Virtual Human Twins Are the Next Frontier in Personalized Healthcare
Image Source: Wongstorn/stock.adobe.com; generated with AI
By Brandon Lewis for Mouser Electronics
Published March 14, 2025
In recent years, digital twins have shown their value across many sectors. These refined models allow industries to predict complex system behavior in a way never before possible, leading to significant improvements in critical outcomes.
While the technology is being implemented across manufacturing, automotive, and aerospace sectors, the greatest potential for digital twins may lie in the healthcare and life sciences. Virtual human twins (VHTs) could completely change everything from surgical planning and biomedical research to disease prevention.
This article looks at these hyper-advanced virtual twins, exploring how they are created, their possible use cases, and their potential in personalized healthcare.
Digital Twins and Virtual Human Twins
Digital twins are virtual models of a physical system, entity, or process. Their design typically starts with representations of individual parts, which are then assembled into more complex systems.[1] These virtual replicas then evolve as they receive data generated by the original system and its surroundings, creating and leveraging new information for predictive modeling.
A VHT is a sophisticated digital twin of a person’s body, encompassing anything from individual cells to tissues and organ systems.[2] Beyond biological characteristics, a VHT also accounts for environmental and behavioral factors and processes. For example, a cardiologist with a virtual twin of a patient’s heart could model how a cholesterol-rich diet and lack of exercise would change the organ over the course of a decade.
Because VHT technology is still in developmental stages, we are likely at least a decade away from full-body simulations.[3] However, digital twins of individual organs and body parts are already entering clinical trials and starting to be used in patient care.[4]
The European Commission has played a significant role in the ongoing development of VHTs through the Virtual Human Twins Initiative. Launched in December 2023, this initiative seeks to accelerate VHT research and consolidate the EU’s fragmented VHT ecosystem. It has already invested nearly EUR 110 million in the technology, with plans to invest at least another EUR 20 million in the near future.[5] Similar programs exist in both Canada and the United States.[6],[7]
How VHTs Are Created
In theory, creating a VHT should be no different than creating any sophisticated digital twin, comprising the following steps:[8]
- Collect initial data: Gather information about the individual from sources such as medical records, wearable technology, biometric sensor data, and connected medical systems.
- Process data: Artificial intelligence (AI) and machine learning (ML) analyze and orchestrate the collected data.
- Generate models: Using the processed data, generate 3D models of the cells, tissues, or organs being twinned.
- Collect real-time data: Continue feeding real-time information into the virtual twin as it simulates bodily functions, behavior, and environmental factors.
- Use predictive modeling: Leverage AI-driven analytics to forecast possible health conditions, assess the impact of environmental changes, warn of a potential medical emergency, and predict the possible side effects of a new medication.
In practice, modeling the human body and behavior is more informationally complex than even the most advanced industrial system. To model even a single organ, one must account for potentially billions of variables, from high-level functions down to individual cellular processes.
Due to differences in anatomy and biology, a VHT’s applicability is also limited outside of the individual from whom it was generated. For instance, two people with similar biology might react differently to a clinical drug. Environmental factors, influenced by unpredictable human behavior, introduce even more complexity.
This complexity also means that VHTs require sophisticated AI models to support them—and those models come with immense computational demands. For instance, a digital twin of the human heart developed in 2023 required a model with one billion spatial degrees of freedom. Solving a single heartbeat on eight NVIDIA A100 devices required roughly 12 hours of processing time and produced 8TB of data for post-processing analysis.[9]
Data collection is another major roadblock. Health data is far more sensitive than the information recorded by an industrial sensor. The extensive collection and processing required to create a VHT raises considerable privacy, security, and ethical concerns.
Regulatory concerns aside, creating an accurate digital replica of a human requires real-time data collection at the cellular level. Current biometric technology simply cannot capture data at that scope and scale.[10]
The good news is that we may be closer to addressing all these roadblocks than one might expect. In addition to the EU’s initiative, multiple agencies in North America (including NASA) are exploring the development of advanced VHT technology.[11] Many of these initiatives will also aid in the creation of more robust, modern data protection frameworks with clear guidelines around usage rights and data ownership.
