A digital twin is a virtual replica to reflect a physical object precisely. The object under observation is equipped with various sensors at vital areas of functionality to provide data about its performance such as energy output, temperature, weather conditions and more. This data is then transmitted to a processing system and applied to the digital copy. Then this virtual model is used to run simulations, study performance issues and generate possible improvements with an aim to generate valuable insights, which can then be applied back to the original physical object. This process provides benefits such as better research and development, greater efficiency, and product end-of-life.

In healthcare, a digital twin is a computer-generated image of a patient, healthcare facility or a healthcare lab. The benefits of designing a digital twin in healthcare include the ability to improve patient care and research, hospitals can save money on personnel costs and on research projects.

The use of digital twin in healthcare is not new and scientists have been using it for more than a decade to study chronic conditions such as cancer. However, the use of digital twin in healthcare has evolved recently and scientists have started using them as replacements for patients in real life. During clinical trials, by using virtual patients instead of real ones, doctors can study how a particular treatment or drug will react to a particular patient, thus savings money on personnel costs and on research projects.

Digital twin has also found their application in hospitals, where they can be used as replacements for patients before an operation for planning a surgery to study how to carry out surgery and how it will impact a patient’s body. As a result, hospitals don’t need to invest in new equipment or staff members until they know whether or not it works well enough for use in real life.

Some of the benefits of designing a digital twin in healthcare include:

• Increased Accuracy – Rather than just relying on physical specimens, digital twin by creating a digital replica of a patient’s brain, allows scientists to study diseases more accurately.
• Reduced Labour Costs – Hospitals can save money on personnel costs and research projects by using digital twins as patient replacements.
• Improved Communication – By using digital twins, medical staff can connect with each other more effectively and efficiently as if they were using human counterparts.

Global Digital Twin in Healthcare Market was valued at US $584.65MM in 2022 and is expected to reach US $3,801.23MM by 2030 growing at a CAGR of 26.37% during the forecast period 2023 – 2030.

COVID -19 Impact on Digital Twin in Healthcare Market  

The pandemic presented numerous challenges to the healthcare industry, and digital twins emerged as a valuable tool to address some of these challenges. Though there are not much evidences to show that it was used widely, however few organizations in healthcare did try leveraging the potential of digital twin for improved healthcare outcomes.  For instance, during COVID-19, the NHS COVID-19 app was a contact tracing app developed for monitoring the spread of the COVID-19 pandemic in England and Wales.

Digital twin technology within the NHS COVID-19 app was used to create a behavioral feedback loop. This formed the basis for data science modelling and ongoing analysis to inform decision-makers about the spread of the virus. The digital twin gathered critical real-time data while ensuring anonymity and user privacy. The data science and modelling allowed to perform data science and analysis to build models and experiment with different scenarios. Digital twin also allowed for scenario testing to understand the implications of changing lockdown measures – for example, the impact of changing a specific location’s measures from level one to level two. last but not the least was actionable recommendations. Epidemiological data was accessible to senior decision-makers in the U.K. via a dedicated channel, with data-backed recommendations on how to minimize COVID-19 outbreaks at a local and national level.  

In this way, the digital twin was of great contribution to senior decision-makers as it helped them in anticipating and monitoring their decisions' impact, with the agility to adapt measures in line with rapidly changing virus patterns. 

Factors Driving the Digital Twin in Healthcare Market

Digital Twin in Healthcare Market Drivers

Surge in Adoption of Data Analytics and AI in Healthcare

Healthcare has been one of the fastest-growing economies in the recent years and in the light of growing threats of pandemics such as COVID-19 outbreak, the industry is ready to rise once again. To be able to provide advanced healthcare services and solutions to the population and to expand their reach, organizations worldwide are turning to unconventional techniques such as AI including ML and big data analytics for improved patient outcome, increased accuracy and cos-effectiveness.  
The potential applications of AI in preventative health care are increasing day by day. Apart from heart attacks, scientists are actively researching the application of AI to predict a wide range of other diseases and illnesses such as cancer and diabetes. For instance, AI has the potential to identify which people who are healthy currently are likely to develop breast cancer within five years, based on information hidden in mammograms, which is likely impossible by today’s clinicians to interpret.

