Blockchain in Genomic Data Management: Market Landscape and Competitive Insights, 2018-2030

  • ID: 4703850
  • Report
  • 156 Pages
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It is Estimated that, by 2025, Around 15% of the World’s Population will Have had Their Genomes Sequenced, Resulting in the Generation of Several Zettabytes of Data

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The success of the Human Genome Project resulted in the generation of large volumes of genomic data, which is extensively used in biotechnology and medical research. Further, advancements in high throughput gene sequencing technologies have enabled scientists to expedite the genome sequencing process, and achieve significant cost benefits as well. In fact, it is estimated that, by 2025, around 15% of the world’s population will have had their genomes sequenced, resulting in the generation of several zettabytes of data. However, currently, there are not many reliable and secure data management resources that offer secure storage, seamless exchange of information, and a reliable transaction platform, for large volumes of genomic and clinical data. Therefore, at this stage, it has become important to develop and establish the necessary tools and technologies to effectively help with the processing and analysis of the aforementioned information and for making it easily accessible to practicing physicians, scientists, pharmaceutical companies and other stakeholders.

The blockchain technology has emerged as a viable option to store/exchange genomic data. The decentralized information management model used in blockchains has demonstrated significant benefits in banking and the fintech industry. Moreover, cryptocurrencies, which are based on the blockchain technology, are considered to be a powerful tool for peer-to-peer transactions without involving a third party to track the exchange. In the field of genomics, blockchain can act as a trusted means of carrying out transactions between data owners and data users (research groups/pharmaceutical companies). Moreover, such platforms enable easy access to genomic datasets, thereby, significantly improving the information procurement process for research studies related to personalized drugs/therapies. As a result, many companies have undertaken initiatives to promote the use of blockchain technology for genomic data management. In fact, the growing importance of blockchain for managing genetic information and using it in healthcare decision-making is also evident in the number of tweets (~1,750) posted on the social media platform, Twitter, in the recent years. In the past few years, recent activities in this domain, such as the establishment of strategic partnerships (involving pharmaceutical players and relevant government bodies) and investments by venture capital/other stakeholders, indicate that the concept of using blockchain platforms for the storage and management of genetic information is gaining traction in the healthcare industry. We believe that such efforts are likely to boost the overall growth of this market in the coming years.

The ‘Blockchain in Genomic Data Management: Market Landscape and Competitive Insights, 2018-2030’ report features an extensive study on the industry players that are offering blockchain platforms for the storage and management of genomic data. Amongst other elements, the report features:

  • An overview of the current status of the market with respect to companies providing blockchain platforms, along with information on year of establishment, geographical location, company size, type of business model used, types of services offered to data owners and data users (pharmaceutical companies/research institutes), proprietary blockchain platforms and utility tokens, and end-users (pharmaceutical companies, research institutes, genomic data providers (patients and healthy individuals), software developers, and insurers).
  • Tabulated profiles of all the players engaged in this field, featuring a brief overview of the company, and details on funding (if available), types of service(s) offered, proprietary blockchain platforms and utility tokens, key historical milestones, information on partnership(s) (if available), recent development(s) and roadmaps/future plans (if available).
  • An analysis of the prevalent and emerging trends related to this domain as represented on the social media platform, Twitter, highlighting the most frequently talked about utility tokens, active players, and influential authors. It includes an insightful sentiment analysis, summarizing the impact/influence of various tweets posted on the platform.
  • A comparative analysis of the needs of different stakeholders (pharmaceutical companies, research institutes, patients, healthy individuals, insurers and government agencies) in this industry.
  • A detailed analysis highlighting the various business models and go-to-market strategies adopted by companies involved in this space. It features details on the various channels adopted/being adopted by companies to raise awareness and promote the use of their proprietary products/services.
  • An informative bubble analysis, highlighting the market capitalization of the utility tokens of different companies engaged in this domain, based on total maximum supply, circulating supply and token price.
  • A list of recent use cases of blockchain platforms, by pharmaceutical companies, highlighting the ways in which such tools/services have been used to manage and analyze genomic data.
  • An insightful opportunity analysis, featuring an estimation of the existing market size; based on multiple parameters, we have also provided an informed estimate on the potential growth opportunities for companies engaged in this domain over the period 2018-2030.
  • An analysis of various developments/recent trends related to companies offering blockchain platforms for genomic data management, offering insights on [A] instances wherein companies have raised funds to support their respective initiatives, [B] partnership and collaborations established within the industry, [C] other initiatives undertaken by different companies, [D] recent global events (summits, conferences, and annual meetings), and [E] views expressed/opinions of selected key opinion leaders/industry experts on social media platforms, such as YouTube.

