Prof. Dr. Shabbir Syed Abdul, Professor of Artificial Intelligence & Digital Health, Graduate Institute of Biomedical Informatics shares how using digital twins in healthcare is revolutionizing clinical processes and hospital management by enhancing medical care with digital tracking and advancing the Modeling of the human body.
With the advent of technologies, such as big data, cloud computing, and the Internet of Things (IoT), a digital twin is being applied in different domains as a precision simulation technology from concept to practice . Simulation plays a very extensive role in the healthcare field, particularly in research on medical pathway planning, medical resource allocation, medical prediction, etc.
Historically, the expression ‘digital twin’ is related to the nowadays more common notion of a ‘digital model’ As early as 1960, radiologists have started using rudimentary computational models of phantoms that are objects employed in medicine or other fields to replicate the reaction of human tissue to certain processes, e.g., to radiation. The digitalization of phantoms resulted in digital phantoms that are in many ways the ancestor of the digital twin.
It is then not surprising that the earliest use of the expression digital twin appeared in 1994 in the field of medical imaging (10). Incorporating digital twins in healthcare can give rise to an innovative and efficient approach to providing more accurate and fast services for those suffering from chronic disorders. The Digital Twin of a patient is created by transferring the patient’s genomic or clinical data (EHR) and real-time changes in the body parameters (Behavioural Data) to the digital environment .
The use of digital twins in healthcare is revolutionising clinical processes and hospital management by enhancing medical care with digital tracking and advancing the Modeling of the human body. These tools are of great help to researchers in studying diseases, new drugs, and medical devices. This technology offers new and definitive solutions for correct diagnosis and subsequent treatment processes appropriate for the patient, which is one of the most important principles of personalized medicine . However, the methods to achieve personal health management throughout the entire lifecycle of these patients, and ways to combine the medical physical world and the virtual world to comprehend real smart healthcare, have limited research in precision medicine .
The healthcare sector requires higher accuracy in diagnosis and treatment, with the valuable data from IoT, digital twins can play a crucial role by reducing the hospital expense for the patient, providing precautionary alerts to avert health deterioration, and giving tailored health support systems . Thus, the digital twin framework is a beneficial contribution to digital healthcare and to improving healthcare operations .
Agent-Based Digital Twin’s Model
It was introduced by Croatti et al  and this model refers to the integration of digital twins with agents and Multi-Agent Systems (MAS) technologies in healthcare. This model represents all the features and aspects of the physical asset to which the DT is coupled through a cyber-physical connection, properly defined. Agents can observe and connect with the digital twin by exploiting the digital twin’s operations – as well as humans can interact with the coupled physical asset. Finally, the digital twin could also communicate directly with external sources of information, i.e. other software systems, and sensors. (Figure 2).
Aspects of DT in India
Industry 4.0, evolved in 2011 with the concept of smart manufacturing for the future development to increase mass production with the emergence of data-driven technologies. But industry 5.0 is an evolution of the future which is designed to use the creativity of human minds with the help of artificial intelligence and machine learning approaches . The scenario of the digital twin is still an infant in India, with the great promises, this nascent technology allows a real-time look at industrial processes.
Coupled with the IoT and AI, it opens new vistas of improvement and innovations in the various domains of the industry, and the Healthcare domain is one of them as there is an increase in using IoT- based healthcare devices and prediction models for the understanding the anatomy and physiology of the human body and related various lethal diseases. There is only a US-based DT industry by the name of Twin Health. But the Digital twin has a wide potential for research and DT development in the Indian population due to the presence of a wide diversity of people with lots of medical data-driven industries. For E.g., Twin Health (Digital Twin -Based Indian Start-up) invented the ‘Whole Body Digital Twin’ to help reverse and prevent chronic metabolic diseases, improve energy and physical health, and extend lifespan.
The emerging situation has been a catalyst toward digital transformation and demonstrates the value of remote monitoring technologies and telecommunications . Remote monitoring can help in patient empowerment and patient engagement, which is the key to survival with COVID-19  and can be achieved via rapidly advancing information and communication technologies. Recently, digital twins have been adapted as precision simulation technology . In the form of healthcare digital twins, smart devices and sensors can offer a wide range of new services and related business models to enable automation in the healthcare sector. There are various challenges for the Digital Twin Based healthcare solutions including quality of data for the analysis owing to limited adoption and privacy of data.
So, in the future the impact of DT in the healthcare can be seen in the following fields: personalized and precision medicine , “to build biologically detailed digital reconstructions” of a brain or a heart , and particular models for specific conditions such as brain aneurysms , simulation models for operations and other interventions by using the ‘-omics’: “genomics, biomass, proteomics, or metabolomics, as well as physical markers, demographic, and lifestyle data over time of an individual” , drug discovery through in silico (‘organ-on-a-chip’s) clinical trials .
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