Dublin, Aug. 26, 2025 (GLOBE NEWSWIRE) -- The "Digital Twins in Healthcare Market Industry Trends and Global Forecasts to 2035: Distribution by Therapeutic Area, Type of Digital Twin, Areas of Application, End Users and Key Geographical Regions" report has been added to ResearchAndMarkets.com's offering.
The global digital twins in healthcare market is estimated to grow from USD 1.9 billion in the current year to USD 33.4 billion by 2035, at a CAGR of 30% during the forecast period to 2035.
In recent years, there have been significant advancements related to technologies, such as artificial intelligence, deep learning and machine learning and big data. These programs have now garnered significant interest of players engaged in the healthcare domain. Consequently, the industry stakeholders are undertaking efforts to drive innovation and improve the performance of the existing processes, using the aforementioned technologies.
Amidst these technologies, digital twins have emerged as a promising technique for use in the healthcare sector. In this context, it is worth mentioning that a digital twin, in its essence, is a virtual model that employs real-world data to create simulations, which are capable of predicting the performance of a system or process. Specifically, in the healthcare domain, digital twins can be applied for risk prediction, lowering labor costs, providing improved patient care and automated decision-making process.
Furthermore, players engaged in the healthcare domain may increasingly adopt the digital twin concept to cut down their research and development costs. Driven by the growing demand for personalized medicine, virtual simulation and automated technologies, the digital twin in healthcare is poised to witness substantial growth.
Digital Twins in Healthcare Market: Key Insights
The report delves into the current state of the digital twins in healthcare market and identifies potential growth opportunities within the industry. Some key findings from the report include:
- Currently, over 90 digital twins are either commercially available in the market or are under development for various healthcare related applications including diagnosis, health monitoring and surgical planning.
- Over 42% of the digital twins offered by industry players are process twins; majority of the twins are primarily intended for asset / process management, personalized treatment and surgical planning.
- The partnership activity in this industry has grown at a rate of over 20% in the past three years; it is worth noting that over 45% of the deals have been signed in the last two years.
- To support the ongoing innovations, several private and public investors have made substantial capital investments; notably, most of the funding rounds took place in the past few years.
- Start-ups in the digital twin market are gradually adopting advanced and innovative technologies, such as artificial intelligence and blockchain, in order to differentiate themselves from their competitors.
- Owing to the growing interest towards remote patient monitoring, predictive analytics, personalized treatment, and IoT integration, the market for digital twins in healthcare will increase steadily in the foreseeable future.
- Driven by increasing adoption of digital twin technologies in healthcare and pharmaceutical industries, it is anticipated that the global digital twins market in healthcare domain is likely to grow at an annualized rate of 30% to 2035.
Digital Twins in Healthcare Market: Research Coverage
- Market Sizing and Opportunity Analysis: The report features an in-depth analysis of the digital twins in healthcare market, focusing on key market segments, including therapeutic area, type of digital twin, area of application, end users and key geographical regions.
- Market Landscape: A comprehensive evaluation of companies involved in the development of digital twins, considering various parameters, such as year of establishment, company size, location of headquarters, status of development, therapeutic area, areas of application, type of technology used, type of digital twin and end users.
- Key Insights: An in-depth digital twins in healthcare market analysis, highlighting the contemporary market trends, using five schematic representations, based on areas of application and status of development, type of technology used and type of digital twin, type of end user and type of digital twin, area of application and location of headquarters, and company size and location of headquarters.
- Company Competitiveness Analysis: A comprehensive competitive analysis of digital twins developers, examining factors, such as years of experience, portfolio strength, partnership strength and funding strength.
- Company Profiles: In-depth profiles of key industry players offering digital twins, focusing on company overviews, financial information, recent developments and an informed future outlook.
- Partnerships and Collaborations: An analysis of partnerships established in this sector, since 2018, covering acquisitions, mergers, commercialization agreements, licensing agreements, product development agreements, research agreements, service agreements, service alliances, technology development agreements, technology integration agreements, technology utilization agreements and others.
- Funding and Investment Analysis: A detailed evaluation of the investments made in the digital twins market, encompassing grants, seed funding, venture capital investments, initial public offering, secondary offerings, private placements, debt financing and other equity.
- Berkus Start-Up Valuation Analysis: A proprietary analysis designed to assess start-ups in this market, by assigning monetary values to various competition differentiators possessed by a player. This evaluation is based on the Berkus start-up valuation criteria, which include factors such as sound idea, prototype, management experience and strategic relationships undertaken by market players.
- Market Impact Analysis: The report analyzes various factors such as drivers, restraints, opportunities, and challenges affecting the market growth.
Key Players in the Digital Twins in Healthcare Market, Profiled in the Report Include:
- ai
- Certara
- Dassault Systemes
- DEO
- Mesh Bio
- NavvTrack
- OnScale
- Phesi
- PrediSurge
- SingHealth
- Twin Health
- Unlearn
- Verto
- VictoryXR
- Virtonomy
Key Questions Answered in this Report
- How many companies are currently engaged in this market?
- Which are the leading companies in this market?
- What factors are likely to influence the evolution of this market?
- What is the current and future market size?
- What is the CAGR of this market?
- How is the current and future market opportunity likely to be distributed across key market segments?