The opinions and insights presented in this study were also influenced by discussions conducted with several stakeholders in this domain. The report features detailed transcripts of interviews held with the following individuals:

  • David Koepsell (Chief Executive Officer, EncrypGen)
  • Jake Dreier (Director of Growth and Operations, SimplyVital Health)
  • Aldo de Pape (Chief Executive Officer, Genomes.io) and Louis Gooden (Analyst, Genomes.io)

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:

  • The current market landscape is relatively niche with a limited number of companies offering blockchain platforms for genomic data management. Of the total number of players involved, more than 35% are based in North America, primarily in the US. Examples of players based in this region include (in alphabetical order, no specific selection criteria) EncrypGen, GnoMine, LunaDNA, and Nebula Genomics. It is worth highlighting that companies are also based in developing regions, such as Brazil, India, Israel, Russia, Singapore, and South Korea.
  • Majority of the companies (86%) are involved in offering services primarily to pharmaceutical players and research institutes. In addition, the companies also offer genomic data management through blockchain platforms to other key stakeholders such as data owners, software developers, and insurers.
  • All the companies engaged in this domain offer genomic data sharing/transfer service to both data owners and data buyers. In addition, companies also claim to offer services, such as genomic data storage (87%), full data anonymity (87%), incentives for sharing their genomic data (87%), full genome sequencing (53%) and genetic counseling (27%), exclusively to data owners. Further, the services offered to data buyers include access to genomic datasets and genomic data analysis.
  • An analysis of over 1,750 tweets on social media platforms, and the opinions expressed by industry experts highlight the unaddressed concerns related to genomic data management; these include privacy issues, unsafe transactions, and lack of safety/reliability related to stored genomic data. It is worth mentioning that these challenges can be addressed via exchanging data on blockchain platforms. A comprehensive sentiment analysis of the tweets demonstrated that 85% were positive, suggesting that, at this stage, stakeholders are optimistic regarding the future potential of blockchain platforms for managing genomic data.
  • In order to enhance the adoption of blockchain platforms in genomic data management, stakeholders in the industry are exploring a variety of innovative marketing strategies. The most popular marketing strategies that are being implemented include the use of social media platforms to spread awareness related to blockchain platforms, online media and increasing participation in global events, such as conferences, to gain the required visibility in the market.
  • The overall coin market capitalization is currently estimated to be around USD 400 million-USD 750 million, based on total maximum supply, circulation supply, and the price (in USD) of the utility tokens of different companies engaged in this domain. Considering that such platforms are readily adopted within the healthcare industry, the aforementioned value is anticipated to significantly increase in the long term.
  • Overall, the market for genomic data management using blockchain platforms is expected to grow at an annualized rate of 43.5% between 2018 and 2030. While the current opportunity is higher for applications related to the development of personalized medicines, its scope in other application areas (such as advanced genetic testing services and identification of genotypic markers to enable better diagnosis) is anticipated to grow at a relatively faster rate in the forecast period.
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1. Preface
1.1. Chapter Overview
1.2. Research Methodology
1.3. Chapter Outlines

2. Executive Summary

3. Introduction
3.1. Chapter Overview
3.2. Concept of Blockchain
3.3. Potential Applications of Blockchain in Healthcare Industry
3.4. Overview and Importance of Genomic Data
3.5. Historical Evolution of Genomic Testing
3.6. Need for Sharing Genomic Data on Blockchain Platforms
3.6.1. Process of Sharing Genomic Data on Blockchain Platforms
3.6.1.1. Role of Utility Tokens
3.6.1.2. Token Distribution Events
3.6.1.3. Role of Compression Tools
3.6.2. Controversies Related to Sharing Genomic Data on Blockchain Platforms
3.7. Advantages and Limitations of Sharing Genomic Data on Blockchain Platforms

