Digital Twin Market, Distribution by Therapeutic Area (Cardiovascular Disorders, Metabolic Disorders, Orthopedic Disorders, and Other Disorders), Type of Digital Twin (Process Digital Twin, System Digital Twin, Whole Body Digital Twin and Body Part Digital Twin), 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
The digital twin market in healthcare and pharmaceutical industry is expected to reach USD 1 billion in 2022 and anticipated to grow at a CAGR of 30% during the forecast period 2023-2035.
The creation of a new pharmaceutical product necessitates an average investment nearing USD 1 billion. Presently, over 90% of potential medications encounter failure at various stages of clinical trials, leading to significant financial setbacks for pharmaceutical developers. With the emergence of Industry 4.0 technologies—like augmented reality, big data, the Internet of Things (IoT), and virtual reality—digital twin technology has arisen as a promising solution to tackle numerous challenges in the healthcare sector. Digital twins are virtual replicas of physical entities, processes, or services that can mimic real-world operations to collect real-time data and forecast performance. They have showcased the capability to expedite clinical trials and replicate studies involving larger populations within shorter durations. Researchers working on categorizing drug risks through digital twin models suggest that a further development of this approach could potentially save up to USD 2.5 billion typically spent on the design and testing of new drugs. Various digital twin models have proven reliable in diagnosing and treating various diseases, potentially reducing excessive costs attributed to inaccurate medical diagnoses. On an annual basis, medical errors are projected to cause a loss of nearly USD 20 billion in the United States.
Consequently, digital twins are expected to yield significant cost reductions. Approximately 15% of organizations implementing IoT projects have already integrated digital twin platforms, while over 60% of firms are either considering or in the process of incorporating this technology into their operations in the foreseeable future.
Report Coverage
The creation of a new pharmaceutical product necessitates an average investment nearing USD 1 billion. Presently, over 90% of potential medications encounter failure at various stages of clinical trials, leading to significant financial setbacks for pharmaceutical developers. With the emergence of Industry 4.0 technologies—like augmented reality, big data, the Internet of Things (IoT), and virtual reality—digital twin technology has arisen as a promising solution to tackle numerous challenges in the healthcare sector. Digital twins are virtual replicas of physical entities, processes, or services that can mimic real-world operations to collect real-time data and forecast performance. They have showcased the capability to expedite clinical trials and replicate studies involving larger populations within shorter durations. Researchers working on categorizing drug risks through digital twin models suggest that a further development of this approach could potentially save up to USD 2.5 billion typically spent on the design and testing of new drugs. Various digital twin models have proven reliable in diagnosing and treating various diseases, potentially reducing excessive costs attributed to inaccurate medical diagnoses. On an annual basis, medical errors are projected to cause a loss of nearly USD 20 billion in the United States.
Consequently, digital twins are expected to yield significant cost reductions. Approximately 15% of organizations implementing IoT projects have already integrated digital twin platforms, while over 60% of firms are either considering or in the process of incorporating this technology into their operations in the foreseeable future.
Report Coverage
- The report examines the digital twin market concerning therapeutic areas, digital twin types, application areas, end users, and key geographical regions.
- It analyzes the market growth factors, including drivers, restraints, opportunities, and challenges.
- It evaluates potential advantages and obstacles for stakeholders and provides insights into the competitive landscape for leading market players.
- The report forecasts segment-wise market revenue across six major regions.
- It offers a concise summary of crucial findings from research, presenting an overview of the current state and anticipated evolution of the digital twin market in the short, mid, and long terms.
- It includes a succinct introduction explaining essential concepts related to digital twins, exploring various types and their primary applications in the healthcare sector, along with recent advancements.
- It provides a comprehensive overview of digital twin enterprises, encompassing details such as establishment year, company size, headquarters location, market status (marketed and in progress), therapeutic focuses, applications, employed technologies (AI, VR, AR, blockchain), types, and end-user categorization.
- The report highlights contemporary trends in the digital twin market through visual representations, including stacked bar charts, heat maps, grid representations, bar charts, and hybrid charts comparing players based on company size and headquarters location.
- It conducts a competitive analysis of entities involved in healthcare digital twin development, evaluating factors like experience, portfolio strength, partnership depth, and funding intensity.
- It presents detailed profiles of prominent companies in the healthcare digital twin market, covering company overview, recent developments, and future prospects.
- An in-depth examination of partnerships forged among stakeholders between 2018 and 2022, including acquisitions, mergers, agreements, and technology integration.
- Analysis of funding and investments received by players between 2018 and 2022, encompassing various types of funding.
- Proprietary evaluation of digital twin startups, using Berkus startup valuation parameters to assign values to competitive differentiators such as idea strength, prototypes, management expertise, and strategic relationships.
- Babylon
- ExactCure
- ImmersiveTouch
- Navv Systems
- ThoughtWire
- Unlearn.AI
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 Syst?mes
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
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 Syst?mes
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
