Twins for Everyone!
I have lived my entire life as a twin, and, while it isn’t an unalloyed blessing, on balance I’d recommend it. Most of you, though, probably aren’t twins and have missed the experience. Don’t worry: you may still get a chance — with a digital twin.
It could have profound implications for your health and for healthcare generally.
A digital twin, in case you are not familiar with the concept, is a virtual representation of a physical object. It is created from data about that physical object, and is fed ongoing data (e.g., via IoT) about it to keep the model accurate.
The concept is not new, often attributed to Michael Grieves at the Florida Institute of Technology in 2002. Dr. Grieves saw the value of the concept for manufacturing; for example, GE’s Aircraft Engines has been using them to make their engines safer and more efficient. Other applications include building maintenance, data centers, and even creating a digital twin of the whole planet.
People have seen the potential of digital twins for healthcare for years. Back in 2016, GE’s Digital CEO Bill Ruh predicted:
I believe we will have a digital twin at birth, and it will take data off of the sensors everybody is running, and that digital twin will predict things for us about disease and cancer and other things. I believe we will end up with health care being the ultimate digital twin. Without it, I believe we will have data but with no outcome, or value.
We’re not there yet, not nearly, but it’s coming.
Digital twins are, to some extent, still in early days. The Digital Twin Consortium (DTC) was formed in 2020 with a goal “to drive consistency in vocabulary, architecture, security and interoperability of digital twin technology.” Last month it announced “an open-source collaboration community to accelerate the adoption of digital twin-enabling technologies and solutions.”
Dell’s Dr. Said Tabet, a DTC steering committee member, said: “Open-source collaboration will encourage innovation in digital twin solutions. Our Open-Source Collaboration Community will also accelerate the adoption of digital twins and drive business transformation.” Pieter van Schalkwyk, CEO, XMPro, agreed: “Building a library of open-source digital twin resources will help lower the barriers to entry for many companies who want to get started with digital twins.”
But, as Gartner’s Peter Havart-Simkin told VentureBeat: “There is no multi-vendor open standard for a digital twin that can be used by third parties, and there is currently no such thing as an open multi-vendor digital twin integration framework.” VentureBeat translates: “The industry is lacking a digital twin app store where enterprises could buy a digital twin template of an asset that they own.”
Microsoft and IBM — are you paying attention to the “digital twin app store” idea?
We have a ways to go to get there. VentureBeat noted that a survey by the Industrial Internet Consortium identified at least eight industry-wide efforts working on digital twin standards, with the report concluding:
The development of standards for Digital Twin is an imperative for setting the necessary foundation to ensure its successful adoption in the market. However, it is clear that an effort based solely on establishing open standards is not enough. In particular, …the demand for enabling software is increasing. Adequate, widely supported and widely adapted Digital Twin Open Source software can establish de facto standards for the underlying architecture of Digital Twins.
DTC has some work to do.
Meanwhile, a new paper in Nature outlines “a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset,” which sounds pretty dry until senior author Karen Willcox points out that, until now, “missing has been the foundational mathematical framework that would enable digital twins at scale.” The press release promises: “the same mathematical model could be applied in situations as seemingly disparate as the human body, a space rocket or a building.”
And we’re back to healthcare.
In The Hill, Mark Minevich argues that, with digital twins, “If implemented successfully we can say goodbye forever to human clinical trials,” since we “can test all possible vaccines and treatments on digital twins, save lives faster and never test potentially dangerous treatments on humans again.” He also mentions patient monitoring that detect symptoms at an early stage, surgery simulation, diagnosis and treatment, and digital twins for hospital operations.
Similarly, in a recent Forbes article, Sindhu Kutty wonders: “why aren’t more smart hospitals cropping up like smart factories?” Good question.
Another digital twin advocate, Stephen M. Levine, Ph.D., wrote in Fierce Healthcare:
Once it was considered impossible to build a twin of an entire commercial jet under all possible flight conditions. Now it is routine. The human body poses some unique challenges, but these projects demonstrate that if we collectively commit to developing them, virtual twins can deliver the holy grail for medicine; personalized, precise, successful medical treatments — not by themselves, but by providing, in parallel, a living, breathing medical record that combines the latest fundamental knowledge with the patients exact history and unique physiology.
My dream is that our infuriating, siloed, clunky EHRs transition into our digital twins. They’d know us, our health history and what is happening with us in real-time. More importantly, they’d be capable of identifying problems at early stages and modeling future risks/benefits — of lifestyle changes, treatments, procedures, or lack thereof. Let our digital twins take the risks; we’d enjoy the benefits.
Throw in some holograms and we’d really have something new.
It’s not going to be easy. The aforementioned Dr. Willcox also contributed to an opinion piece in Nature Computational Science, along with three other digital twin experts. Lead author Steven Niederer (King’s College London) warned: “We also need to further develop the mathematics of how we create digital twins from patient data, how we measure uncertainty in patient data, and how to account for uncertainty in the model in predictions.”
Another author, Mark Girolami (The Alan Turing Institute), sees the promise of digital twins: “In healthcare for instance, the increasing power of computers and algorithms are enabling technologies to build a patient-specific digital twin, catering to our diversity as human beings and improving individual health outcomes.” He warned, though, that “these promised advances are going to be hard won, requiring further concerted and sustained foundational research and development to fully realise the promise of the digital twin.”
The advances will be hard won, but are worth winning. I’m happy with my current twin, but I can’t wait for my digital twin.
