Digital Twins Market by Therapeutic Area, Type of Digital Twin, Area of Application, End Users and Key Geographical Regions : Industry Trends and Global Forecasts, 2022-2035

The research and development behind a new drug is reported to require, on an average, an investment of nearly USD 1 billion. At present, over 90% of the drug candidates fail across different stages of clinical trials, leading to significant financial losses for developers. In recent years, with the introduction of industry 4.0 technologies, such as augmented reality, big data, internet of things (IoT) and virtual reality, the digital twins technology has emerged as a promising approach to mitigate a number of the aforementioned healthcare related concerns. Digital Twins refer to the virtual model of a physical object, process or service; such models are able to replicate real-life processes in order to collect real-time data to predict their performance. Further, digital twins have been shown to pace up the clinical trials and simulate studies for a larger population, in much quicker timelines. In fact, a group of researchers engaged in the classification of drug risks using digital twins claim that an extended version of the model could help save up to USD 2.5 billion spent on design and testing new drugs. Several digital twins have been found to be reliable in the diagnosis / treatment of various diseases and are, hence, expected to reduce the excessive cost spent on false medical diagnosis. It is worth mentioning that, on an annual basis, medical errors are expected to lead to a loss of nearly USD 20 billion in the US. Therefore, digital twins are believed to have the potential to enable significant cost savings. As a result, about 15% of organizations that implement IoT projects have already started using digital twin platforms, while over 60% of the firms are either planning or in the process of establishing digital twin technologies in their processes, in the near future.

Digital twin technology companies are currently engaged in the development of products which are intended for numerous applications, such as asset / process management, personalized treatment and surgical planning. Additionally, as mentioned earlier, a number of digital twin platforms have been found reliable in several healthcare applications, such as diagnosis, health monitoring and medical training. The growing interest in this market can also be validated from that fact that, in the last two years, close to USD 6 billion has been invested by several investors based across the globe, in companies engaged in the development or those offering digital twins. Interestingly, the partnership activity in the industry has also witnessed a growth rate of over 15%, in the past three years. It is also important to note that, over the past few years, there have been a significant innovation in this market space. For instance, in September 2022, European Medicines Agency (EMA) released a favorable qualification opinion for TwinRCT™ solution, for implementation in AI-generated prognostic digital twins being evaluated in phase II and phase III clinical trials. Considering the continuous innovation related to digital twins and a growing interest in automation and prognostic systems, we believe the digital twin market size is likely to evolve at a rapid pace, over the coming years.

SCOPE OF THE REPORT

The "Digital Twins Market, Distribution by Therapeutic Area (Cardiovascular Disorders, Metabolic Disorders, Orthopedic Disorders, and Other Disorders), Type of Digital Twin (Process Twins, System Twins, Whole Body Twins and Body Part Twins), Area of Application (Asset / Process Management, Personalized Treatment, Surgical Planning, Diagnosis and Other Applications), End Users (Pharmaceutical Companies, Medical Device Manufacturers, Healthcare Providers, Patients and Other End Users) and Key Geographical Regions (North America, Europe, Asia, Latin America, Middle East and North Africa, and Rest of the World): Industry Trends and Global Forecasts, 2022-2035" report features an extensive study of the current landscape, offering an informed opinion on the likely adoption of digital twins in the healthcare domain, till 2035. The report features an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this market space. Amongst other elements, the report includes:

An executive summary of the key insights captured during our research., offering a high-level view on the current state of the digital twins market and its likely evolution in the short to mid and long term.

A brief introduction to important concepts related to digital twins, featuring information on various types of digital twins and its primary applications in the healthcare domain. Further, this chapter features details related to the recent advancements that have been reported in this market space.

A detailed overview of the current market landscape of players engaged in the development of digital twins, along with information on their year of establishment, company size and location of headquarters. Further, it highlights a detailed assessment of the overall market landscape of digital twins in the healthcare domain, based on several relevant parameters, such as status of development (marketed and under development), therapeutic area (cardiovascular disorders, metabolic disorders, orthopedic disorders, and other disorders), area(s) of application (asset / process management, personalized treatment, surgical planning, diagnosis, health monitoring, clinical trials and medical training), type of technology used (artificial intelligence, virtual reality, augmented reality, blockchain and others), type of digital twin (body part twin, whole body twin, process twin and system twin) and end users (healthcare providers, pharmaceutical companies, medical device manufacturers, patients and others).

