The Role of Digital Twin in Healthcare: Virtual Patient Models & Beyond
- Anuj Abhiwan
- 4 days ago
- 5 min read
Updated: 4 hours ago

Technology is growing fast in many industries. One of the most effective industries is healthcare, which uses advanced technologies that help doctors, hospitals and patients. One of the most popular technologies is the digital twin in healthcare. Not only in healthcare, but it is also used in many industries. This technology creates virtual models of patients, organs, and hospitals. These virtual models will help doctors to predict problems, treatments and personalised care. We’ll know about the detailed information of it, how it works in healthcare, challenges, and opportunities.
What is Digital Twin?
The digital twin is a virtual copy of the real objects that are computer-made versions. It works as a real object. They look, behave, and react like real objects. If the patient’s heart rate changes, the digital twin helps to show how the body might react, which will help Doctors to test treatments safely.
When entering digital twin in healthcare industry, it can be a copy of:
The human body or organs,
Hospitals or machines,
Treatment or medical process.
The Virtual Patient Models
The virtual patient model is the most important use of digital twin applications in the healthcare industry. These models are like virtual humans.
These help in
Medical history.
Scans such as an MRI and a CT scan
Genetics disease
Lifestyle habits
Realtime data
Through these data, doctors can do many things, like treatments, predictions, and tracking diseases.
Predict how the patient responds to the drug
Track disease
Plan surgery with accuracy
Treatment without any risks.
For example, a patient survives heart disease, and a digital twin in healthcare shows how it pumps blood. A doctor can give treatment accordingly.
How to create a Digital Twin?
Digital Twin has many steps, such as purpose, modelling, installation and many more.
Here is the complete information:
Define the purpose
Create the virtual model
Install IoT sensors.
Connect IoT to the cloud.
Link real-time data.
Analytics for AI
Monitoring and optimize
Stage | Details | Tools/Technologies |
Define Objectives | Identify the purpose: monitoring, simulation, optimisation, or predictive maintenance. | Business Analysis Tools |
Select Physical Asset/System | Choose the real-world asset (e.g., machine, building, vehicle) to model. | Asset Management Tools |
Instrument with Sensors | Attach IoT sensors to collect real-time data such as temperature, vibration, pressure, etc. | IoT devices (e.g., Arduino, Raspberry Pi, Siemens) |
Data Acquisition | Collect and transmit data from the physical asset to a centralised platform. | MQTT, OPC-UA, AWS IoT, Azure IoT Hub |
Data Integration | Integrate sensor data with enterprise systems (ERP, MES, CRM). | APIs, Middleware, Integration Platforms (MuleSoft, Zapier) |
Create 3D/2D Model | Build a virtual representation (CAD or real-time 3D model). | Unity, Blender, AutoCAD, Unreal Engine |
Build Simulation Model | Simulate behaviour using mathematical or physics-based models (digital logic, AI, ML). | MATLAB, Ansys, Simulink, Python + TensorFlow/PyTorch |
Link Physical & Digital | Map real-time sensor data to the virtual model for mirroring and analysis. | Digital Twin Platforms (Azure Digital Twin, Siemens NX) |
Enable Real-Time Monitoring | Provide live dashboards for visualisation, monitoring KPIs, and health status. | Power BI, Grafana, Tableau |
Apply Analytics/AI/ML | Use historical + real-time data to predict failures, optimise performance, and prescribe actions. | Python, R, Azure ML, AWS SageMaker |
User Interface | Develop a front-end dashboard for interaction and control. | Web (React, Angular), Mobile (Flutter, Swift) |
Test & Validate | Compare Digital Twin results with real-world outcomes to calibrate models. | Simulation Validation Tools |
Deploy & Maintain | Deploy the system, monitor performance, and refine models based on new data. | DevOps, CI/CD Tools, Cloud Services |
Benefits of Digital Twins in Healthcare
The digital twin in healthcare has some major benefits, such as personalised treatment, better surgeries, disease prevention and monitoring.
Here are the detailed benefits of the digital twin:
Personalised Treatment
Doctors offer treatment according to your body and the disease. It helps them to see how the body reacts after the treatment.
Better Surgeries
Surgeons are using the digital twin for practising before the operations. This will help to make the surgery successful and faster.
Disease Prevention
The Digital Twin in Healthcare will help to diagnose the disease early which will help to treat the disease before it gets serious.
Remote Monitoring
The wearable devices and twins help to monitor every disease.
Training for Doctors
Medical students receive training on virtual models of patients that prevent real-life risk.
Digital Twins of Organs
Digital twin is not made for a single organ or any treatment. These models are used by AI , which makes twins smart.