Similarly, data analytics in healthcare helps in transforming health data into easily understood actionable insights. It combines historical and real-time data to predict trends, provide insights, drive long-term growth, and achieve medical advances. Digitizing medical records is one of the major benefits of data analytics in healthcare resulting in substantial savings. In particular, EHR comprising of administrative and diagnostic patient information provides information on procedures, demographics, length of stay, and fees, thus improving the quality of care since they can trigger warnings and reminders for diagnostics.

The surge in adoption of data analytics and AI in healthcare has significantly increased the need for digital twins in the industry. By utilizing data analytics and AI algorithms, healthcare professionals can leverage digital twins to optimize patient-specific treatments, personalize care, and predict outcomes. These digital replicas help in real-time monitoring, early detection of anomalies, and continuous improvement of medical processes, resulting in enhanced patient outcomes, reduced costs, and improved overall healthcare efficiency. As a result, with the increase in the adoption of data analytics and AI the potential for digital twin to grow is increasing at a tremendous rate, thus will benefit the global digital twin in healthcare market in coming years.

Digital Twin in Healthcare Market Challenges

Lack of Technical Expert

A digital twin is a cutting-edge technology, part of Industry 4.0 and therefore, the level and depth of of technical expertise required to create, implement and manage it is relatively high. Factors contributing to its complexity includes the need to constantly update and refine the entire system or process based on real-world data. Also, digital twin requires sophisticated modeling and simulation techniques to create it. It also requires advanced data analytics to analyze and interpret the huge amount of data it generates. Additionally, it must be capable of integrating with existing healthcare IT systems.

Since this entire process of developing and running digital twin is lengthy and complex, it requires a healthcare provider to be technically advanced to implement it. However, the healthcare professionals often have their hands full with patient care, leaving limited time and resources for extensive training in these technical areas.

As a consequence, healthcare organizations may struggle to find individuals with the necessary expertise to design, implement, and maintain digital twins effectively. Additionally, the shortage of technical talent can result in slower integration of digital twin technologies into the healthcare system or only larger hospitals or technologically advanced healthcare providers can install them, potentially delaying the realization of their full potential in improving patient outcomes and operational efficiency.

To address this issue, healthcare institutions should invest in targeted training programs to upskill existing staff in data analytics and AI technologies. Collaborations with technology experts and partnerships with educational institutions can also help bridge the skills gap. Furthermore, cloud-based platforms and user-friendly tools might be developed to simplify the implementation and management of digital twins, enabling a wider range of healthcare professionals to leverage this transformative technology. Until then, there will be a lack of availability of technical experts to run and implement digital twin in healthcare, thus acting as a barrier to the overall market growth.  

Digital Twin in Healthcare Market Trends

Rise in Software-as-a-Medical Device

According to International Medical Device Regulators Forum (IMDRF), the term software-as-a-medical device is defined as the software intended to be used for one or more medical purposes that perform these purposes without being part of a hardware medical device. The adoption of software-as-a-medical device is steadily growing due to its versatility across various technology platforms including medical device platforms, commercial "off-the-shelf" platforms, and virtual networks etc. This type of softwares were formerly known by names such as "medical device software," "standalone software," and/or "health software," by international regulators, industry, and health care providers, which occasionally led to confusion with other types of software.

As a response to this, the FDA is developing a regulatory framework that enables companies to obtain certification and market and sell software-as-a-medical device. The core idea revolves around the creation of  a patient-specific digital twin from different data sources, including lab tests, ultrasound, imaging devices, and genetic tests. For instance, a digital twin of a patient could be used to continuously monitor and collect real-time health data, which is then analyzed by software-as-a-medical device algorithms to provide personalized treatment recommendations. In addition, digital twins can also help optimize the software in medical devices such as automated insulin pumps, novel brain treatments, and pacemakers. Medical devices equipped with digital twin capabilities can simulate the performance of a medical device and predict its potential malfunctions and areas of improvement thus, allowing for proactive improvements and maintenance. The software-as-a-medical device can then analyze the data generated by the digital twin of the medical device to optimize its functionality further and enhance patient safety.

