Introduction: how digital twins are personalising healthcare

In healthcare, “digital twins” (DTs) are virtual replicas of actual individuals, providing doctors valuable insights to customise treatment plans and ensure personalised care.¹ These twins mimic intricate physiological procedures, minimise animal testing, and help connect laboratory findings to anticipated in vivo results.¹ As such, digital twins may enable better supervision and diagnosis, the creation of tailor-made therapies, and enable doctors to predict a patient’s response to a given drug. Ultimately, they promote personalised healthcare while paving the way for future breakthroughs.¹

A digital twin is essentially a virtual duplicate of a physical entity, process, or service. Digital twin technology surpasses mere modelling by merging both realms digitally and physically.² By employing advanced technology like smart sensors, artificial intelligence, and data analytics, digital twins can identify issues beforehand, boost efficiency, and uncover new possibilities within healthcare.² However, their true value lies in advancing medical research and enhancing clinical and public health outcomes via personalised medicine. These outcomes require meticulously modelling each person's distinct biology.²

Healthcare digital twins include virtual likenesses of people, their body parts, or even hospitals, amalgamating various data types. The data used to create digital twins can be drawn from electronic health records (EHRs), disease registries, and omics data, as well as accumulated demographics and lifestyle habits.³ 

Utilising this wealth of information, digital twins may provide dynamic models capable of improving precision medicine, assisting decisions, and streamlining hospital management via simulations, forecasts, and real-time surveillance.³ Furthermore, digital twins may help medical professionals predict a patient’s response to a given treatment based on their genetic makeup, lifestyle, and medical backgrounds.³ Additionally, digital twins may be useful in designing clinical trials and refining their operational efficiency, as researchers can use them as virtual control groups..³

Overview

Digital twins are promising to make healthcare more about you. Here’s how:⁴

• Tailored care: your digital twin is designed to make sure your health care is just right for you, considering your unique health profile.
• Smart treatments: by diving deep into how diseases work, digital twins may help researchers discover new ways to treat illnesses without having to experiment on animals or real people first.
• Testing without risk: before any new medicine or device is used on humans, digital twins could test them virtually, which means safer healthcare innovations.
• Cutting costs: digital twins could help save money by reducing the number of unnecessary hospital visits and ensuring resources are used wisely.
• Learning for doctors: medical students and professionals may learn through realistic simulations, making their education more interactive and informative.

How digital twins make healthcare better for you

Here are some instances highlighting the beneficial influence of digital twins on healthcare, primarily focusing on precise tracking and individually catered therapies. An artificially intelligent pancreas accurately anticipates blood sugar levels and diminishes recalibration requirements, revolutionising diabetes management.¹ Similarly, Cardiac Digital Twins (CDTs) craft specialised healing pathways by emulating particular heart conditions relevant to every patient.¹ Also, examining cells one-by-one improves understanding about how cancer develops and spreads, which might eventually lead to more concentrated treatment options.¹

Individualised therapy based on each person's health profile

When treatments adapt to individual health circumstances, there's a noticeable improvement in patient welfare.³ Implementing this strategy wisely manages available resources while achieving desirable outcomes. Subsequently, everyone involved in the healthcare sector enjoys its positive impacts.

More efficient clinical trials using virtual simulations

Employing virtual simulations reduces time and expenditure for clinical trials, which have historically been characterised by high costs and prolonged durations.³ As a result, experts can rapidly examine data and design new and essential drugs, extending faster access to treatment for many people.

Effectively managing hospitals with anticipatory tools

Utilising predictive tools enables professionals to estimate forthcoming patient volumes together with material necessities. This knowledge promotes more efficient hospital governance.³ Equipped with such far-sightedness, officials strategically allocate supplies and preserve optimal functioning amidst fluctuating demand cycles, persistently raising general care standards across all facilities.

