Rohit Puri, Group SVP, BPO, NTT DATA Services highlights that from simulating the cellular, and even the sub-cellular functions, to creating a replica of the human body or an entire organ system, digital twins in the healthcare sector are used for a wide range of operations of varying degrees of complexity
Over the years, advancements in the ‘Digital Twin’ technology have brought ideas hitherto in the realm of the impossible closer to realisation: For instance, advancements are taking the healthcare sector close to replicating the functions of a human body. Venki Ramakrishnan, the Nobel Prize-winning biologist, observed that, over the past two decades, medicine and biology have reaped the benefits of the gigantic strides made in the field of technology and computing, and the ‘Digital Twin’ is one technology finding increased application in the healthcare sector.
What is a ‘Digital Twin’?
A digital twin is a virtual replica of any physical entity – it could be an object, a process, or a service unit. However, it is its dynamic nature, coupled with some of its unique features that go beyond conventional simulation models, that sets the digital twin apart. The digital replica can be dynamically and bi-directionally linked with the physical world to build, test and improvise a real-world entity until optimised for expected performances.
First used in manufacturing for product management and testing, the digital twin is now finding application across sectors. Its distinctive features have enabled integration with several other advanced technologies such as Artificial Intelligence (AI), digital analytics’ tools, and smart sensors.
The many ‘wearable’ healthcare gadgets, which monitor vital functions of the human body in real-time, hint at how computing technology can be used to effectively tackle various disorders. Meanwhile, experts are exploring the capabilities of the digital twin to assess the feasibility of creating dynamic human models to increase overall life expectancy.
Many types of twins
From simulating the cellular, and even the sub-cellular functions, to creating a replica of the human body or an entire organ system, digital twins in the healthcare sector are used for a wide range of operations of varying degrees of complexity. Digital twins can be efficiently used to build a virtual model of a diseased organ, or assist experts in studying interactions between the body, and micro-organisms.
In fact, the digital twin can also be used to construct the virtual replica of the healthcare institution itself, to facilitate planning, and implementation of efficient management practices.
Digitising diagnostic processes
Improvements, and augmentations to ‘digital twin’ models can, meanwhile, greatly broaden the scope of its functionality, while offering experts a more comprehensive picture of the problem requiring treatment. To that end, models such as digital instances, digital aggregates, and digital threads can enable accurate simulation of the real-time behaviour of the human body.
- Digital instances are identical copies of the digital twin, which can be employed for a comparative analysis of responses to various treatment procedures.
- Digital aggregates refer to a collection of digital twin instances, clubbed together to create a group with similar traits. For instance, digital aggregates can be created for the members of a family, or for special population groups.
- Digital thread provides the data cycle of a digital twin along a timeline thereby enabling experts to observe any trends or patterns.
The technology-driven revolution in the healthcare sector is progressing simultaneously on multiple planes. While Internet of Things devices such as environmental sensors, remote health monitoring systems, have transformed many procedures, use of big data tools, cloud computing technologies, has enabled real-time processing of voluminous data sets, analysis of which has led to novel discoveries. Integration of the digital twin into this technological setup can enable the creation of a highly sophisticated quality healthcare system.
A guiding light in medical research
Among the reasons the healthcare sector is enthused about the promising capabilities of the digital twin is that it is seen as a more efficient, inexpensive, and less labour-intensive alternative to the in-silico simulation model. The limitations of the in-silico simulations were brought to the fore during the pandemic. The in-silico simulations could only be used for structural analyses, and did not boast the dynamic capabilities that could have enabled study of real-time responses.
As of now, experts have been successful in using the digital twin to build artificial pancreas to construct digital treatment models for diabetic patients. The integration of this virtual technology in a clinical set-up hinges on ensuring a successful collaborative network of electronic devices, culminating in the creation of a fully-automated and portable digital treatment ecosystem for diabetic patients.
A virtual assistant for clinical procedures
The digital twin, albeit in a fragmented avatar, is already being used in clinical procedures. For instance, cardiologists are using patient-specific digital twin models, studying them alongside MRI reports, clinical records, demographic studies, and running simulations to help forecast possible strategies for long-term management of cardiac disorders. Approved medical devices such as Heartflow FRCT Analysis, and CardioInsight, for instance, use customised computation models to help doctors come up with the best diagnostic response to problems. HeartFlow, for example, uses a three-dimensional model of the coronary arteries to predict blood flow. Such innovations are providing doctors with crucial nuggets of diagnostic data, enabling them to study biomarkers that would otherwise be very hard to measure.
Meanwhile, the pharmaceutical sector is increasingly leaning on digital twin technology for a variety of applications. In fact, the sector is leveraging the technology’s capabilities to make breakthroughs in development and discovery of new drugs. The digital twin of an organ, say a liver, can, for example, enable pharmaceutical companies to simulate the perceptions of drug-induced injuries.
Ensuring preparedness during healthcare crises
Beyond operation theatres, and consulting chambers, the digital twin can also be put to use for administrative functions in the healthcare sector. From tracking the outbreak of any disease, to surveillance, and ensuring adequate preparedness for a future outbreak, the digital twin technology can help increase the efficacy of the response to situations such as the pandemic. Cloud computing systems, along with AI tools, integrated with the patient database, can render tasks such as identification and tracing, of infected individuals, their close contacts much easier.
Healthcare administrators can ensure optimal utilisation of the entire scope of the digital twin technology by employing it in conjunction with ‘Smart City’ infrastructure. In such a system, a patient’s smartphone, in itself, serves as a digital twin, providing real-time updates on the individual’s condition.
Challenges, and future scope
The sheer complexity of connections, and the intricacies of the neural, and cardiovascular networks, render the construction of a digital model of the entire human body incredibly difficult. Although there is no gainsaying the advantages that the healthcare sector has accrued following the advent of the digital twin, the technology is not without its attendant challenges. Its use has triggered questions on the ethics of using AI and big data, turning the focus on the stakeholders to ensure stringent enforcement of data privacy norms to protect individual data rights,
Clear visualisation and accessibility to data, coupled with the necessity to integrate it into existing clinical workflow procedures, is one of the challenges in ensuring safe and efficient use of the digital twin technology is. However, attempts are under way to standardise methods and protocol for interoperability, and integration in medical applications.
Although developing a virtual model of the human body remains a far-fetched proposition, the potential of the digital twin to revolutionise management of electronic healthcare records is beyond question. A patient-specific digital twin can enable doctors to pursue a more comprehensive course of treatment, by combining their knowledge of the human physiology, with the real-time clinical data for running predictive simulations of infections, and other disorders. The digital twin technology will doubtless play an instrumental role in enabling breakthroughs, by easing the process of testing hypotheses, and running comparative models.
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