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09 July 2021

Tech Perspective #30: Digital Twins and the Future of Personalised Medicine

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When it comes to medicine, the expression “you’re not like the others” takes on new meaning. Our bodies and organisms differ. Each of us is unique in so many different ways that most of the current methods of treatment, designed for the average patient, are inefficient or not efficient enough for the actual patients.

With so many different variables distinguishing us from one another, it’s near to impossible to design a treatment or procedure that works for everybody. The same applies to medication.

The natural question that follows is: isn’t there a method to turn around the treatment process to focus on the actual patient? Well, of course, that will be personalized medicine.

However, easier said than done. How to introduce personalised medicine on a larger scale?

General Equals Ineffective

Do you know what’s the percentage of patients with Alzheimer’s whom the medication doesn’t work on? Or those with arthritis or cardiac arrhythmia? Get ready, as the numbers may blow your mind. According to the US Food and Drug Administration (FDA) 70%, 50%, and 40% respectively.

Quite shocking, isn’t it? As I mentioned before, the main reason for this ineffectiveness is the genetic makeup of every individual. It is so unique that therapies for the “average patient”, in some cases, may not work at all. Ultimately, patients with the same diagnosis will react differently to the same therapy.

As for now, there’s no way to produce medication that works for everybody and design general procedures that will guarantee successful surgeries. Our organisms surprise us in the most unpredictable ways. Without the ability to predict exact reactions of one’s body to medication or medical procedures, doctors are often forced to run around in the fog, hoping for the best possible result.

However, with the development of cutting-edge technology, it may soon change. Let’s explore the concept of digital twins.

Revolutionary Digital Twins

A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object or process that can be analysed independently of its real-world counterpart to make informed decisions.

Now imagine applying this concept to medicine. It would allow us to create a virtual representation of the human body and its organs where the effects of drugs and reactions to procedures can be studied. It would allow doctors to easily choose the optimal treatment and medical procedures. On top of that, they could also monitor the virtual body and alert before any medical issues arise to prepare preventive measures for the real person.

As Benjamin Meder, a cardiologist at Heidelberg University Hospital, summarises, “We would be able to predict weeks or months in advance which patients will get ill, how a particular patient will react to a certain therapy, which patients will benefit the most. That could revolutionize medicine.”

Even though we’re still far away from creating a digital twin of the whole body, several companies succeeded in creating digital twin models of human organs. One of the examples is the digital heart twin developed by Siemens Healthineers, based on patients’ data with the same parameters of the given patient (size, ejection fraction, muscle contraction).

Era of Personalised Healthcare

As for now, the concept of digital twins is still evolving, with only organ twins demonstrated. Even though organizations like the Swedish Digital Twin Consortium push for the idea, we are still far from a completely digitised version of ourselves.

However, the ability to model digital organs gives us hope for future improvements and the rise of personalised healthcare.

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Author
Marcin Bartoszuk
Chief Operating Officer

With Microsoft technologies related since 2005. He graduated from the Computer Science Faculty of the Bialystok University of Technology where he was the leader of the .NET Group and the Microsoft Student Partner. Four times finalist of the national stage of the Imagine Cup competition, and later the mentor and the jury member of the contest. Co-founder of the Bialystok .NET Group. He lectured .NET development at the Bialystok University of Technology. Microsoft MVP in the Client Application Development category in 2008-2010, when he actively participated in the IT community. Constant new technology enthusiast and IT consultant.