Overall, the combination of digital twin technologies and software-as-a-medical device has the potential to revolutionize healthcare by enabling more personalized, precise, and data-driven medical interventions, leading to improved patient outcomes and operational efficiency. 

Digital Twin in Healthcare Market by Market Segmentation

Digital Twin in Healthcare Market By End-users

• The healthcare provider segment dominated the digital twin in healthcare market in 2022.
• The research organizations and academic institutions is the fastest growing segment, growing at a CAGR of 27.48% during the forecast period.

By end-users, the global digital twin in healthcare market is divided into healthcare providers, medical device companies, pharmaceutical companies, research organizations and academic institutions. Healthcare providers are further divided into hospitals, diagnostics centers, ambulatory centers, and clinics.
The healthcare provider segment dominated the digital twin in healthcare market in 2022 with the market share of 33.33%. The large share of this segment can be attributed to use and potential of digital twin in both patient and process to enhance the overall healthcare industry. In the case of patients, digital twins allow healthcare providers to create virtual representations of individual patients, considering their unique physiology, genetics, and medical history. This enables more personalized treatment plans and interventions, leading to better patient outcomes. In the case of process, hospitals and other healthcare providers can use digital twins to optimize resource allocation, such as staff scheduling, equipment utilization, and patient flow. This improves efficiency and helps manage patient loads effectively, especially during peak times or emergencies.

The research organizations and academic institutions is the fastest growing segment, growing at a CAGR of 27.48% during the forecast period. The increasing demand for digital twins in research and academic settings is driven by the desire for advanced tools and technologies that facilitate more efficient and data-driven investigations, leading to groundbreaking discoveries and solutions to complex problems.

Digital Twin in Healthcare Market by Application

• The healthcare facility construction and management segment dominated the digital twin in healthcare market in 2022.
• The personalized diagnosis and treatment planning is the fastest growing segment, growing at a CAGR of 27.68% during the forecast period.

By application the digital twin in healthcare market is divided by healthcare facility construction and management, medical device design and development, personalized diagnosis and treatment planning, drug discovery and development, and others. Others is further divided into medical imaging and medical education.   

The healthcare facility construction and management segment dominated the digital twin in healthcare market in 2022 with the market share of 32.56%. This can be attributed to increasing adoption of technologies such as digital twin by the hospitals and healthcare facilities to make informed decisions about the layout of the hospital, asset and process management. For instance, digital twin enables precise 3D modeling of hospital structures, facilitating accurate planning and design, reducing errors, and ensuring optimal space utilization. Additionally, once the hospital is operational, digital twins continue to benefit by providing an interactive platform for facility management, aiding in maintenance and decision-making for ongoing operations.

The personalized diagnosis and treatment planning is the fastest growing segment, growing with the CAGR of 27.68% during the forecast period. There has been an increased focus on personalized diagnosis in recent years due to the benefits it provides such as targeted treatment to increase effectiveness, reduced side-effects etc.  Further, optimal treatment selection ensures that the most appropriate treatment options are chosen based on evidence-based guidelines and the patient's response to previous therapies. Thus, the digital twins have emerged as a powerful tool in personalized diagnosis and treatment planning, offering several advantages for healthcare professionals and patients by providing personalized patient models, disease progression simulation or how the patient will react to particular treatment or surgery. As a result, the digital twin will find its major application in personalized diagnosis and treatment planning in coming years as it helps in treatment optimization, informed decision making, and long-term health management.