As for computing demands, hardware grows more advanced each year, offering greater performance per watt. Meanwhile, emerging technologies such as nanobots could support targeted, real-time data collection within the human body.
Beyond these measures, the best way forward is simply to support increased investment into and education around VHTs, promoting research and development while also addressing barriers such as implementation cost.
Potential Use Cases for VHTs
In addition to patient care, advanced digital twins may also be used for everything from education to biomedical research.
Predictive, Proactive Medicine
Often, early detection of diseases results in faster intervention and a better patient outcome. Digital models could be critical in these cases, providing advanced warning of the need for treatment and predicting likely outcomes.
For people with chronic health conditions, VHTs could also provide greater autonomy through knowledge of both their illness and their treatment options. Wearable devices could play an important role in this space. Today, wearable devices focus on health and wellness, providing users with information like sleep patterns, heart rate, and blood oxygen content. VHTs could leverage this data to provide insights into the body’s inner workings. The technology could easily identify the root causes of conditions like migraines or even predict the onset of a degenerative disease.
VHTs could also help manage population-wide health issues, helping health agencies track disease spread and identify high-risk populations ahead of time.[12] VHTs, alongside real-time data collection, could prove invaluable in surveilling disease outbreaks. They may even help public health agencies prevent future pandemics.
A Better Patient Experience
Imagine going to the doctor’s office and not having to spend part of the visit trying to explain your symptoms. Instead, a physician walks into the exam room already understanding what is troubling you, guided by a virtual twin of your body and real-time data from your wearables.
Better yet, you would be able to get a firsthand look at the impact of different treatment options. Rather than looking at a list of possible side effects, your physician could use predictive modeling to show how you would likely react to a particular type of medication.
For telehealth, the benefits could be even more significant. One of the biggest challenges for remote care has been the inability of physicians to examine their patients directly. They were limited to reviewing photos, videos, and patient testimony. Leveraging VHTs and remote, Internet of Things (IoT)-enabled instrumentation, physicians could gain deep insights into patients’ health.[13]
Guiding the Health Industry’s Development
VHTs have far-reaching implications for the future. They provide researchers with a growing number of capabilities, from modeling the effects of a disease to performing virtual clinical trials of new medicines and medical devices. They can also help healthcare policymakers visualize the impact of proposed legislation.
VHTs could also change how we approach healthcare education. Through immersive training based on augmented reality (AR) and virtual reality (VR) technologies, medical students and professionals could enter the workforce with more experience and greater confidence.
Conclusion
VHTs represent a step forward in healthcare, potentially transforming clinical research and patient care. Even with technological and legislative challenges, the technology has a bright future with the ability to help others. These challenges can be overcome. After all, it was not long ago that the idea of modeling a factory floor or vehicle in real time seemed like something from the realm of science fiction.
Both are now realities, so it is only a matter of time before VHTs unlock the ultimate in personalized healthcare.
Sources
[1]https://www.mouser.com/applications/digital-twinning-types/
[2]https://digital-strategy.ec.europa.eu/en/policies/virtual-human-twins
[3]https://wired.me/science/human-digital-twins/
[4]https://www.technologyreview.com/2024/12/19/1108447/digital-twins-human-organs-medical-treatment-drug-trials/
[5]https://digital-strategy.ec.europa.eu/en/policies/virtual-human-twins
[6]https://scc-ccn.ca/resources/case-studies/digital-twin-initiative-providing-new-opportunities-canadian-innovators
[7]https://www.nsf.gov/funding/opportunities/fdt-biotech-foundations-digital-twins-catalyzers-biomedical
[8]https://www.mouser.com/applications/digital-twins-offer-insight/
[9]https://www.nature.com/articles/s41598-023-34098-8
[10]https://wired.me/science/human-digital-twins/
[11]https://iacis.org/iis/2024/4_iis_2024_287-298.pdf
[12]https://www.explorationpub.com/Journals/edht/Article/10113
[13]https://www.explorationpub.com/Journals/edht/Article/10113