4. Market Landscape
4.1. Chapter Overview
4.2. Blockchain in Genomic Data Management: List of Industry Players
4.2.1. Analysis by Year of Establishment
4.2.2. Analysis by Geographical Location
4.2.3. Analysis by Company Size
4.2.4. Analysis by Geographical Location and Year of Establishment
4.2.5. Analysis by Company Size and Geographical Location
4.2.6. Analysis by Type of Business Model
4.2.7. Analysis by Type of Services Offered
4.2.8. Analysis by Type of End-Users
4.2.9. Analysis by Type of Services Offered and Geographical Location
4.2.10. Analysis by Type of Services Offered and End-Users

5. Company Profiles
5.1. Chapter Overview
5.2. Block23
5.3. DNAtix
5.4. EncrypGen
5.5. Company 4
5.6. Company 5
5.7. Company 6
5.8. Company 7
5.9. Company 8
5.10. Company 9
5.11. Company 10
5.12. Company 11
5.13. Company 12
5.14. Company 13
5.15. Company 14
5.16. Company 15

6. Emerging Trends On Social Media
6.1. Chapter Overview
6.2. Blockchain in Genomic Data Management: Trends on Twitter
6.2.1. Historical Trends in Volume of Tweets
6.2.2. Cumulative Year-Wise Activity
6.2.3. Trending Words / Phrases on Twitter
6.2.4. Trending Utility Tokens on Twitter
6.2.5. Popular Players on Twitter
6.2.6. Most Prolific Contributors on Twitter
6.2.7. Sentiment Analysis
6.3. Concluding Remarks

7. Stakeholder Needs Analysis
7.1. Chapter Overview
7.2. Needs of Stakeholders (Pharmaceutical Companies / Research Institutes / Data Owners / Government Agencies / Insurers)
7.2.1. Qualitative Analysis of Existing and Future Needs

8. Go-To-Market Strategy
8.1. Chapter Overview
8.2. Blockchain in Genomic Data Management: Marketing Strategies
8.2.1. Participation in Global Events
8.2.2. Marketing on Social Media Platforms
8.2.3. Marketing on Online / Print Media Platforms
8.2.4. Adopting Strategic Business Models
8.2.4.1. B2C Business Model
8.2.4.2. B2B Business Model
8.2.4.3. C2B Business Model
8.2.5. Undertaking Promotional Activities
8.3. Concluding Remarks

9. Market Capitalization Analysis
9.1. Chapter Overview
9.2. Methodology
9.2.1. Key Assumptions
9.3. Market Capitalization Analysis for Different Utility Tokens: 3D Bubble Analysis
9.4. Concluding Remarks

10. Blockchain in Genomic Data Management Use Cases and Opportunity Assessment
10.1. Chapter Overview
10.2. Blockchain in Genomic Data Management: Use Cases
10.3. Blockchain in Genomic Data Management: Market Opportunity Assessment
10.3.1. Methodology and Key Assumptions
10.3.2. Blockchain in Genomic Data Management: Market Opportunity, 2018-2030

11. Recent Trends Analysis
11.1. Chapter Overview
11.2. Blockchain in Genomic Data Management: Venture Capital Funding Activity
11.2.1. Types of Funding
11.2.2. List of Funding and Investments
11.2.2.1. Summary of Funding and Investments
11.3. Blockchain in Genomic Data Management: Partnership Activity
11.3.1. List of Partnerships and Collaborations
11.3.1.1. Summary of Partnerships and Collaborations
11.4. Blockchain in Genomic Data Management: Recent News Activity
11.4.1. List of Recent News
11.4.1.1. Analysis by Key Focus Area
11.5. Blockchain in Genomic Data Management: Recent / Upcoming Global Events
11.5.1. List of Recent / Upcoming Global Events
11.5.1.1. Analysis by Year of Occurrence
11.5.1.2. Analysis by Geography
11.5.1.3. Analysis by Type of Event
11.6. Blockchain in Genomic Data Management: Transcripts of Public Discussions
11.6.1. Dennis Grishin, Chief Scientific Officer / Co-founder, Nebula Genomics
11.6.2. Henry Ines, Chief Executive Officer, Shivom
11.6.3. Ofer a Lidsky, Co-founder, Chief Executive Officer and Chief Technology Officer, DNAtix
11.6.4. David Kerr, Chief Executive Officer, Block23
11.6.5. Alex Gorbachev and Nikolay Kulemin, Co-founders, Zenome
11.7. Concluding Remarks