Digital Twin in Healthcare Market by Region

• The North America region dominated the digital twin in healthcare market in 2022.
• The APAC region is the fastest growing segment, growing at a CAGR of 28.53% during the forecast period.

By region, the global digital twin in healthcare market is divided into North America, Europe, APAC and Others. Others is further divided into Middle East, Africa and South America.

The North America region dominated the digital twin in healthcare market in 2022 with the market share of 36.52%. The presence of digitally advanced infrastructure supported by government funding is one of the major factors for the high market share. The presence of the key players such as Microsoft Corporation, NVIDIA Corporation, GE Healthcare, and ANSYS among others is another factor for the high rate of adoption of advanced technologies such as digital twin in the countries such as US and Canada.

However, APAC is the fastest growing region, growing at a CAGR of 28.53% during the forecast period owing to factors such as rapid economic growth, leading to increased healthcare spending. As disposable incomes rise, there is a greater demand for improved healthcare services and facilities. Further, several APAC governments have implemented healthcare reforms and initiatives to improve healthcare accessibility and quality. These policies encourage private sector participation and foster innovation in the healthcare industry.

Digital Twin in Healthcare Market Competitive Landscape

The global digital twin in healthcare market is consolidated with the presence of few major players contributing to the market revenue. This dominance of these major players is driven by their technological expertise, extensive resources, and established brand recognition. These companies typically offered comprehensive and diversified digital twin solutions, dealing with various aspects of healthcare, such as patient-specific modeling, predictive analytics, and operational optimization.

However, the attractiveness of the market has resulted into many new start-ups entering the market with specific solutions and thereby attracting the healthcare providers.

Major Players

• Siemens Healthineers AG (Germany)
• Dassault Systems (France)
• Microsoft Corporation, (U.S.)
• Koninklijke Philips N.V. (The Netherlands)
• Faststream Technologies (U.S.)
• Twin Health LTD. (U.S.)
• Q Bio, Inc. (U.S.)
• IBM Corporation (U.S.)
• NVIDIA Corporation (U.S.)
• GE Healthcare (U.S.)
• NUREA (France)
• ANSYS, Inc. (U.S.)
• Rescale, Inc. (U.S.)
• Verto Health (Canada)
• Predictiv Care, Inc. (U.S.)
• Atos SE (France)
• QiO Technologies (U.K.)
• ThoughtWire (Canada)
• PrediSurge (France)
• Virtonomy GmbH (Germany)
• Unlearn AI (U.S.)

Recent Developments

• July 2023: SingHealth, Singapore’s healthcare institution is scaling digital twin project beyond disease outbreak monitoring. SingHealth's partnership with the National Supercomputing Centre Singapore and NVIDIA, which was signed last year, is also supporting its use of digital twin technology.
• February 2023: The National Institutes of Health (NIH) has awarded researchers from Cleveland Clinic and MetroHealth a US $3.14MM grant to use digital twins to better understand and address health disparities.