An in-depth analysis, highlighting the contemporary market trends, using five schematic representations, including a stacked bar chart representation (based on area(s) of application and status of development), a heat map representation (based on type of technology used and type of digital twin), a grid representation (based on type of end user and type of digital twin), a bar chart representation (based on area of application and location of headquarters), a hybrid chart representation comparing the players engaged in the digital twins in healthcare domain (based on company size and location of headquarters).

An insightful competitiveness analysis of players involved in the production / development of digital twins in the healthcare domain, based on several relevant parameters, such as years of experience, portfolio strength (in terms of number of products, status of development, area(s) of application, technology used, end user(s) and type of twin(s)), partnership strength (in terms of number of partnerships, year of partnerships, and type of partnership) and funding strength (in terms of number of funding instances, amount of funding, year of funding and type of funding).

Elaborate profiles of various prominent players that are currently engaged in the digital twins domain. Each company profile features a brief overview of the company (including information on its year of establishment, number of employees, location of headquarters and key members of the executive team), details related to its recent developments and an informed future outlook.

An insightful analysis of the partnerships inked between various stakeholders, during the period 2018-2022, covering acquisitions, mergers, development agreements, technology integration agreements and technology utilization agreements.

An analysis of funding and investments received by players engaged in digital twins domain, during the period 2018-2022, including grants, debt, seed funding, venture series, initial public offering, secondary offerings, private placements, private equity and other equity.

A proprietary analysis to evaluate start-ups engaged in this market space, by assigning monetary values to various competition differentiators possessed by a player, based on the Berkus start-up valuation parameters, including sound idea, prototype, management experience and strategic relationships undertaken by market players.

A detailed market forecast analysis, highlighting the likely growth of the digital twins market, for the period 2022-2035. Additionally, the report features the likely distribution of current and forecasted opportunity across various segments, such as therapeutic area (cardiovascular disorders, metabolic disorders, orthopedic disorders and other disorders), type of digital twin (process twins, system twins, whole body twins and body part twins), area(s) of application (asset / process management, personalized treatment, surgical planning, diagnosis and other applications), end users (pharmaceutical companies, medical device manufacturers, healthcare providers, patients and other end users) and key geographical regions (North America, Europe, Asia, Latin America, Middle East and North Africa and Rest of the World).

The opinions and insights presented in the report were influenced by discussions held with multiple stakeholders in this domain. The report features detailed transcripts of interviews held with several industry stakeholders.

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.

RESEARCH METHODOLOGY

The data presented in this report has been gathered via secondary and primary research. For all our projects, we conduct interviews with experts in the area (academia, industry, medical practice 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 over the coming 15 years, the report also provides our independent view on various technological and 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.

KEY QUESTIONS ANSWERED

What are digital twins?

Who are the leading players engaged in the development of digital twins for the healthcare domain?

Which type of digital twin is most commonly offered by developers engaged in this market space?

What is the relative competitiveness of different players engaged in the digital twins domain?

What is the likely valuation of start-ups involved in the development of digital twins for the healthcare sector?

What is the present and likely future demand for digital twins in the overall healthcare sector?

What are the anticipated future trends related to digital twins in the healthcare domain?

How is the current and future opportunity likely to be distributed across key market segments?

CHAPTER OUTLINES

Chapter 2 is an executive summary of the key insights captured during our research. It offers a high-level view on the current state of the digital twins market and its likely evolution in the short to mid and long term.

Chapter 3 is an introductory chapter that highlights important concepts related to digital twins. It also features information on various types of digital twins and its primary applications in healthcare domain. Further, this chapter features details about the recent advancements that have been reported in this market space.

Chapter 4 provides a detailed overview of the current market landscape of players engaged in the development of digital twins, along with information on their year of establishment, company size and location of headquarters. Further, it highlights a detailed assessment of the overall market landscape of digital twins in the healthcare domain, based on several relevant parameters, such as status of development (marketed and under development), therapeutic area (cardiovascular disorders, metabolic disorders, orthopedic disorders, and other disorders), area(s) of application (asset / process management, personalized treatment, surgical planning, diagnosis, health monitoring, clinical trials and medical training), type of technology used (artificial intelligence, virtual reality, augmented reality, blockchain and others), type of digital twin (body part twin, whole body twin, process twin and system twin) and end users (healthcare providers, pharmaceutical companies, medical device manufacturers, patients and others).

