Digital Twin Technology – Assessing the Growing Role and Its Evolving Applications in Healthcare Market

The rapid growth in technology and innovation are bringing new opportunities and scope for simplification in product development and process and are creating comfort and simplifying lives in their own way. The ongoing breakthroughs and innovation are leading to better outcomes/productivity, saving time, increasing efficiency, quickness, and other benefits, thereby making life more comfortable. Artificial intelligence and machine learning, robotic process automation, virtual reality and augmented reality, and blockchain, among others, are some of the cutting-edge emerging technologies that are set to impact our daily lives significantly in the coming years These technologies are driving the fourth industrial revolution and are currently in the initial stages of development, and immense growth is expected in the near future. These technologies, in a way, are anticipated to transform how we live and how we will interact with each other and our surroundings in the future.

Similarly, Digital Twin is also one of the emerging and advantageous technology, gaining immense attention across different industries. Digital Twins are a replica of real-world objects in digital form and based on the what-if scenarios. It has several benefits and advantages across fields. It will likely play a key role in effective research and product design and delivery, thereby opening doors for new business opportunities. Additionally, it can help predict uncertainties and give early warnings, boosting productivity, streamlining operations, increasing profits, and reducing costs. The growth and development of allied technologies such as Big Data, AI, ML, and the Internet of Things are providing tremendous growth to the Digital Twin Technology. 

Understanding What Digital Twin Is and Their Use Across Industries

The concept of Digital Twins has been around us since 2022; however, the concept has gained moment in recent years only. The concept was coined and nurtured at NASA, which employs the full-scale mockups of technology for early space capsules used on the ground to mirror and diagnose problems in orbit, which later on eventually gave way to fully digital simulations.

The development of the Internet of Things (IoT), artificial intelligence, machine learning, data analytics, and their cost-effectiveness have led to gains in the Digital Twin Technology concept. There are many definitions of Digital Twins. However, in simple terms, it refers to a digital replica, virtual copy, or models of a real physical asset or place, such as a device, process, product, vehicle, equipment, or any other object. The digital counterpart or virtual object of real-world things helps to evaluate the practical applications such as testing, system stimulation, maintenance, and monitoring, pre-launch assessment of the product. 

Digital-twin model mimics the device, and evaluating the product performance & figures out the issue before final production, thereby maintaining a huge scope to reduce the cost and manpower wastage. Manufacturing, automotive, supply chain, architecture, construction, real estate, telecom, and retail are some of the major industries implementing the Digital Twin Technology to improve operational efficiency and processes. Similarly, it holds the potential to offer many significant benefits to the healthcare industry in almost every arms and segment. Many tech companies and startups across the industry are actively working in Digital Twin Technology to take the early advantage and gain market share.

Digital Twins in Healthcare

The Digital Twins has many benefits they offer to the Healthcare industry. The data collected across various sources, i.e., from individuals’ health history, present medical conditions, current drug and therapy responses, lifestyle, including biophysical and behavioral stats, the surrounding ecosystem, and the multiple internets of medical things (IoMT) devices can be used to create a patient’s digital twin. It is estimated that the growth in wearable sensors will also play a key role in the Digital Twins adoption in the Healthcare segment. The wearable sensors can collect a wide range of vital data on a real-time basis that can be transferred and fed continuously to a remote server holding the digital twin of the user. The digital human blueprint can help detect predicting future health issues and can be used to suggest a treatment plan. Digital twins rely on data generated from multiple sources and use AI-powered models to suggest tailored and more suitable treatment plans. It can create a big impact on the management of chronic diseases. Additionally, it has a huge scope on device manufacturing, drug development, and hospital management. 

In the future, Digital Twins can play a major role in advancing the healthcare industry’s growth in terms of clinical trial design, diagnosis, treatment, and follow-up care. Moreover, it can enhance the service delivery, care coordination, operational efficiency, and effectiveness of the organizations working in the healthcare segment to a much large extent. The ongoing research and development are just the beginning, and they only symbolize the tip of the iceberg; in the future, it can be a major market drive and trendsetter technology in the healthcare industry. 

Digital Twins in Healthcare – Major Applications and Segments

Digital Twins can be implemented in almost every arm of the healthcare industry. With the ongoing innovations, the application is widening to new areas, which were hard to imagine a few years back. Some of the key applications include – 

Digital Twin In Personalized Medicine

Digital twins have amazing potential in the care segment. One of the major applications of Digital twins in the human body is modeling organs and single cells or an individual’s genetic makeup. All these services can be utilized to create personalized medicine and treatment plans for the individual as they are based on their unique genomic makeup, anatomy, physiological characteristics, lifestyle habits, and behavior. It can provide a more individual focus treatment plan than precision medicine which generally concentrates on small sample groups. However, developing replicas or Digital twins for a human body is more complex than other processes and products as the human body consists of several elements, which can be time-consuming and expensive. Virtual organs, planning surgery, genomic medicine, and personalized health information are other major segments where the Digital twin can be easily implemented. 