Digital Twin in Healthcare Market Scope

Table of Contents

1 INTRODUCTION OF GLOBAL DIGITAL TWIN IN HEALTHCARE MARKET

1.1 Overview of the Market

1.2 Scope of Report

1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY

3.1 Data Mining

3.2 Validation

3.3 Primary Interviews

3.4 List of Data Sources

4 GLOBAL DIGITAL TWIN IN HEALTHCARE MARKET OUTLOOK

4.1 Overview

4.2 Market Dynamics

4.2.1 Drivers

4.2.2 Restraints

4.2.3 Opportunities

4.3 Porters Five Force Model

4.3.1. Bargaining Power of Suppliers

4.3.2. Threat of New Entrants

4.3.3. Threat of Substitutes

4.3.4. Competitive Rivalry

4.3.5. Bargaining Power among Buyers

4.4 Value Chain Analysis

5 GLOBAL DIGITAL TWIN IN HEALTHCARE MARKET, BY END-USERS

5.1 Healthcare providers

5.2 Healthcare payers

5.3 Medical device companies

5.4 Pharmaceutical companies

5.5 Research organizations and academic institutions

6 GLOBAL DIGITAL TWIN IN HEALTHCARE MARKET, BY APPLICATIONS

6.1 Healthcare Facility Construction and Management

6.2 Medical Device Design and Development

6.3 Personalized Diagnosis and Treatment Planning

6.4 Drug Discovery and Development

6.5 Others

7 GLOBAL DIGITAL TWIN IN HEALTHCARE MARKET, By REGION

7.1 North America

7.1.1 U.S.

7.1.2 Canada

7.2 Europe

7.2.1 Germany

7.2.3 U.K.

7.2.4 France

7.2.5 Rest of Europe

7.3 Asia Pacific

7.3.1 China

7.3.2 Japan

7.3.3 India

7.3.4 South Korea

7.3.5 Singapore

7.3.6 Malaysia

7.3.7 Australia

7.3.8 Thailand

7.3.9 Indonesia

7.3.10 Philippines

7.3.11 Rest of Asia Pacific

7.4 Others

7.4.1 Saudi Arabia

7.4.2 U.A.E.

7.4.3 South Africa

7.4.4 Egypt

7.4.5 Israel

7.4.6 Rest of Middle East and Africa (MEA)

7.4.7 Brazil

7.4.8 Argentina

7.4.9 Mexico

7.4.10 Rest of South America

8 COMPANY PROFILES

8.1 Siemens Healthineers AG

8.1.1. Company Overview

8.1.2. Key Executives

8.1.3. Operating Business Segments

8.1.4. Product Portfolio

8.1.5. Financial Performance (As per availability)

8.1.6 Key News

8.2 Dassault Systems  

8.2.1. Company Overview

8.2.2. Key Executives

8.2.3. Operating Business Segments

8.2.4. Product Portfolio

8.2.5. Financial Performance (As per availability)

8.2.6 Key News

8.3 Microsoft Corporation 

8.3.1. Company Overview

8.3.2. Key Executives

8.3.3. Operating Business Segments

8.3.4. Product Portfolio

8.3.5. Financial Performance (As per availability)

8.3.6 Key News

8.4 Koninklijke Philips N.V.  

8.4.1. Company Overview

8.4.2. Key Executives

8.4.3. Operating Business Segments

8.4.4. Product Portfolio

8.4.5. Financial Performance (As per availability)

8.4.6 Key News

8.5 Faststream Technologies   

8.5.1. Company Overview

8.5.2. Key Executives

8.5.3. Operating Business Segments

8.5.4. Product Portfolio

8.5.5. Financial Performance (As per availability)

8.5.6 Key News

8.6 Twin Health LTD.  

8.6.1. Company Overview

8.6.2. Key Executives

8.6.3. Operating Business Segments

8.6.4. Product Portfolio

8.6.5. Financial Performance (As per availability)

8.6.6 Key News

8.7 Q Bio, Inc.  

8.7.1. Company Overview

8.7.2. Key Executives

8.7.3. Operating Business Segments

8.7.4. Product Portfolio

8.7.5. Financial Performance (As per availability)

8.7.6 Key News

8.8 IBM Corporation  

8.8.1. Company Overview

8.8.2. Key Executives

8.8.3. Operating Business Segments

8.8.4. Product Portfolio

8.8.5. Financial Performance (As per availability)

8.8.6 Key News

8.9 NVIDIA Corporation  

8.9.1. Company Overview

8.9.2. Key Executives

8.9.3. Operating Business Segments

8.9.4. Product Portfolio

8.9.5. Financial Performance (As per availability)

8.9.6 Key News

8.10 GE Healthcare  

8.10.1. Company Overview

8.10.2. Key Executives