12. Executive Insights
12.1. Chapter Overview
12.2. EncrypGen
12.2.1. Company Snapshot
12.2.2. Interview Transcript: David Koepsell, Chief Executive Officer
12.3. SimplyVital Health
12.3.1. Company Snapshot
12.3.2. Interview Transcript: Jake Dreier, Director of Growth and Operations
12.4. Genomes.io
12.4.1. Company Snapshot
12.4.2. Interview Transcript: Aldo de Pape, Chief Executive Officer and Louis Gooden, Analyst

13. Appendix 1: Tabulated Data

14. Appendix 2: List of Companies and Organizations

List of Tables
Table 3.1 Applications of Blockchain in Various Industries
Table 3.2 Challenges and Solutions Related to Blockchain in Healthcare Industry
Table 4.1 Blockchain Genomic Companies: List of Industry Players
Table 4.2 Blockchain Genomic Companies: Information on Blockchain Platform and Utility Token
Table 4.3 Blockchain Genomic Companies: Information on Type of Services Offered
Table 4.4 Blockchain Genomic Companies: Information on Type of End-Users
Table 5.1 Block 23: Company Profile
Table 5.2 DNAtix: Company Profile
Table 5.3 EncrypGen: Company Profile
Table 5.4 Company 4: Profile
Table 5.5 Company 5: Profile
Table 5.6 Company 6: Profile
Table 5.7 Company 7: Profile
Table 5.8 Company 8: Profile
Table 5.9 Company 9: Profile
Table 5.10 Company 10: Profile
Table 5.11 Company 11: Profile
Table 5.12 Company 12: Profile
Table 5.13 Company 13: Profile
Table 5.14 Company 14: Profile
Table 5.15 Company 15: Profile
Table 8.1 Blockchain in Genomic Data Management: Summary of Marketing Strategies
Table 9.1 Relative Potential of Utility Tokens: Comparative Analysis
Table 10.1 Blockchain in Genomic Data Management: Use Cases, 2017-Q3 2018
Table 11.1 Blockchain in Genomic Data Management: Funding and Investments, 2017-Q3 2018
Table 11.2 Blockchain in Genomic Data Management: Partnerships and Collaborations, 2017-Q3 2018
Table 11.3 Blockchain in Genomic Data Management: Recent News Activity, 2017- Q3 2018
Table 11.4 Blockchain in Genomic Data Management: Recent / Upcoming Global Events, 2017-H1 2019
Table 12.1 SimplyVital Health: Key Highlights
Table 13.1 Blockchain Genomics Companies: Distribution by Year of Establishment
Table 13.2 Blockchain Genomics Companies: Distribution by Geographical Location
Table 13.3 Blockchain Genomics Companies: Distribution by Size
Table 13.4 Blockchain Genomics Companies: Distribution by Geographical Location and Year of Establishment
Table 13.5 Blockchain Genomics Companies: Distribution by Size and Geographical Location
Table 13.6 Blockchain Genomics Companies: Distribution by Type of Business Model
Table 13.7 Blockchain Genomics Companies: Distribution by Type of Services Offered
Table 13.8 Blockchain Genomics Companies: Distribution by Type of End-Users
Table 13.9 Trends on Social Media: Overview of Keywords
Table 13.10 Trends on Social Media: Cumulative Year-Wise Analysis by Volume, 2015-2018
Table 13.11 Trends on Social Media: Sentiment Analysis
Table 13.12 Go-to-Market Strategy: Commonly Used Social Media Platforms
Table 13.13 Go-to-Market Strategy: Commonly Used Online / Print Media Platforms
Table 13.14 Go-to-Market Strategy: Promotional Activities
Table 13.15 Market Capitalization Analysis for Utility Tokens: 3D Bubble Analysis based on Total Maximum Supply, Circulation Supply and Token Price
Table 13.16 Overall Market Capitalization Value: Likely Scenarios (USD Billion)
Table 13.17 Blockchain in Genomic Data Management Market Opportunity, 2018, 2024 and 2030: Conservative, Base and Optimistic Scenarios (USD Billion)
Table 13.18 Global Events: Cumulative Year-Wise Trend, 2017-H1 2019
Table 13.19 Global Events: Distribution by Location
Table 13.20 Global Events: Distribution by Type