Reasons to Buy this Report
- The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
- Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
- The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.
Additional Benefits
- Complimentary PPT Insights Packs
- Complimentary Excel Data Packs for all Analytical Modules in the Report
- 10% Free Content Customization
- Detailed Report Walkthrough Session with Research Team
Key Topics Covered:
1. PREFACE
2. RESEARCH METHODOLOGY
3. ECONOMIC AND OTHER PROJECT SPECIFIC CONSIDERATIONS
4. EXECUTIVE SUMMARY
5. INTRODUCTION
5.1. Chapter Overview
5.2. Overview of Digital Twins in Healthcare
5.3. Types of Digital Twins Used in Healthcare
5.4. Applications of Digital Twins in the Healthcare Domain
5.5. Challenges Associated with the Adoption of Digital Twins
5.6. Concluding Remarks
6. MARKET LANDSCAPE
6.1. Chapter Overview
6.2. Digital Twins in Healthcare: Overall Market Landscape
6.3. Digital Twins in Healthcare: Developer Landscape
7. KEY INSIGHTS
7.1. Chapter Overview
7.2. Analysis by Area of Application and Development Status
7.3. Analysis by Type of Technology Used and Type of Digital Twin
7.4. Analysis by Type of End User and Type of Digital Twin
7.5. Analysis by Location of Headquarters and Area of Application
7.6. Analysis by Company Size and Location of Headquarters
8. COMPANY COMPETITIVENESS ANALYSIS
8.1. Chapter Overview
8.2. Assumptions and Key Parameters
8.3. Methodology
8.4. Digital Twins in Healthcare: Company Competitiveness Analysis
9. DETAILED COMPANY PROFILES
9.1. Chapter Overview
9.2. BigBear.ai
9.3. Certara
9.4. Dassault Systemes
9.5. NavvTrack
9.6. Unlearn.ai
10. TABULATED COMPANY PROFILES
10.1. Chapter Overview
10.2. Players Based in North America
10.2.1. OnScale
10.2.2. Phesi
10.2.3. Twin Health
10.2.4. Verto
10.2.5. VictoryXR
10.3. Players Based in Europe
10.3.1. DEO
10.3.2. PrediSurge
10.3.3. Virtonomy
10.4. Players Based in Asia
10.4.1. Mesh Bio
10.4.2. SingHealth
11. PARTNERSHIPS AND COLLABORATIONS
11.1. Chapter Overview
11.2. Digital Twins in Healthcare: Partnerships and Collaborations
12. FUNDING AND INVESTMENTS ANALYSIS
12.1. Chapter Overview
12.2. Types of Funding
12.3. Digital Twins in Healthcare: List of Funding and Investments
12.4. Concluding Remarks
13. BERKUS START-UP VALUATION ANALYSIS
13.1. Chapter Overview
13.2. Key Assumptions and Methodology
13.3. Berkus Start-Up Valuation: Total Valuation of Players
13.4. Digital Twins in Healthcare: Benchmarking of Berkus Start-Up Valuation Parameters
13.4.1. AI Body
13.4.2. AnatoScope
13.4.3. Antleron
13.4.4. EmbodyBio
13.4.5. Klinik Sankt Moritz
13.4.6. KYDEA
13.4.7. MAI
13.4.8. Mindback AI
13.4.9. Neo PLM
13.4.10. Twinsight
13.4.11. Yokogawa Insilico Biotechnology
13.5. Digital Twins in Healthcare: Benchmarking of Players
14. MARKET IMPACT ANALYSIS: DRIVERS, RESTRAINTS, OPPORTUNITIES AND CHALLENGES
15. GLOBAL DIGITAL TWIN IN HEALTHCARE MARKET
15.1. Chapter Overview
15.2. Assumptions and Methodology
15.3. Global Digital Twin in Healthcare Market, Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
16. DIGITAL TWIN IN HEALTHCARE MARKET, BY THERAPEUTIC AREA
16.1. Chapter Overview
16.2. Key Assumptions and Methodology
16.3. Cardiovascular Disorders: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
16.4. Metabolic Disorders: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
16.5. Orthopedic Disorders: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
16.6. Other Disorders: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
17. DIGITAL TWIN IN HEALTHCARE MARKET, BY TYPE OF DIGITAL TWINS
17.1. Chapter Overview
17.2. Key Assumptions and Methodology
17.3. Process Twins: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
17.4. System Twins: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
17.5. Whole Body Twins: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
17.6. Body Part Twins: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
18. DIGITAL TWIN IN HEALTHCARE MARKET, BY AREA OF APPLICATION
18.1. Chapter Overview
18.2. Key Assumptions and Methodology
18.3. Asset / Process Management: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
18.4. Personalized Treatment: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
18.5. Surgical Planning: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
18.6. Diagnosis: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
18.7. Other Applications: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
19. DIGITAL TWIN IN HEALTHCARE MARKET, BY END USERS
19.1. Chapter Overview
19.2. Key Assumptions and Methodology
19.3. Pharmaceutical Companies: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
19.4. Medical Device Manufacturers: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
19.5. Healthcare Providers: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
19.6. Patients: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
19.7. Other End Users: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
20. DIGITAL TWIN IN HEALTHCARE MARKET, BY GEOGRAPHY
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