Real-world uses of digital twins: from heart care to cancer and migraine treatment 

Digital twins are like high-tech digital copies of our bodies health, from our hearts to how diseases like cancer or headaches manifest. These digital helpers use computer power to mimic the real-life workings of our bodies, helping doctors figure out the best way to treat us. These are a few examples of how DTs are changing things:

• Custom care: digital twins help doctors create treatments that are just for you, looking at everything from your DNA to your daily habits.⁵ For example, by simulating how your heart works, doctors can plan surgeries or treatments that match your body perfectly.³
• Fighting cancer: digital twins are a big help in cancer care, too, letting doctors design personalised therapies in cancer treatments like neoantigen identification for tumour immunotherapy - treatments that target cancer cells in a way that is tailored to you.⁵ Moreover, by looking at cells one at a time (single-cell RNA sequencing), researchers can find new ways to tell different types of cancer apart, leading to better treatment​.¹ Additionally, scientists are making digital lungs to find new ways to fight lung cancer, aiming for treatments that go right where they're needed.³
• Heart health: projects like The Living Heart make a digital version of a heart to test treatments and design medical gadgets.³ Similarly, health tech companies are using millions of images to create heart models, helping to spot and fix heartbeat issues with 3D maps.³ These 3D scans can predict heart problems, keeping an eye on heart health without invasive tests.¹
• Straight smiles: in orthodontics, digital twins help plan treatments to get the perfect smile, using 3D images to customise care.²
• Multiple sclerosis (MS) management: DTs are also used to figure out the best way to manage MS, helping predict how the disease might progress.²
• Liver health: a digital liver helps doctors understand how different treatments can affect liver function, aiming for the best outcome.²
• Artificial pancreas: this device watches your blood sugar and adjusts insulin, making life easier for people with diabetes.¹

In simple terms, digital twins in healthcare are giving us a glimpse into a future where treatments are more personalised, effective, and designed just for us, making a big difference in how we fight diseases and stay healthy.

Making migraine management smarter with digital twins

Digital twins are changing how we handle migraines. Here’s how:⁴

• Gathering your health data: by collecting info from things you might wear (like a smartwatch), your doctor's notes, pictures from inside your body, and even your genetic information, doctors can make a super-detailed digital version of you. This big collection of data helps make your digital twin as accurate as possible.
• Predicting migraines before they start: using data from wearable devices, such as your heart rate or how warm your skin is, artificial intelligence (AI) can offer real-time tips to manage your migraines better. Doctors can get better at guessing when a migraine might hit, meaning they can give you a heads-up before it hits.
• Understanding what sets off your migraines: digital twins help doctors explore how different things in your life (like what you eat, your routine, or even other medicines you take) might affect your migraines. It's all about getting to know this complicated condition better.
• Virtual testing: doctors can use DTs to try out different ways to handle your migraines. They can test how you might respond to various treatments without any real-world risks. This means they can figure out the best plan for you before you even take any medication.

In short, digital twins in migraine care are like having a rehearsal space for doctors to figure out the best way to tackle your migraines, making treatment personal, precise, and proactive.

Creating your digital health avatar: a simplified science

The process of developing a digital health avatar (DT) involves integrating diverse data types. This integration is challenging due to the need for standardising and combining different forms of data, such as medical images, heart rate data, and comprehensive health metrics, all while maintaining accuracy in the digital representation of an individual's health. As such, advanced computational techniques and a team with extensive and varied expertise are needed to achieve this.¹

Keeping your digital twin up-to-date

DTs are advancing personalised medicine by integrating extensive health data and utilising technologies like AI, Internet of Things (IoT), cloud computing, and virtual or extended reality (VR/XR).^3,4 These technologies enhance data analysis, simulation capabilities, and real-time monitoring.³

Digital twins remain accurate through continuous updates. This involves running simulations and comparing the results with real-world data, requiring expertise from biomedical, engineering, and computer science fields. However, there's a noted gap in establishing clear validation processes for DT models in healthcare.³

To ensure precision and utility, various methodologies are employed, including continuous monitoring and sophisticated algorithms designed for specific health conditions. For example, cardiac DTs use specific models to simulate heart functions, while glucose monitoring systems rely on different algorithms to manage diabetes. Moreover, cell-level analyses incorporate genomic data and metabolic rates.¹

Artificial intelligence (AI) and machine learning (ML) are pivotal in processing and modelling data, leading to improved predictive accuracy. These models benefit from large, diverse datasets and are validated by comparing simulated outcomes with actual data. The incorporation of real-world data from wearable devices enriches these digital twins, enabling continuous refinement and validation against physical counterparts.⁴