8.10.3. Operating Business Segments

8.10.4. Product Portfolio

8.10.5. Financial Performance (As per availability)

8.10.6 Key News

8.11 ANSYS, Inc.

8.11.1. Company Overview

8.11.2. Key Executives

8.11.3. Operating Business Segments

8.11.4. Product Portfolio

8.11.5. Financial Performance (As per availability)

8.11.6 Key News

8.12 Rescale, Inc.

8.12.1. Company Overview

8.12.2. Key Executives

8.12.3. Operating Business Segments

8.12.4. Product Portfolio

8.12.5. Financial Performance (As per availability)

8.12.6 Key News

8.13 Verto Health

8.13.1. Company Overview

8.13.2. Key Executives

8.13.3. Operating Business Segments

8.13.4. Product Portfolio

8.13.5. Financial Performance (As per availability)

8.13.6 Key News

8.14 Predictiv Care, Inc.

8.14.1. Company Overview

8.14.2. Key Executives

8.14.3. Operating Business Segments

8.14.4. Product Portfolio

8.14.5. Financial Performance (As per availability)

8.14.6 Key News

8.15 Atos SE

8.15.1. Company Overview

8.15.2. Key Executives

8.15.3. Operating Business Segments

8.15.4. Product Portfolio

8.15.5. Financial Performance (As per availability)

8.15.6 Key News

8.16 QiO Technologies

8.16.1. Company Overview

8.16.2. Key Executives

8.16.3. Operating Business Segments

8.16.4. Product Portfolio

8.16.5. Financial Performance (As per availability)

8.16.6 Key News

8.17 ThoughtWire

8.17.1. Company Overview

8.17.2. Key Executives

8.17.3. Operating Business Segments

8.17.4. Product Portfolio

8.17.5. Financial Performance (As per availability)

8.17.6 Key News

8.18 PrediSurge

8.18.1. Company Overview

8.18.2. Key Executives

8.18.3. Operating Business Segments

8.18.4. Product Portfolio

8.18.5. Financial Performance (As per availability)

8.18.6 Key News

8.19 Virtonomy GmbH

8.19.1. Company Overview

8.19.2. Key Executives

8.19.3. Operating Business Segments

8.19.4. Product Portfolio

8.19.5. Financial Performance (As per availability)

8.19.6 Key News

8.20 Unlearn AI

8.20.1. Company Overview

8.20.2. Key Executives

8.20.3. Operating Business Segments

8.20.4. Product Portfolio

8.20.5. Financial Performance (As per availability)

8.20.6 Key News

Global Digital Twin in Healthcare Market Segmentation

Digital Twin in Healthcare by Types: Market Size & Forecast 2023-2030

• Healthcare Providers
• Medical Device Companies
• Pharmaceutical companies
• Research Organizations and Academic Institutions

Digital Twin in Healthcare Market by Application: Market Size & Forecast 2023-2030

• Healthcare Facility Construction and Management
• Medical Device Design and Development
• Personalized Diagnosis and Treatment Planning
• Drug Discovery and Development
• Others

Digital Twin in Healthcare by Geography: Market Size & Forecast 2023-2030

• North America (USA, Canada, Mexico)
• Europe (Germany, UK, France, Russia, Italy, Rest of Europe)
• Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Rest of Asia-Pacific)
• South America (Brazil, Argentina, Columbia, Rest of South America)
• Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, South Africa, Rest of MEA)

Major Players:

• Siemens Healthineers AG (Germany)
• Dassault Systems (France)
• Microsoft Corporation, (U.S.)
• Koninklijke Philips N.V. (The Netherlands)
• Faststream Technologies (U.S.)
• Twin Health LTD. (U.S.)
• Q Bio, Inc. (U.S.)
• IBM Corporation (U.S.)
• NVIDIA Corporation (U.S.)
• GE Healthcare (U.S.)
• NUREA (France)
• ANSYS, Inc. (U.S.)
• Rescale, Inc. (U.S.)
• Verto Health (Canada)
• Predictiv Care, Inc. (U.S.)
• Atos SE (France)
• QiO Technologies (U.K.)
• ThoughtWire (Canada)
• PrediSurge (France)
• Virtonomy GmbH (Germany)
• Unlearn AI (U.S.)