Did you recently come across the term digital twins?

Your first thought might have been, “It is something related to a digital look-alike.”

Well! If not for you, we bet it was for most of the people.

In reality, digital twins is a technology that can create a digital replica of physical bodies, products, and systems. It can be used to perform various simulations, analyze problems, and help with possible enhancements, leading to many exciting advancements across different fields.

Stick with us while we explore what digital twins in healthcare actually are, how they are being used in the real world, what difference they are making for healthcare, and more.

What are Digital Twins in Healthcare?

Have you heard of a virtual model?

Digital twin is exactly that! In simple words, this is a new technology that can easily virtualize real-world systems for you. Since it is related to healthcare, this virtualization includes everything from patient records, a complete human body, to the hospital systems. Basically, both physical entities and processes can be represented through a computer system with this technology.

Let’s explore it in a real-world context to have a better understanding of it.

Recently, some researchers from Johns Hopkins University successfully developed a digital twin technology that creates a virtual replica of a heart. It is called “genotype-specific digital-twin” and nicknamed Geno-DT. It provides precise simulations of cardiac health that can help doctors with more accurate diagnoses, better treatment plans, and can also help doctors prepare for a crucial surgery beforehand.

This FDA-approved technology has been developed by the researchers at Johns Hopkins University to provide personalized treatment for ARVC (Arrhythmogenic Right Ventricular Cardiomyopathy), which is a rare genetic heart condition, and personalized treatments can be of great help to doctors treating patients with ARVC.

This development has been groundbreaking for the healthcare industry in the United States, as it can significantly reduce trial-and-error methods and improve decision-making to a great extent.

Apart from cardiovascular treatment, digital twins can be used in all parts of patient care; for example, they can easily predict how a patient might respond to surgery, optimize how an ICU is run, or find out how a new drug will behave in the human body.

We will thoroughly explore the use cases of digital twins in healthcare in this blog, but before that, let’s have a look at what the market has to say about this technology.

Is it here to stay or not?

Digital Twins in Healthcare Market

According to recent research, the digital twins in the healthcare market is estimated at USD 2.81 billion in 2025, and is expected to reach USD 11.37 billion by 2030. This means a CAGR growth of 32.31% in approximately 5 years.

You must be wondering what’s driving this growth.

This growth is due to a rise in the use of artificial intelligence all around the world. There is an increasing demand for digital solutions, including personalized healthcare, accurate predictive analysis, real-time data monitoring, and more.

By using digital twins, organisations would be able to test the processes, analyze and determine outcomes, as well as streamline the process before transferring them to real life. This all can help in minimizing the risks and saving time.

The digital twins technology is not limited only to patient care; it is also being used by some pharmaceutical firms to develop models of drug creation, by medical device makers to test their product performance, and by hospital administrators to plan and resource.

All of these use cases are also contributing to its growth and creating opportunities for businesses that are always ready to bring new solutions and improve their operations, as well as patient care.

Moreover, digital twins technology is here to transform not only the healthcare industry, but it can also play an important role in driving digital transformation in industries like manufacturing, energy, and aerospace. The overall market for digital twin technology itself is expected to be valued at approximately USD 149.81 billion by 2030.

To summarize this, let’s say this technology is here to stay and will transform many industries. So, for businesses, this space is still wide open and growing fast, which means this is the right time to discover and invest in the digital twin technology.

Types of Digital Twins in Healthcare

There are different models of digital twins in healthcare, categorized by their purpose and level of complexity. Each one is designed to address a specific healthcare need.

Let’s have a look at the main types of digital twins in healthcare.

1. Patient Digital Twin

This is like having a virtual copy of a patient’s body that helps doctors see how treatments or medicines might affect them. Think of it as a safe test run before trying anything on the real person.

2. Process Digital Twin

Instead of focusing on a person, this one looks at how healthcare processes work, like how an ICU or hospital department runs. It helps find ways to save time, cut costs, and make care smoother.

3. Surgical Digital Twin

Before a surgeon makes a single cut, they can practice on a digital version of the patient. It’s like a rehearsal, letting them plan the best and safest approach for surgery.

4. Cellular and Molecular Digital Twin

This one works at the tiniest level, the cells and molecules in the body. It helps researchers see how new drugs or treatments might behave without risking real patients.

5. Organ Digital Twin

Imagine a virtual heart or lung that reacts just like the real one. Doctors use this to understand how an organ is functioning, predict problems, and plan treatments.

6. Population Health Digital Twin

This isn’t about one person, but about whole groups of people. It’s used to see health trends, predict disease outbreaks, and improve public health decisions.

7. Progressive Digital Twin

A progressive digital twin grows and updates with new data over time. It’s more like a living copy that keeps track of changes, making predictions more accurate.

8. System Digital Twin

This is the big-picture version. It brings together patients, processes, equipment, and even staff into one digital model to see how everything works together in a healthcare system.

Digital twins in healthcare come in many forms, from copies of a single organ or patient to full models of entire systems and even whole populations. Some focus on big-picture planning, while others dive into tiny cellular details.

In simple words, they all serve the same goal to help doctors, hospitals, and researchers make smarter, safer decisions without putting real people at risk first.

