Tuesday, September 27, 2022
Published 6 Months Ago on Friday, Mar 25 2022 By Ahmad El Hajj
If you are old enough to have watched the series “Bones,” then for sure you have bumped into the “Angelator,” a holographic projector developed for forensics. Based on data and evidence collected from the crime scene, a reconstruction is achieved, allowing inspectors to visualize a 3D representation of the victim or weapons used and study different hypotheses related to the incident itself.
This fictitious device created for TV purposes several years ago is an incontestable premise to appreciate the realistic and future impersonation of the idea, namely, digital twins. The talks about the digital twins’ concept go as far as early 1990 with the publication of Mirror Worlds by David Gelernter. However, a clearer view of the concept was described by Grieves in 2002 and Vickers from NASA in 2010.
Although the idea was clear at that time, the practical realization of a digital twin was not possible as the associated technology was not mature enough. Looking at IBM’s definition of a digital twin, that is, “A digital twin is a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning, and reasoning to help decision-making.”, one can clearly sense that the right time is now to start investing in this technology.
Digital twins technology is at the crossroads of advanced telecom standards, powerful computing resources, and accurate artificial intelligence algorithms. The advent of the 5G wireless standard and, more importantly, the prospects of the following 6G standard would allow the achievement of the appropriate latencies and data rate for a real-time operation of the twin. The increasing investment in cloud and edge computing resources will provide the power to gather and analyze significant amounts of collected data. Finally, the constant improvement of AI algorithms will further lead to better decision-making. And the conditions will only get better for digital twin solutions as the development efforts are relentless on all fronts.
Digital twins are disruptive at all fronts. Among others is its high contribution to the fourth industrial revolution, known as industry 4.0. It offers to migrate the agile development methodology from the software industry to a myriad of other applications. The ability to crunch huge amounts of data collected from sensors interpret them will allow manufacturers to validate their concepts, integrate components together, optimize the production process without the need to resort to the costly traditional approach of manufacturing prototypes and conducting rigorous testing. It also allows complex management of systems and dramatically simplifies troubleshooting tasks.
Healthcare is considered among the sectors which would be significantly affected by the inception of digital twins solutions, given its increasing reliance on advanced technology. The use cases of digital twins in healthcare are numerous, spanning logistics, operations, supply chain management, medical diagnostics, and therapeutics, among others. The latest coronavirus pandemic is one striking example that justifies twinning solutions. With the surge in the number of hospitalized people, the hospital ecosystem was placed under immense stress, nearly becoming non-functional with a shortage in protection equipment, ventilators, and, most importantly, emergency room beds.
A digital twin solution would have allowed to proactively optimize the response to the pandemic through tweaks made to the digital twin, given all the patient and hospital data collected. Compared to traditional simulations, the new solution allows the visualization of the resolution, rather than just obtaining numbers that eventually need to be used. Visualizing the future certainly passes by a proper visualization of the present, which is the heart of the twinning solution.
Another use case relates to medical diagnostics. The sci-fi concept introduced in “Bones” will soon become a reality. Imagine a doctor having a visual update of a patient heart condition. The data collected from different sources such as heart rate, oxygen levels, electrocardiograms, and potentially medical imaging, will be useful in updating the patient’s virtual twin.
The advanced computing and learning capabilities will even allow the caregiver to trial various drugs and therapeutic techniques, observing their impact, before administering them to the patient. Genomic medicine and mRNA-based treatments (such as some COVID-19 vaccines) can be developed better and easier to ensure a faster and more tailored response to illnesses and diseases.
The adoption of this digital twin in the healthcare sector hasn’t picked up yet properly due to many challenges. “Technology literacy” is one issue that needs to be addressed to increase the adoption rate, as Healthcare providers and caregivers need to be comfortable with the new technology to embrace the foreseen health revolution. Another major issue relates to data integrity and privacy.
Biomedical data is considered among the essential sources of information as they nearly permit the reconstruction of a person’s profile. Thus, ensuring that the data used to construct the digital twins is unaltered (integrity) and will not leak out (privacy) will ensure that more institutions are willing to invest in the technology after proper guarantees that ethical principles are respected.
Finally, the data itself should be detailed enough to ensure that the twin properly represents the patient and that all analyses and decisions made are accurate. While other industries are not as sensitive to these issues, health provision highly depends on it.
As in any new technology, early adopters of digital twins are mainly startups, each trying to commercialize its own use of this innovation. The German company Virtonomy aims at shortening the time-to-market of medical products. They rely on digital twins to study the anatomical constraints and design medical implants accordingly. Another company, namely, unlearn.ai, has implemented several twinning solutions to reduce the number of trials, offloading some of the developed twins. Another goal is to forecast the progress in patients who have Alzheimer’s disease.
The French startup Nurea is employing digital twins to prevent cardiovascular accidents. The US startup Predictiv uses collected DNA samples to build your digital twin, then performs the analysis to predict genetic disorders. Another US startup in the name of Q-bio takes twinning to another level, utilizing their whole body Q Bio Mark I scanner to develop a digital twin for the whole body. Finally, the British company Babylon Health allows users to explore their bodies learn about possible risks and how to improve their health.
The aforementioned examples are only some among many startups flourishing worldwide and aiming to be at the forefront of the new healthcare revolution driven by digital twins. As the adoption of this solution increases among healthcare providers, it will become an integral part of our life.
The development of wireless technologies will undoubtedly have a human-centric flavor, with several key performance indicators and use cases developed based on human-centric applications such as healthcare provision. The next few years will most certainly witness the rise of digital healthcare. The coronavirus pandemic has convinced a large group of people that the healthcare system as it stands is very brittle and that waves of change need to come as fast as possible. Digital twins are probably the first tidal wave that will lead to the metamorphosis of the healthcare sector.
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