List of Figures
Figure 3.1 Applications of Blockchain in Various Industries
Figure 3.2 Benefits of Analyzing Genomic Data
Figure 3.3 Traditional Method of Genomic Sequencing and Blockchain
Figure 3.4 Key Considerations for Sharing Genomic Data on Blockchain Platforms
Figure 3.5 Controversies Related to Sharing Genomic Data on Blockchain Platforms
Figure 3.6 Advantages and Limitations of Sharing Genomic Data on Blockchain Platforms
Figure 4.1 Blockchain Genomics Companies: Distribution by Year of Establishment
Figure 4.2 Blockchain Genomics Companies: Distribution by Geographical Location
Figure 4.3 Blockchain Genomics Companies: Distribution by Size
Figure 4.4 Blockchain Genomics Companies: Distribution by Geographical Location and Year of Establishment
Figure 4.5 Blockchain Genomics Companies: Distribution by Size and Geographical Location
Figure 4.6 Blockchain Genomics Companies: Distribution by Type of Business Model
Figure 4.7 Blockchain Genomics Companies: Distribution by Type of Services Offered
Figure 4.8 Blockchain Genomics Companies: Distribution by Type of End-Users
Figure 4.9 Blockchain Genomics Companies: Heat Map Analysis by Type of Services Offered and Geographical Location
Figure 4.10 Blockchain Genomics Companies: Heat Map Analysis by Type of Services Offered and End-Users
Figure 6.1 Trends on Social Media: Overview of Keywords
Figure 6.2 Trends on Social Media: Historical Activities on Twitter, 2015-2018
Figure 6.3 Trends on Social Media: Cumulative Year-Wise Analysis by Volume, 2015-2018
Figure 6.4 Trends on Social Media: Popular Words / Phrases on Twitter
Figure 6.5 Trends on Social Media: Popular Utility Tokens on Twitter
Figure 6.6 Trends on Social Media: Popular Players on Twitter
Figure 6.7 Trends on Social Media: Most Prolific Contributors
Figure 6.8 Trends on Social Media: Most Influential Contributors
Figure 6.9 Trends on Social Media: Sentiment Analysis
Figure 7.1 Stakeholder Needs Analysis: Summary of Existing and Future Needs
Figure 7.2 Stakeholder Needs Analysis: Qualitative Assessment
Figure 7.3 Stakeholder Needs Analysis: Distribution by Priority
Figure 8.1 Go-to-Market Strategy: Commonly Used Social Media Platforms
Figure 8.2 Go-to-Market Strategy: Commonly Used Online / Print Media Platforms
Figure 8.3 Go-to-Market Strategy: Promotional Activities
Figure 9.1 Market Capitalization Analysis for Utility Tokens: 3D Bubble Analysis based on Total Maximum Supply, Circulation Supply and Token Price
Figure 9.2 Overall Market Capitalization Value: Likely Scenarios (USD Billion)
Figure 10.1 Blockchain in Genomic Data Management Market Opportunity, 2018-2030: Base Scenario (USD Billion)
Figure 10.2 Blockchain in Genomic Data Management Market Opportunity, 2018, 2024 and 2030: Conservative, Base and Optimistic Scenarios (USD Billion)
Figure 11.1 Summary of Funding and Investments, 2017-Q3 2018 (USD Million)
Figure 11.2 Summary of Partnerships and Collaborations, 2017-Q3 2018
Figure 11.3 Recent News Activity: Key Focus Areas
Figure 11.4 Global Events: Cumulative Year-Wise Trend, 2017-H1 2019
Figure 11.5 Global Events: Distribution by Location
Figure 11.6 Global Events: Distribution by Type

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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 blockchain technology in genomic data management market in the short to mid-term and long-term.