Digital twin in Personalized diagnosis and treatment

In the diagnostics segment, the doctor or physician can use the Digital twin to aggregate and collects the medical information and other vital states (such as blood pressure, oxygen levels, etc.) and overlays it onto a model of the standard human body and can create a personal medical/treatment plan for the patient. The digital twin can exhibit how exactly the real-life body functions during diagnosis or at that exact juncture. The doctor can compare the virtual version of a patient to a physical condition or history. It will make it easier for the doctor to customize the treatment plan based on the diagnosis and customize the simulations to track the reactions in the body. Similarly, the large amount of data generated by the twin will determine if the medication works as expected and how each of the patients is reacting to the different treatments based on their diagnosis. In the treatment planning, the surgeon, through the advanced modeling of the human body, can create a  dynamic digital human twin. The digital human twin can be used to monitor health, alert the system and identify the pathology before the disorders are evident, and enhance the surgical outcome.

In the coming years, with the rise in the adoption of smartphones, billions of people worldwide are expected to get free access to digital human twins, which can play a key role in monitoring and tracking their health stats continuously. Similarly, if changes are recorded in the body, the user can get the more relevant healthcare higher-resolution combination tests recommended by the digital human twin and paid for by their healthcare system.

Digital twins in Drug Development 

Digital twins of drugs and chemical substances can aid the clinical researcher in altering or redesigning drugs that are under development. They can easily modify the particle size and adjust the elements to improve efficiency. Similarly, the virtual human twin is a safer option for testing medications and ceratin making assumptions about effectiveness. In the drug development segment, the digital human twins can simulate how people will respond to certain treatments or drugs. If the person is not responding well to the treatment, digital human twins can provide key insights into human biology by testing different biomarkers. It can evaluate how medication might personally affect their patients and adjust the dosage to that person’s needs. In the long run, it can cut costs and save time from the traditionally expensive, lengthy clinical trials. Moreover, Digital twins can be employed to classify and identify drug risks. 

Digital twins in Devices Trials and Manufacturing

Device development is one of the segments that take huge time, and investment and costs of failures are also high. With the digital twins, both aspects can be addressed easily while enhancing performance and unlocking more accurate monitoring of medical devices. In the devices segment, the digital twins of a medical device allow the developer or manufacturers to test the features or uses of a device as it can mimic the device’s behavior and functions. Moreover, they can be tested for the success or failure of the modifications in a virtual environment before final launching. Overall they can increase the safety profile of the final product before they are manufactured in large quantities. 

Additionally, software-as-a-medical devices, stimulating new production lines, streamlining the entire production facility, supply chain resilience, post-market surveillance, and enhancing the device uptime are other potential applications of the Digital Twin in the medical devices market.  

Improving healthcare organizations

The Digital Twin can help healthcare organizations improve the efficiency and effectiveness of service delivery.  Improving the patient experience and treatment journey, shrinking critical treatment window, faster hospital construction, value-based healthcare, digital twin of a lab, simulating human variability, and streamlining the patient interaction, are some of the major applications of the Digital Twin Technology in the healthcare industry.

Deployment of digital twins can greatly help in the planning business process,  identify irregularities, shorten the service time, avoid unfavorable circumstances, and improve operational workflow. The ultimate aim of Digital Twin Technology in healthcare is to improve the healthcare organization’s efficiency and profitability while improving their care delivery.

Major Companies in the Healthcare Digital Twin Technology Market

Digital Twin is an untapped market, and globally, several prominent MedTech and HealthTech companies are actively working to explore the potential of Digital Twin in the healthcare segment. Some of the key companies in the Healthcare Digital Twin Market include NUREA, PrediSurge, Predictiv, Q Bio, Virtonomy.io, Sim&Cure, Optimo Medical, General Electric, Ansy, Atos, Dassault Systems (3DS Company), Philips Healthcare, Siemens, Twin Health, Verto Health, Fasttream Technologies, ThoughtWire, Sim&Cure, Optimo Medical, and several others. 

Companies are working on diverse aspects to cater to the different needs, deliver the desired solution and take the lead in a particular segment. For example,  NUREA, a France-based startup, is working on designing and developing artificial intelligence (AI)-based digital twin imaging software for cardiovascular surgeons. Philips is working on modeling the heart. US-based startup Predictive is working to develop a model to predict genetic disorders in patients utilizing their DNA-based digital twin. Hewlett Packard (HP) is working to create digital models of the brain.

Healthcare Digital Twin Market Dynamics

Digital Twin in the Healthcare industry is set to grow at an immense pace in the coming years owing to the boost in the research and development (R&D) activities, rising awareness among the general population about Digital Twin’s potential benefits and applications, and active participation of the global tech giants in the segment. Additionally, wide-scale adoption and implementation of AI and IoT technologies will also drive the growth of the Healthcare Digital Twin Market in the coming years. 

However, high investments in the implementation stage, lack of skilled professionals, data quality, and data privacy are some of the key challenges expected to hamper the Healthcare Digital Twin Market growth. The low data quality can negatively affect the trustworthiness of the models designed for assessment in the diagnosis and treatment processes. Similarly, data privacy is one of the great challenges in almost every industry, and in healthcare, it negatively impacts the user’s trust due to its sensitivity to extremely personal data.

Healthcare Digital Twin Market – Future Perspective 

Healthcare Digital Twin is in the infancy stage at present. Several key developments, innovations, and research are going on to execute its application in the healthcare industry. In the future,  Digital Twin can play an important from clinical trial design to drug development, from diagnosis to care coordination, and from streamlining the healthcare process to improving the caregiver experience. Due to its more personalized, efficient, and predictive qualities, the Digital Twin is one of the right approaches in the healthcare segment that can make healthcare delivery accessible to everyone. Overall, Digital Twin has a huge potential in the healthcare market and can save countless lives while dramatically reducing healthcare costs and reducing the burden on the healthcare system.