Chapter 5 features an analysis, highlighting the contemporary market trends through five different schematic representations, including a stacked bar chart representation based on area of application and status of development, a heat map representation based on type of technology used and type of digital twin, a grid representation based on type of end user and type of digital twin, a bar chart representation based on area(s) of application and location of headquarters, a hybrid chart representation comparing the players engaged in digital twins in healthcare domain, based on company size and location of headquarters.

Chapter 6 presents an insightful competitiveness analysis of players involved in the production / development of digital twins in the healthcare domain, based on several relevant parameters, such as years of experience, portfolio strength (in terms of number of products, status of development, area(s) of application, technology used, end user(s) and type of twin(s)), partnerships strength (in terms of number of partnerships, year of partnerships, and type of partnership) and funding strength (in terms of number of funding instances, amount of funding, year of funding and type of funding).

Chapter 7 features elaborate profiles of various prominent players that are currently engaged in the digital twins domain. Each company profile features a brief overview of the company (including information on its year of establishment, number of employees, location of headquarters and key members of the executive team), details related to its recent developments and an informed future outlook.

Chapter 8 presents information about partnerships undertaken by players engaged in digital twins domain. This chapter includes analysis of the partnerships that have been inked between various stakeholders, during the period 2018-2022, covering acquisitions, mergers, development agreement, technology integration agreement and technology utilization agreement.

Chapter 9 presents information about funding and investments received by players engaged in digital twins domain. This chapter includes analysis of the financial aid received during the period 2018-2022, including venture series, initial public offering, and private equity.

Chapter 10 includes a proprietary analysis to evaluate start-ups engaged in this market space, by assigning monetary values to various competition differentiators possessed by a player, based on Berkus start-up valuation parameters, including sound idea, prototype, management experience and strategic relationships undertaken by market players.

Chapter 11 features a detailed market forecast analysis, highlighting the likely growth of the digital twins market, for the period 2022-2035. Additionally, the report features the likely distribution of current and forecasted opportunity across various segments, such as therapeutic area (cardiovascular disorders, metabolic disorders, orthopedic disorders and other disorders), type of digital twins (process twins, system twins, whole body twins and body part twins), area(s) of application (asset / process management, personalized treatment, surgical planning, diagnosis and other applications), end users (pharmaceutical companies, medical device manufacturers, healthcare providers, patients and other end users) and key geographical regions (North America, Europe, Asia, Latin America, Middle East and North Africa and Rest of the World).

Chapter 12 summarizes the overall report, wherein all the key facts and figures have been mentioned. Further, the chapter also highlights important evolutionary trends that were identified during the course of the study and are expected to influence the future of the digital twins market.

Chapter 13 is a collection of interview transcripts of discussions held with various key stakeholders in this market. The chapter provides a brief overview of the companies and details of interviews held with several stakeholders.

Chapter 14 is an appendix, which provides tabulated data and numbers for all the figures provided in the report.

Chapter 15 is an appendix, which contains the list of companies and organizations mentioned in the report.

Product Code: RA100397

1. PREFACE

1.1. Scope of the Report
1.2. Market Segmentation
1.3. Research Methodology
1.4. Key Questions Answered
1.5. Chapter Outlines

2. EXECUTIVE SUMMARY

3. INTRODUCTION

3.1 Chapter Overview
3.2. Overview of Digital Twins in Healthcare
- 3.3.1. Types of Digital Twins Used in Healthcare
- 3.3.1. Process Twin
- 3.3.2. System Twin
- 3.3.3. Human Body Twin
3.4. Primary Applications of Digital Twins in the Healthcare Domain
- 3.4.1. Asset / Process Management
- 3.4.2. Evaluation of Clinical Trials
- 3.4.3. Personalized Treatment
- 3.4.4. Surgical Planning
3.5. Concluding Remarks

4. MARKET LANDSCAPE

4.1. Chapter Overview
4.2. Digital Twins in Healthcare: Overall Market Landscape
- 4.2.1. Analysis by Status of Development
- 4.2.2. Analysis by Therapeutic Area
- 4.2.3. Analysis by Area(s) of Application
- 4.2.4. Analysis by Type of Technology Used
- 4.2.5. Analysis by End User
- 4.2.6. Analysis by Type of Digital Twin
4.3. Digital Twins in Healthcare: Developers Landscape
- 4.3.1. Analysis by Year of Establishment
- 4.3.2. Analysis by Company Size
- 4.3.3. Analysis by Location of Headquarters