Use Cases of Digital Twins in Healthcare

To best understand the applications of digital twins in healthcare, let’s imagine if doctors could test a surgery before stepping into the operating room, or see how a new drug might work without testing it on a single human being.

That’s exactly what digital twins make possible. They create safe, virtual spaces where ideas can be tried, mistakes can be caught, and better choices can be made. Here’s how they’re already being used in healthcare.

1. Personalized Treatment

A digital twin can create a virtual model of an individual patient, letting doctors test how different treatments or medications might affect them before making a real decision.

For example, digital twins can be used to design custom prosthetics and implants that perfectly match a patient’s body, or they can be used for patients with rare diseases to decide what treatment should be proposed and how the patient’s body will react to different medications. This can make healthcare more precise and personal.

2. Hospital Operations

Healthcare systems are under constant pressure to do more with fewer resources. With digital twins, administrators can simulate patient flow, staffing, and equipment usage to spot areas of gaps and improve efficiency.

For example, hospitals can test how their emergency rooms would handle a sudden surge of patients, making sure they’re prepared before it happens.

3. Medical Device Development

Device manufacturers can use digital twins to test and refine designs before building physical prototypes. This cuts costs and speeds up the process of getting safe, effective devices to market.

A good example is in prosthetic limbs and implants, where digital twins can help predict how the device will function inside the human body, reducing trial-and-error.

4. Drug Discovery and Research

Pharmaceutical companies use digital twins to model how drugs interact with the human body. This reduces guesswork in research and helps speed up development.

For example, researchers can simulate how a cancer drug might affect tumor cells or how a vaccine could trigger an immune response, without exposing patients to risk.

5. Epidemic and Public Health Management

Digital twins aren’t limited to individuals; they can also represent entire populations. Public health experts can use them to predict how diseases might spread, plan responses, and test strategies for containment.

During COVID-19, similar models helped governments decide when to enforce lockdowns or allocate resources to hospitals.

These are a few examples of how digital twins in healthcare can be a solution to a lot of challenges that are currently being faced in the healthcare sector. It is also not only about solving issues but also about making healthcare easy for doctors and hospitals by providing extra support in critical situations.

Benefits and Challenges of Digital Twins in Healthcare

Like any new technology, digital twins in healthcare come with both exciting benefits and real-world challenges. Let’s have a look at both.

Key Benefits

Personalized Care: Patient digital twins make it possible to create treatment plans with far more precision.

Better Decision-Making: Simulations help doctors, researchers, and administrators test options before acting.

Cost Savings: By reducing trial-and-error in drug research, device testing, and hospital operations, digital twins can cut expenses significantly.

Faster Innovation: From pharma research to medical devices, the ability to model virtually accelerates timelines.

Main Challenges

Data Integration: Healthcare data is often fragmented across systems, which can make it tough to build accurate twins.

Privacy Concerns: If copies or replicas of the data are being made, then patient information has to be handled with strict security and compliance.

High Investment: Developing and scaling digital twin technology in healthcare requires advanced infrastructure and expertise.

Adoption Barriers: Many healthcare organizations still struggle with trust and readiness to embrace such complex tech.

What we can conclude from these benefits and challenges is that the benefits are huge, but the industry needs to address these challenges to easily use and unlock the full potential of digital twin applications in healthcare.

The Future of Digital Twins in Healthcare

For now, let’s say that the story of digital twins in healthcare is still in its early chapters because, as of now, most projects are focused on pilot programs or specific use cases, but after looking at the use cases and benefits, we can surely say that it has a lot of potential. As AI, machine learning, and real-time data collection continue to advance, digital twins will become more accurate and more widely adopted.

One of the biggest shifts we’ll see is in predictive healthcare. Instead of reacting to illness, doctors will be able to use patient digital twins to find out problems before they happen and make important decisions earlier. This could transform chronic disease management, surgical planning, and even everyday preventive care.

Another area with huge promise is the integration of digital twin technology in healthcare with large-scale hospital systems and even entire healthcare networks. Imagine being able to simulate the impact of a new treatment protocol across thousands of patients or preparing an entire hospital for a sudden surge in cases before it happens.

The digital twin in the healthcare market will also keep expanding as more organizations realize the cost savings and efficiency gains. For businesses and innovators, this means plenty of room to experiment, scale, and shape the direction of the industry.

What this really points to is a healthcare future that is more personalized and smarter than anything we’ve seen before.

And for anyone thinking digital twins would replace doctors or hospitals,

Digital twins will just make them more capable than ever.

Partner with DigiTrends for Digital Twin Adoption

At DigiTrends, we believe the rise of digital twins in healthcare is a chance to redefine how patient care is delivered and how hospitals operate. By combining data, AI, and innovation, we help healthcare providers, med-tech companies, and startups bring digital twin solutions to life.

Our expertise spans healthcare platforms, predictive modeling, and AI-driven applications that enable personalized patient care, efficient hospital management, and smarter decision-making.

With a strong track record of building scalable healthcare solutions, DigiTrends works side by side with organizations to design and implement digital twin applications in healthcare that deliver real impact.

From improving operational efficiency to supporting compliance and accelerating innovation, our goal is simple: to help you unlock the full potential of digital twin technology in healthcare.