Digital Twins in Healthcare Market Size is valued at USD 1.64 Bn in 2023 and is predicted to reach USD 82.40 Billion by the year 2031 at a 63.65% CAGR during the forecast period for 2024-2031.
A "digital twin," or virtual depiction of a person's physical state, is used in medicine to predict how various treatments and interventions would affect a patient's condition. The medical digital twin concept is created by combining data from electronic health records, wearable technologies, imaging research, and other sources. Over the course of the forecast period, the worldwide market is likely to be driven by the expansion of the use of data analytics and machine learning, the increase of telemedicine and remote patient monitoring, and the enhancement of the efficacy of digital twin technology in the healthcare sector. In the near future, it is also expected that the need for digital twins in the healthcare industry will increase due to an increase in new product releases and an increase in company strategic alliances.
Additionally, the industry is expanding because of a greater emphasis on community health management and value-based treatment. Businesses in the industry are offering state-of-the-art software and solutions to increase their market share. Consequently, there are currently lucrative opportunities for digital twin businesses in the healthcare industry.
The digital twins in healthcare market is segmented according to component, application, and end user. Based on component, the market is categorized as Software and Services. The application segment includes Drug Discovery & Development, Surgical Planning and Medical Education, Personalized medicine, Medical Device Design and Testing, Healthcare Workflow Optimization & Asset Management, and Others. On the basis of end user, the market is segmented into Pharma & Bio-pharma companies, Research & Academia, Providers, Medical device Companies, and Others.
The personalized medicine category is expected to hold a major share in the global digital twins in healthcare market. The potential of customized medicine to increase patient outcomes, reduce side effects, and optimize treatment efficacy is what is propelling its expansion. The need for digital twin solutions in customized medicine has grown significantly as a result of developments in precision medicine, genomics, and molecular diagnostics.
The providers segment is expected to grow at a rapid rate in the global digital twins in healthcare market. The hospitals' improved diagnostic capabilities, which allow for more accurate disease diagnosis, better and timely medication administration, data-driven decision-making, and the growing use of telehealth and telemedicine in the healthcare industry, are all responsible for this segment's size.
The North America digital twins in healthcare market is expected to hold the highest market revenue share in the near future. Due to the rising use of digital twins in healthcare in the area, this region is expected to lead the sector during the projection period. The region's digital twin in healthcare business development is influenced by a number of factors, including the expansion of better healthcare facilities, particularly in hospitals and ambulatory surgery centers (ASC), the development of medical technologies, and the profitable presence of major players in the United States and Canada. In addition, Asia Pacific is estimated to show rapid growth rapidly in the global digital twins in healthcare market because digital twin software is being adopted at a rapid pace in the area. Many businesses in the Asia-Pacific region are working on developing and researching digital healthcare solutions. The digital twin in the region's healthcare market statistics is benefiting from this.
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Report Attribute |
Specifications |
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Market Size Value In 2023 |
USD 1.64 Bn |
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Revenue Forecast In 2031 |
USD 82.40 Bn |
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Growth Rate CAGR |
CAGR of 63.65 % from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Component, Application, End-User |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
IBM, Siemens Healthineers AG, Koninklijke Philips N.V, Faststream Technologies, Dassault Systèmes, Twin LTD, Microsoft, NVIDIA Corporation, GENUREA, ANSYS, Inc., AMAZON (AWS), Rescale, Inc., Predictiv, Verto Health, PrediSurge, Oracle, SAP, ATOS SE, Other Prominent Players |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Digital Twins in Healthcare Market Snapshot
Chapter 4. Global Digital Twins in Healthcare Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Component Estimates & Trend Analysis
5.1. by Component & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Component:
5.2.1. Software
5.2.2. Services
Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:
6.2.1. Drug Discovery & Development
6.2.2. Personalized medicine
6.2.3. Surgical Planning and Medical Education
6.2.4. Medical Device Design and Testing
6.2.5. Healthcare Workflow Optimization & Asset Management
6.2.6. Others
Chapter 7. Market Segmentation 3: by End-User Estimates & Trend Analysis
7.1. by End-User & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End-User:
7.2.1. Pharma & Bio-pharma companies
7.2.2. Research & Academia
7.2.3. Providers
7.2.4. Medical device Companies
7.2.5. Others
Chapter 8. Digital Twins in Healthcare Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Component, 2019-2031
8.1.2. North America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.1.3. North America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.1.4. North America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.2. Europe
8.2.1. Europe Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Component, 2019-2031
8.2.2. Europe Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.2.3. Europe Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.2.4. Europe Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.3. Asia Pacific
8.3.1. Asia Pacific Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Component, 2019-2031
8.3.2. Asia-Pacific Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.3.3. Asia Pacific Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.3.4. Asia Pacific Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.4. Latin America
8.4.1. Latin America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Component, 2019-2031
8.4.2. Latin America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.4.3. Latin America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.4.4. Latin America Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
8.5. Middle East & Africa
8.5.1. Middle East & Africa Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Component, 2019-2031
8.5.2. Middle East & Africa Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031
8.5.3. Middle East & Africa Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2019-2031
8.5.4. Middle East & Africa Digital Twins in Healthcare Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. Siemens Healthineers AG (Germany)
9.2.2. Dassault Systèmes (France)
9.2.3. Microsoft (US)
9.2.4. Koninklijke Philips N.V. (Netherlands)
9.2.5. Faststream Technologies (US)
9.2.6. Twin LTD (US)
9.2.7. IBM (US)
9.2.8. NVIDIA Corporation (US)
9.2.9. GE Healthcare (US)
9.2.10. NUREA (France)
9.2.11. ANSYS, Inc. (US)
9.2.12. Rescale, Inc. (US)
9.2.13. Predictiv (US)
9.2.14. Verto Health (Canada)
9.2.15. PrediSurge (France)
9.2.16. Qbio (US)
9.2.17. Virtonomy GmbH (Germany)
9.2.18. Unlearn AI (US)
9.2.19. Atos SE (France)
9.2.20. ThoughtWire (Canada)
9.2.21. Amazon Web Services Inc (US)
9.2.22. Oracle (US)
9.2.23. PTC (US)
9.2.24. SAP (Germany)
9.2.25. Sim and Cure (France).
9.2.26. Other Prominent Players
Digital Twins In Healthcare Market By Component-
Digital Twins In Healthcare Market By Application-
Digital Twins In Healthcare Market By End User-
Digital Twins In Healthcare Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