5. KEY INSIGHTS

5.1. Chapter Overview
5.2. Analysis by Area of Application and Status of Development (Stacked Bar Chart)
5.3. Analysis by Type of Technology Used and Type of Digital Twin (Heat Map

Representation)

5.4. Analysis by Type of End User and Type of Digital Twin (Grid Representation)
5.5. Analysis by Area of Application and Location of Headquarters (Bar Chart)
5.6. Analysis by Company Size and Location of Headquarters (Hybrid Chart)

6. COMPANY COMPETITIVENESS ANALYSIS

6.1. Chapter Overview
6.2. Assumptions and Key Parameters
6.3. Methodology
6.4. Digital Twins in Healthcare: Company Competitiveness Analysis
- 6.4.1. Company Competitiveness Analysis: Benchmarking of Portfolio Strength
- 6.4.2. Company Competitiveness Analysis: Benchmarking of Partnership Activity
- 6.4.3. Company Competitiveness Analysis: Benchmarking of Funding Activity
- 6.4.4. Company Competitiveness Analysis: Very Small Companies
- 6.4.5. Company Competitiveness Analysis: Small Companies
- 6.4.6. Company Competitiveness Analysis: Mid-sized Companies
- 6.4.7. Company Competitiveness Analysis: Large Companies
- 6.4.8. Company Competitiveness Analysis: Very Large Companies

7. COMPANY PROFILES

7.1. Chapter Overview
7.2. Babylon
- 7.2.1. Company Overview
- 7.2.2. Recent Developments and Future Outlook
7.3. ExactCure
- 7.3.1. Company Overview
- 7.3.2. Recent Developments and Future Outlook
7.4. ImmersiveTouch
- 7.4.1. Company Overview
- 7.4.2. Recent Developments and Future Outlook
7.5. Navv Systems
- 7.5.1. Company Overview
- 7.5.2. Recent Developments and Future Outlook
7.6. ThoughtWire
- 7.6.1. Company Overview
- 7.6.2. Recent Developments and Future Outlook
7.7. Unlearn.AI
- 7.7.1. Company Overview
- 7.7.2. Recent Developments and Future Outlook

8. PARTNERSHIPS AND COLLABORATIONS

8.1. Chapter Overview
8.2. Digital Twins in Healthcare: Partnerships and Collaborations
- 8.2.1. Partnership Models
- 8.2.2. List of Partnerships and Collaborations
- 8.2.3. Analysis by Number of Partnership Instances
- 8.2.4. Analysis by Type of Partnership
- 8.2.5. Analysis by Year and Type of Partnership
- 8.2.6. Analysis by Type of Partnership and Company Size
- 8.2.7. Most Active Players: Analysis by Number of Partnerships
- 8.3.8. Analysis by Region
- 8.3.9. Intercontinental and Intracontinental Agreements

9. FUNDING AND INVESTMENTS ANALYSIS

9.1. Chapter Overview
9.2. Types of Funding
9.3. Digital Twins in Healthcare: List of Funding and Investments
- 9.3.1. Analysis by Number of Funding Instances
- 9.3.2. Analysis by Amount Invested
- 9.3.3. Analysis by Type of Funding
- 9.3.4. Analysis by Geography
- 9.3.5. Most Active Players: Analysis by Number of Funding Instances
- 9.3.6. Most Active Players: Analysis by Amount of Funding
- 9.3.7. Most Active Investors: Analysis by Number of Funding Instances
9.4. Concluding Remarks

10. BERKUS START-UP VALUATION ANALYSIS

10.1. Chapter Overview
10.2. Key Assumptions and Methodology
10.3. Berkus Start-Up Valuation: Total Valuation of Players
10.4. Digital Twins in Healthcare: Benchmarking of Berkus Start-Up Valuation Parameters
- 10.4.1. AnatoScope: Benchmarking of Berkus Start-Up Valuation Parameters
- 10.4.2. ExactCure: Benchmarking of Berkus Start-Up Valuation Parameters
- 10.4.3. Klinik Sankt Moritz: Benchmarking of Berkus Start-Up Valuation

