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Digital Twins; A Way For Precise Medicine


The landscape of medical treatment has undergone a transformative shift
in recent years. The focus has transitioned from broad and generalized
diagnoses to more refined, personalized services. The vision of predictive,
preventive, personalized, and participatory medicine, once championed by
a select few pioneers, has now gained widespread acceptance. The
technologies aligned with this paradigm have proliferated. Within this
framework, a specific technology stands out for its ability to simulate
scenarios prior to real-world application, thereby mitigating risks to patients.
This article will delve into the concept, applications, and limitations of
Digital Twins technology, and then venture into the intriguing realm of
Human Digital Twins.


Medical advancement has brought forth virtual representations of human
hearts, meticulously customized to mirror individual characteristics. These
simulations empower physicians to comprehend disease progression and
assess responses to novel drugs, therapies, or surgical interventions. Back
in 2014, the “Living Heart Project” was initiated as an open-source
endeavor, uniting researchers, surgeons, medical device manufacturers,
and pharmaceutical companies. Their collective goal was to faithfully model
a real human heart, enabling participants to explore paradigms such as the
insertion, positioning, and efficacy of pacemaker leads and cardiovascular
devices. This endeavor brought the Living Heart Project closer to furnishing
tailored and interventional care for cardiac patients.
In 2019, researchers at Sweden’s Linköping University embarked on a
groundbreaking journey, mapping the RNA of mice to create digital twins.
This innovative mapping unveiled the gene activity of thousands of cells
within diseased mice, enabling predictions about the effects of diverse
drugs and dosages. Ultimately, this endeavor aspires to personalize the
diagnosis and treatment of human ailments through RNA analysis.
Smartphone applications equipped with artificial intelligence have emerged
to assist users in assessing potential medical conditions with ease. Notably,
some applications like Babylon Health in the UK leverage digital twins to
enhance their relevance. These twins not only rely on user-provided data
but also incorporate patient health records and information generated by
wearable devices.
Despite being termed “digital twins,” Human Digital Twins represent a
significant leap forward from their non-human counterparts. Developing
such a tool presents formidable challenges, particularly given the current
limitations in computing capacity and accessibility. Nonetheless, the rapid
strides in informatics science—both in terms of performance and
affordability—alongside the growth of big data storage and AI
advancements, are paving the way for future Human Digital Twins.
Enabling the creation of comprehensive digital twins will provide
researchers with unprecedented insights into the intricacies of human
beings. It’s for these reasons that Human Digital Twins stand as a
promising and imminent technological frontier.

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