Digital twins. This picture is a photomontage showing two Gunnar Cedersunds. Photo credit Magnus Johansson
“When you want to predict the weather, or send a rocket up in space, you build computer models of the processes and forces that you believe will affect weather changes or the movements of the rocket. We’re doing the same thing, but for processes in the body”, says Gunnar Cedersund, associate professor at the Department of Biomedical Engineering (IMT).
There are lots of processes going on in every one of the body’s organs all the time. Each process can be described using mathematical equations, which can be put together to make an advanced model of how any one organ works. By feeding in somebody’s own data, the general model can be adapted for each specific individual – a digital twin. The researchers’ goal is to make the model predict what will happen when something in the system changes, for example how blood pressure is affected by medicine.
“We’re working on creating apps where everybody can look at their digital twin and use the model to understand how they should act (e.g., with regards to eating or exercising) on a daily basis, or to remind them why they should take their medicine.”
Interface between biology and maths
But first, let's rewind twenty years. At the time, Gunnar Cedersund was studying to be a theoretical physics engineer at LiU. He was fascinated by the theory of relativity and quantum mechanics, and enticed by the study of the boundaries of human knowledge.
“I wanted to understand what we can and can’t know.”
But he began to feel that the most exciting aspects of the field had already been explored to exhaustion years ago. Instead, his eyes were drawn to an area where maths and biology meet.
“What I’m now researching is called chaos theory and complexity theory. I realised that this field was in a phase where our basic understanding of things was being changed at a fundamental level. This really was the thing for me.”
And so it was. During his PhD at the Department of Electrical Engineering (ISY), Gunnar started by looking at techniques for creating advanced mathematical models, and began to adapt them to biological systems. Roughly twenty years later, he and his colleagues have, step for step, built models for different aspects of most of the body’s organs, such as fat and muscles, the liver, brain and blood. They’ve now come far enough to connect the different organ models into a big model for the whole body. There is currently no computer model that can describe a whole living being in complete detail, but the big things like metabolism and the blood flow are beginning to fall into place. With this model as a framework, the researchers can now begin to add new details in a simpler way.- The digital twin consists of models of several organs that are connected to each other and adapted to the individual’s own data. Using the digital twin, researchers can simulate the effects of, for example, different kinds of diet. Photo credit Magnus Johansson
“For example, we can now simulate the effects of different diets with different levels of proteins, carbohydrates and the like. This is possible thanks to us having, for the first time, put a detailed liver metabolism model together with a meal model that also contains data on the metabolism of other organs. Earlier models haven’t been able to describe the transformation from protein to sugars, and have, therefore, not been able to simulate the effects of different diets.”
Gunnar Cedersund believes that, in the long run, it will be possible to use digital twins to help people take care of their own health. His company develops e-health products based on his research. He thinks that the research field of mathematical modelling in biology hasn’t grown much since he started working with it. It has, however, matured.
“I believe that when our digital twins become accessible as a mobile app, in a year or two, people can, for example, take them with them when they go to see a doctor. They can use the data that’s being gathered about us all the time. Maybe you wear a smart watch, have a step counter on your phone, or maybe you even use a blood sugar monitor if you’re diabetic. We work together with actors who have data, data which our model can synthesise into a whole picture.”
Organ on a chip
The models can also be used in pharmaceutical development, something which the research group is exploring together with the pharmaceutical company AstraZeneca. They are using a piece of technology that has become an increasingly common alternative to animal testing. Simply put, the technology involves building tiny “organs” from living cells on a chip: an organ on a chip. Each chip is roughly as large as a USB stick. That way, you can connect several mini organs to each other. Instead of carrying out experiments on animals, the researchers use the chips, which the researchers from LiU have made digital twins of.
“We can test the medicine on the organ on a chip and then analyse the data to understand what the medicine does to the cells. But we can also translate data from these experiments to a model of a person, and look closer at how promising medicine can be used on real people”, says Gunnar Cedersund.
They are using these method with medicine for diabetes and cardiovascular disease, two of the biggest endemic diseases in Sweden.
Everybody can contribute
Gunnar Cedersund and his colleagues want to lay the groundwork for a kind of healthcare artificial intelligence (AI) built on mechanical models of biological processes. This is different from AI in several key ways.Gunnar Cedersund. Photo credit Magnus Johansson
Most current AI is constructed in such a way that people can’t understand what has led to the AI giving the answer it does. It’s like a black box that we can’t see into, and is therefore called “black box AI”. However, with the models from these LiU researchers, it’s possible to see what happens inside the “box”, because the models consist of mathematical descriptions of the biological processes. These models can also help generate completely new, unintended insights, bringing new understanding to us.
“I hope that it will, in the long run, become natural for us to use this technology to understand biology and, indeed, to understand more or less everything. That is to say, that people stop sprouting opinions and partial insights that point in all different directions, and instead come together to understand the links between lots of different data, creating an overall picture. But this isn’t just going to come from researchers’ experiments. It can also come from the experiences of private individuals, who can contribute to generating knowledge as to how the human body works.”