They are made for many organs that will help with treating multiple diseases:
Heart twin is used to study blood flow, blockages and planning of heart surgeries.
Lung CT is used to diagnose lung diseases like asthma and COVID-19.
Brain twin is used for epilepsy, brain tumours or planning neurosurgeries.
Digital Twins of Hospitals
The Digital twin is not only for doctors or patients but also for hospitals. They can be used in emergencies to store data on patients.
The entire hospital management needs these twins for:
Bed availability
Staff scheduling
Equipment use
Emergency response planning.
What is a Digital Twin in healthcare?
As mentioned above, you know about the digital twin in the healthcare industry.
Here you can learn everything in a summarised form:
Aspect | Details |
Definition | A Digital Twin in healthcare is a virtual model of a patient, organ, device, or healthcare system that mirrors its real-world counterpart using real-time data. |
Purpose | To simulate, predict, and optimise health outcomes and medical procedures. |
Data Sources | Electronic health records (EHRs), medical imaging, wearable devices, lab results, and genetic data. |
Types | 1. Patient Digital Twin – a personalised care model of an individual. 2. Device Digital Twin – Tracks and predicts the performance of medical devices. 3. Hospital/Workflow Twin – Optimises hospital operations. |
Applications | Personalised treatment planning Surgery simulations Chronic disease management Drug response modelling Hospital logistics and resource management |
TechnologiesUsed | AI IoT, machine learning, cloud computing, big data, sensors, digital imaging |
Benefits | Improved diagnosis accuracy Customised treatment plans Predictive analytics Reduced costs Enhanced patient safety and care quality |
Example Use Cases | A Heart Digital Twin Predicting Arrhythmia Risk A virtual ICU model optimising staff allocation A digital twin of a cancer patient simulating drug response |
Challenges | Data privacy and security Integration with legacy systems High cost of implementation Regulatory compliance (e.g., HIPAA, GDPR) |
Digital Twin Companies in India
Many companies in India, like TCS, L&T Technology, Tech Mahindra and Abhiwan Technology, are top digital twin service providers.
Here is the top list of the digital twin companies in India:
Company Name | Headquarters | Key Services | Industries Served |
Tata Consultancy Services | Mumbai | Digital twin platforms, IoT integration, and analytics | Manufacturing, Healthcare, Utilities |
L&T Technology Services | Vadodara | Digital twins for industrial plants, smart buildings, and aerospace | Oil & Gas, Automotive, Aerospace, Industrial |
Abhiwan Technology | Noida, Delhi NCR | Digital twin development, metaverse, AR/VR, AI, blockchain | Real Estate, Retail, Gaming, Smart Infrastructure |
Infosys | Bengaluru | Engineering services, AI-driven digital twins | Energy, Utilities, Telecom, Manufacturing |
Tech Mahindra | Pune | AI + IoT + digital twin solutions, predictive analytics | Automotive, Healthcare, Industrial, Telecom |
Siemens India | Mumbai | Digital twin software (Simcenter, Teamcenter), simulation tools | Industrial Automation, Railways, Smart Cities |
GE Digital | Bengaluru | Predix platform for digital twins, asset performance management | Power, Aviation, Manufacturing |
Bosch EngineeringIndia | Bengaluru | Digital twin for connected mobility, predictive maintenance | Automotive, Manufacturing, Smart Devices |
Tata Elxsi | Bengaluru | Digital twins for smart mobility and simulation environments | Automotive, Aerospace, Consumer Electronics |
Dassault Systèmes India | Pune | 3DEXPERIENCE platform, virtual twin experiences | Aerospace, Life Sciences, Industrial Equipment |
HCLTech | Noida | Digital twin & IoT integration, asset monitoring | Smart Manufacturing, Energy, Infrastructure |
Cyient | Hyderabad | Digital twin modelling, simulation, and engineering design | Aerospace, Rail, Utilities, Telecommunications |
Altair Engineering India | Bengaluru | Physics-based digital twins, simulation software (HyperWorks) | Engineering, Automotive, Aerospace |
EInfochips | Ahmedabad | Digital twins, edge computing, and remote monitoring | Healthcare, Industrial, Automotive |
Conclusion
The Digital twin in healthcare is best for planning and tracking the data of the healthcare process. In the future, the use of digital twin applications will be growing. The technologies will help understand medication and treatments, and keep people healthy. From virtual patients to hospital management, the technology will help from every perspective. The technologies have many obstructions, such as cost, privacy, and lack of standards. Beyond these hurdles, the healthcare industry is still smarter, faster, and safer with the help of these technologies.
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