big Data Increasing Investment in the Technology in Next Five Years
8.17 Industry Survey: Likelihood of Organizations that do not use Big Data Increasing Investment in the Technology in Next Five Years
8.18 Industry Survey: Overall Stance of Organizations on the use of Big Data in Healthcare
8.19 References
8.20 Contact Us
8.21 Disclaimer

List of Tables
Table 1: Sources of Big Data in Healthcare
Table 2: Types of Technological Devices and the Information They Can Feed into Big Data Systems
Table 3: Summary of the Drivers and Needs Necessitating the Use of Big Data in Healthcare
Table 4: Summary of Challenges Associated with Big Data in Healthcare
Table 5: Selected Partnerships Between Pharma and Big Data, Technology Companies
Table 6: Platforms and Tools for Big Data Analytics in Healthcare
Table 7: Case Study, Novartis - Overcoming Big Data Challenges to Ensure Competitive Advantage
Table 8: Case Study, Pfizer’s Precision Medicine Analytics Ecosystem
Table 9: Case Study, Fortune 100 Company Uses Big Data to Protect Against Counterfeiting
Table 10: Case Study, Roche and Big Data - Four Key Areas of Work Identified by the Company
Table 11: Case Study, Selected Roche (France) Big Data Projects
Table 12: Case Study, How Advocate Health System Implemented Big Data to Reduce Hospital Re-admissions and Achieve Many Other Benefits
Table 13: Most Common Big Data Ownership Structures within Organizations
Table 14: Key Team Members within a Big Data Program
Table 15: Hype Cycle for Emerging Technologies

List of Figures
Figure 1: The ‘Three Vs’ of Big Data
Figure 2: Sources of Big Data in Healthcare
Figure 3: Typical Big Data Lifecycle
Figure 4: Industry Survey, Breakdown of Respondents by General Industry
Figure 5: Industry Survey, Breakdown of Respondents by Specific Sector
Figure 6: Industry Survey, Breakdown of Respondents by Region
Figure 7: Industry Survey, Proportion of Healthcare Organizations that Currently Utilize Big Data
Figure 8: Industry Survey, Big Data Utilization in Healthcare, Comparison of Expert Panels from Europe, North America and Asia
Figure 9: Cost of Sequencing a Human Genome, 2001-2015
Figure 10: Industry Survey, Most Important Factors Promoting the Use of Big Data in Healthcare
Figure 11: Industry Survey, Most Important Factors Promoting Big Data, Pharmaceutical Expert Panel vs Overall Healthcare Expert Panel
Figure 12: Industry Survey, Most Important Factors Promoting Big Data, Regional Breakdown
Figure 13: Using Big Data to Enable Predictive Analytics and Modeling
Figure 14: Insights Provided by Big Data for the Development of Personalized Medicines
Figure 15: Using Big Data for Drug Repositioning
Figure 16: Big-Data-Guided Drug Development and its Commercial Benefits
Figure 17: Using Big Data to Optimize Sales Force Coverage within Geographic Areas
Figure 18: Industry Survey, Most Common Healthcare Areas for Big Data Implementation
Figure 19: Industry Survey Results, Extent of Utilization of Big Data across Organizations
Figure 20: Industry Survey, Most Common Healthcare Areas for Big Data Implementation, Europe vs North America
Figure 21: Industry Survey: Areas Where Big Data Will Have the Most Impact over the Next Five Years
Figure 22: Industry Survey, Most Important Restraints on Use of Big Data in Healthcare
Figure 23: Industry Survey, Most Important Restraints on Use of Big Data in Healthcare, Breakdown by Region
Figure 24: Industry Survey, Reasons Preventing Organizations from Implementing Big Data into their Business
Figure 25: Underlying Architecture of Big Data Analytics
Figure 26: Industry Survey, Likelihood of Organizations that Use Big Data Increasing Investment in the Technology in Next Five Years
Figure 27: Industry Survey, Likelihood of Organizations that do not use Big Data Investing in the Technology in Next Five Years
Figure 28: Hype Cycle for Big Data within Healthcare: Different Sectors at Differing Points of Progression
Figure 29: Industry Survey, Overall Stance of Organizations on use of Big Data in Healthcare
Figure 30: Overview of Insights and Benefits Offered by Big Data
Figure 31: Industry Survey, Breakdown of Respondents by General Industry
Figure 32: Industry Survey, Breakdown of Respondents by Specific Sector
Figure 33: Industry Survey, Breakdown of Respondents by Region
Figure 34: Industry Survey, Proportion of Healthcare Organizations that Currently Utilize Big Data
Figure 35: Industry Survey, Big Data Utilization in Healthcare, Comparison of Expert Panels from Europe, North America and Asia
Figure 36: Industry Survey, Most Important Factors Promoting the Use of Big Data in Healthcare
Figure 37: Industry Survey, Most Important Factors Promoting Big Data, Pharmaceutical Expert Panel vs Overall Healthcare Expert Panel
Figure 38: Industry Survey, Most Important Factors Promoting Big Data, Regional Breakdown
Figure 39: Industry Survey, Most Common Healthcare Areas for Big Data Implementation
Figure 40:Industry Survey Results, Extent of Utilization of Big Data across Organizations
Figure 41: Industry Survey, Most Common Healthcare Areas for Big Data Implementation, Europe vs North America
Figure 42: Industry Survey, Areas Where Big Data Will Have the Most Impact over the Next Five Years
Figure 43: Industry Survey, Most Important Restraints on Use of Big Data in Healthcare
Figure 44: Industry Survey, Most Important Restraints on Use of Big Data in Healthcare, Breakdown by Region
Figure 45: Industry Survey, Reasons Preventing Organizations from Implementing Big Data into their Business
Figure 46: Industry Survey, Likelihood of Organizations that Use Big Data Increasing Investment in the Technology in Next Five Years
Figure 47: Industry Survey, Likelihood of Organizations that do not use Big Data Investing in the Technology in Next Five Years
Figure 48: Industry Survey, Overall Stance of Organizations on use of Big Data in Healthcare

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  • Allergan
  • AstraZeneca
  • Medtronic
  • Novartis
  • Novo Nordisk
  • Pfizer
  • Roche
  • Sanofi
  • Teva
Note: Product cover images may vary from those shown
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