The first question that comes to mind is What is Digital Twin? and How is it related to Data Science and Medicines that we are studying here.
Don't worry we are going to start our post from this point only.
What is Digital Twin?
As the name suggests, Digital Twin is something related to Twin or a copy of something with a digital presence, or Virtual Presence. So, now the question is What is this "something" of which we create a copy?
This "Something" can be anything process, plant, factory, human, machine etc. which is not well defined and might require multiple rounds of mix and match setups to get to the desired/maximum efficiency. These repeated steps not only take a lot of time but also a huge amount of money is also involved in the whole process. Also, there is an uncertainty that the process would succeed or not and how much more time will be required to get the final version.
Let's take a small example to understand the whole concept of the Digital Twin technology easily.
We all might have seen the movie Avengers: Age of Ultron where Iron Man aka Robert Downey Jr. was trying to create some sort of interface for Artificial Intelligence to create Ultron, for which he and Dr Banner had to run many rounds of simulations but they failed many times, until and unless Jarvis was able to create a perfect interface after running N no. of simulations.
That's what we can typically call a Digital twin, where they first created a digital/artificial environment and then tried to build an interface, with which they had no prior experience. This process not only took a lot of time but also money. Now imagine if they would have not created such a twin then it might have taken years for them to run that many simulations to get the final perfect one.
Official Defination of DIgital Twin is:-
A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object or process.
Hope that makes the concept a bit clearer, about What is Digital Twin and How it is useful.
Digital Twin & Medical
Diseases might seem to be common but often most of these are not caused by a single "fault" rather it mostly depends on the timing of infections entering the body, duration, body's immune system, affected genes, further infections and many more factors. In most of the cases, doctors preferred similar treatment but most of them were not very satisfied as further some other drugs were required in most of the cases.
This led the doctors to come up with the idea to create a Digital Twin of a human infected with hay fever which they can use for finding or creating new drugs/medicines which could be used for providing specifically tailored medicine at the right time to the patients.
To construct the digital twin, researchers used all the data available by analysing the network. The network could be thought of as a pass made by the hockey players during the game, wherein each player passes the ball to other teammates to score the goal. Here the player with the most number of passes is considered the most important player. A similar concept was used to construct the digital twin to identify the most important proteins.
This helped the researchers to find that multiple proteins and various signalling were important in a particular type of infection and also helped them to analyse the effect of medicines at various points of time during infection, which helped them to get the right medicine to the person at the right time. Thus, helping to cure the disease more effectively.
Data Science & Digital Twin
Another question that might be quizzing us till now is the "relation between Digital Twin & Data Science". Don't worry we are going to answer it now.
Digital Twin is something which has no physical presence rather it's just a digital representation of the process, machine etc. that we want to create. So, to make the computer understand what we want from the twin, we need to provide the computer with the historical performance data of the machine so that the computer can recognize the behaviour of the machine and be able to predict its future behaviour based on it.
Thus, a huge amount of data is required to create a digital twin model, to make it more precise and able to predict the future outcomes more accurately. Whenever there is such a huge amount of data involved, Data Science is required to clean, process, visualize and model it.
Summary
A new field in the form of Digital Twin is emerging fast and at a steady pace. It is growing in all the fields and lately, it has found its application in the medical field also which will be surely going to help the researchers and doctors to find better medications.
Let's wait and watch what miracles this new Digital Twin technology shows us and what fields it finds its application in and by what level it can improve the tech.
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