Parameters

10.4.4. KYDEA: Benchmarking of Berkus Start-Up Valuation Parameters
10.4.5. TwInsight: Benchmarking of Berkus Start-Up Valuation Parameters
10.4.6. Yokogawa Insilico Biotechnology: Benchmarking of Berkus Start-Up Valuation Parameters

10.5. Digital Twins in Healthcare: Benchmarking of Players
- 10.5.1. Sound Idea: Benchmarking of Players
- 10.5.2. Prototype: Benchmarking of Players
- 10.5.3. Management Experience: Benchmarking of Players
- 10.5.4. Strategic Relationships: Benchmarking of Players
- 10.5.5. Total Valuation: Benchmarking of Players

11. MARKET FORECAST

11.1. Chapter Overview
11.2. Key Assumptions and Methodology
11.3. Global Digital Twins Market, 2022-2035
- 11.3.1. Global Digital Twins Market: Analysis by Therapeutic Area
  - 11.3.1.1. Global Digital Twins Market for Cardiovascular Disorders, 2022-2035
  - 11.3.1.2. Global Digital Twins Market for Metabolic Disorders, 2022-2035
  - 11.3.1.3. Global Digital Twins Market for Orthopedic Disorders, 2022-2035
  - 11.3.1.4. Global Digital Twins Market for Other Disorders, 2022-2035
- 11.3.2. Global Digital Twins Market: Analysis by Type of Digital Twins
  - 11.3.2.1. Global Process Twins Market, 2022-2035
  - 11.3.2.2. Global System Twins Market, 2022-2035
  - 11.3.2.3. Global Whole Body Twins Market, 2022-2035
  - 11.3.2.4. Global Body Part Twins Market, 2022-2035
- 11.3.3. Global Digital Twins Market: Analysis by Area of Application
  - 11.3.3.1. Global Digital Twins Market for Asset / Process Management, 2022-2035
  - 11.3.3.2. Global Digital Twins Market for Personalized Treatment, 2022-2035
  - 11.3.3.3. Global Digital Twins Market for Surgical Planning, 2022-2035
  - 11.3.3.4. Global Digital Twins Market for Diagnosis, 2022-2035
  - 11.3.3.5. Global Digital Twins Market for Other Applications, 2022-2035
- 11.3.4. Global Digital Twins Market: Analysis by End Users
  - 11.3.4.1. Global Digital Twins Market for Pharmaceutical Companies, 2022-2035
  - 11.3.4.2. Global Digital Twins Market for Medical Device Manufacturers, 2022-2035
  - 11.3.4.3. Global Digital Twins Market for Healthcare Providers, 2022-2035
  - 11.3.4.4. Global Digital Twins Market for Patients, 2022-2035
  - 11.3.4.5. Global Digital Twins Market for Other End Users, 2022-2035
- 11.3.5. Global Digital Twins Market: Analysis by Geography
  - 11.3.5.1. Digital Twins Market in North America, 2022-2035
  - 11.3.5.2. Digital Twins Market in Europe, 2022-2035
  - 11.3.5.3. Digital Twins Market in Asia, 2022-2035
  - 11.3.5.4. Digital Twins Market in Latin America, 2022-2035
  - 11.3.5.5. Digital Twins Market in Middle East and North Africa, 2022-2035
  - 11.3.5.6. Digital Twins Market in Rest of the World, 2022-2035

12. CONCLUSION

13. EXECUTIVE INSIGHTS

13.1. Chapter Overview
13.2. Dassault Systemes
- 13.2.1. Company Snapshot
- 13.2.2. Interview Transcript: Barbara Holtz, Business Consultant
13.3. TwInsight
- 13.3.1. Company Snapshot
- 13.3.2. Interview Transcript: Marek Bucki, Co-Founder and Chief Scientific Officer
13.4. Unlearn.AI
- 13.4.1. Company Snapshot
- 13.4.2. Interview Transcript: Andrew Stelzer, Business Development Executive
13.5. Yokogawa Insilico Biotechnology
- 13.5.1. Company Snapshot
- 13.5.2. Interview Transcript: Klaus Mauch, Managing Director and Chief Executive Officer

14. APPENDIX I: TABULATED DATA

15. APPENDIX II: LIST OF COMPANIES AND ORGANIZATIONS