Chapter 3 is an introductory chapter that provides a brief overview of the concept of blockchain technology and its applications in various sectors, with a detailed discussion on the applications and the challenges related to the use of blockchain technology in the healthcare industry. The chapter includes a discussion on the historical evolution in the area of genetic sequencing and genetic testing and provides information on the growing importance of sharing /storing/analyzing genomic information through blockchain platforms. Further, it presents a brief overview of the cryptocurrencies and utility tokens, the process of token distribution events and the role of compression tools for analyzing huge volume of genomic data. The chapter also highlights the various advantages and limitations associated with the use of blockchain platforms for managing/analyzing genomic data.

Chapter 4 includes a comprehensive market landscape analysis of companies offering blockchain platforms for the storage and management of genomic data. The chapter features analysis of these players on the basis of their year of establishment, geographical location, company size, type of business model used, types of services offered (such as genomic data protection / storage, full genomic sequencing, genetic counselling, genomic data analysis and others), proprietary blockchain platforms and utility tokens, and end-users (pharmaceutical companies, research institutes, genomic data providers (patients and healthy individuals), software developers, and insurers.

Chapter 5 provides tabulated profiles of all the players engaged in this field. Each profile features details on company headquarters, year of establishment, number of employees, key executives, funding (if available), types of service(s) offered, proprietary blockchain platforms and utility tokens, key historical milestones, information on partnership(s) (if available), recent development(s), and roadmaps / future plans (if available).

Chapter 6 provides insights into the popularity of blockchain platforms, related to the storage and management of genomic data, on the social media platform, Twitter. The section highlights the quarterly distribution of tweets posted in the time period January 2015-August 2018, and the most significant events responsible for an increase in the volume of tweets each year. Additionally, the chapter showcases the most frequently mentioned keywords, most talked about utility tokens, and active players, on the social media platform. It elucidates the most prolific contributors and presents a bubble analysis of the most influential contributors related to this domain on Twitter. The chapter also presents an insightful sentiment analysis, summarizing the impact/influence of various tweets posted on the platform.

Chapter 7 presents information on the needs of different stakeholders (pharmaceutical companies, research institutes, patients, healthy individuals, insurers and government agencies) in this industry. The chapter qualitatively assesses the needs of each stakeholder group and the relative importance of their expectations within this domain.

Chapter 8 features a detailed case study highlighting the go-to-market strategies adopted by companies engaged in this space. It presents insightful information on important marketing strategies, such as inbound marketing through social media platforms and online/print media, promotional activities through official websites, and business models used by various players in the market.

Chapter 9 provides an insightful bubble analysis, highlighting the market capitalization of the companies engaged in this domain, based on their proprietary utility tokens. For the purpose of this analysis, we considered several relevant parameters, including total maximum supply, circulation supply, and token price (in USD), of each of the aforementioned utility tokens.

Chapter 10 provides a comprehensive list of recent use cases of blockchain platforms, by pharmaceutical companies, highlighting the ways in which such tools/services have been used to manage and analyze genomic data. In addition, the chapter presents an insightful opportunity analysis, featuring an estimation of the existing market size; based on multiple parameters, we have provided an informed estimate on the potential growth opportunities for companies engaged in this domain over the period 2018-2030.

Chapter 11 highlights a detailed assessment of various developments / recent trends related to companies offering blockchain platforms for genomic data management. This analysis presented in this chapter was focused on understanding the applications and challenges associated with the use of blockchain platforms for genomic data management and the future opportunity for these business models within the healthcare industry. The analysis offer insights on [A] instances wherein companies have raised funds to support their respective initiatives, [B] partnership and collaborations established within the industry, [C] other initiatives undertaken by different companies, [D] recent global events (summits, conferences, and annual meetings), and [E] views expressed / opinions of selected key opinion leaders/industry experts on social media platforms, such as YouTube.

Chapter 12 is a collection of executive insights of the discussions that were held with key stakeholders in this market. The chapter provides a brief overview of the companies and details of interviews held with David Koepsell (Chief Executive Officer, EncrypGen), Jake Dreier (Director of Growth and Operations, SimplyVital Health) and Aldo de Pape (Chief Executive Officer, Genomes.io) and Louis Gooden (Analyst, Genomes.io).

Chapter 13 is an appendix, which provides tabulated data and numbers for all the figures provided in the report.

Chapter 14 is an appendix, which contains the list of companies and organizations mentioned in the report.

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  • Genomes.io
  • GnoMine
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