Challenges of bringing digital twins into your healthcare experience

Introducing digital twins to healthcare isn't without its hurdles. Here's a breakdown of the main challenges:³

• Gathering and managing data: it's a complex task to combine all sorts of health information from electronic health records (EHRs), body scans, and wearable devices into one place. Combining all different health data and making sure the digital twin really matches up with real-life biology is the main tech challenge. There’s also a lack of standards for structuring and managing patient data flows for digital twins that needs to be addressed for a successful integration of this tech into healthcare.
• Making it user-friendly: doctors need easy-to-use tools to understand and use digital twin data. This requires experts from different fields to work together.
• Ethical and privacy worries: there are big questions about who gets to see your health information and how to make sure no one is left behind because they can't access this kind of care. Understanding how much this all costs and making sure it's accessible is key. 
• Building trust: some doctors might worry about relying too much on what a computer model says or even feel like these tech tools could take over their jobs. Helping doctors and patients feel confident in these digital tools and what they can do is a top job.

Technical, regulatory, ethical and economic barriers need to be overcome for digital twins to be successfully translated into standard clinical practice.⁴

Your future health companion: the digital twin

Looking ahead, digital twins are expected to get even smarter, offering more detailed and accurate models of patient health. This means care that’s even more customised and effective treatments. As technology gets better at collecting and analysing health data, these digital doubles could play a huge part in changing how we get better and stay healthy.¹

Technologies shaping the next wave of healthcare

For digital twins to really take off, we’re looking at some key tech developments:⁴

• Cloud power: massive online storage and computing power to handle all this health data.
• Virtual worlds: using virtual, augmented and extended reality (VR/AR/XR) for a new way to see and understand health information.
• Tiny tech monitors: biosensors and nanosensors that keep an eye on your health in incredible detail.
• Ultra-fast internet: thanks to 5G, real-time health data can be streamed directly from gadgets you wear.
• AI and machine learning: advanced artificial intelligence and machine learning techniques, like deep learning, will be needed for sophisticated data integration and simulations.
• Privacy-friendly computing: blockchain and distributed computing paradigms like federated learning that train models without compromising your privacy. Federated learning allows models to be trained across multiple decentralised devices or servers holding local data samples, without exchanging them. This method is particularly useful for privacy preservation, as it doesn't require sending sensitive or personal data to a central server.

Future Medicine: remote doctor’s exam with digital twin. Image by GenAI Stable Cascade

As digital twins evolve, they’ll be powered by AI, deep learning, and other cutting-edge tech. These advancements will likely make digital twins more accurate and also allow for real-time health tracking and sophisticated health simulations. The goal? A healthcare system that’s more effective, personalised, and secure, thanks to enhanced data analysis, privacy, and system integration​.

Summary

Whilst still in the early stages of development, digital twins present a promising avenue to achieve higher precision, efficiency and optimisation across various domains of healthcare delivery and operations. Overcoming the existing technical, regulatory and social barriers will be crucial for unlocking their full transformative potential.

Key benefits of digital twins:

• Personalised treatments: digital twins tailor healthcare to your unique profile, improving how diseases are treated and managed.
• Innovative simulations: they test treatments and medical devices in a virtual environment, ensuring safety and effectiveness before real-world application.
• Cost efficiency: by optimising resource use and reducing unnecessary hospital visits, digital twins could save money.
• Educational tools: they serve as advanced learning platforms for medical professionals, enhancing training with realistic simulations.

Real-life applications:

• Diabetes management: an AI-powered pancreas predicts blood sugar levels, revolutionising diabetes care.
• Heart care: Cardiac Digital Twins (CDTs) allow for customised treatment plans, offering new hope for heart disease patients.
• Cancer treatment: tailored cancer therapies and in-depth cell analysis promise more effective treatment options.
• Migraine relief: digital twins predict migraines and test treatments, offering a proactive approach to management.

To sum up, digital twins technology offers a glimpse into a future where medical care is more responsive to the individual needs of each patient.