What We Do

The ISB group operates mainly in the field of systems biology, meaning that we use mathematical models as a tool to analyse biological data and help us derive knowledge from the system. The core idea, from which the systems biology field has risen, is that physiology and biological systems are far too complex to be understood on a detailed level. In contrast to classical biology, where you isolate one specific part and try to understand everything about that part (it could be a cell type, or even a specific protein) ignoring all cross-talk outside your zoomed-in view, systems biology tries to zoom out instead. Acknowledging that the cross-talk is as important, as detailed knowledge of a part, to understand the overall function of a system, systems biology aims to identify key processes in a system that can explain most of the overall functionality. With the idea that once a structure can describe the overall system, we zoom in to add relevant (for the overall system) interactions and functions of specific parts and thus, we will derive the processes and interactions that can explain all of a system's behaviour.

In practice, there are two key components: experimental data and a mechanistic hypothesis. In contrast to black-box modelling, we strive for our mathematical models to be explainable and expand upon our biological knowledge. Therefore, the mechanistic hypothesis is of importance, to base the development of model identified biological processes. The experimental data's role is to validate mechanistic hypotheses and can be of different formats, but time series is typically used. To end up with a robust model more data is always better. In figure 1 down below, we can see a schematic overview of the iterative process of developing a model. The starting mechanistic explanation and experimental data are inputs to the process. As a first step, a model is developed to describe the behaviour in the data. If an explanation is unable to describe the data, this hypothesis is rejected and the mechanistic explanation needs to be revisited and reformulated. This loop continues until one or more mechanistic explanations can describe the data, and then we proceed to the core prediction analysis. Here, the value of big data comes to show, as we want to test our model against new data (validation data) that is unseen to the model. The idea is that if the model formulation is close to the true system, then the model hypothesis should be able to explain unseen data from different experiments (on the same system). Here, again, the hypothesis can be rejected as data might not be described and the iterative process continues. Once a model formulation passes this validation data, this is a core prediction. However, new data and hypotheses can always be added to further develop the model formulation, to come closer to a model formulation that can describe the true system.



The ISB modelling has it's root in ordinary differential equations (ODE's), but have expanded to new techniques over the years. Although ODE's remain has a core fundation for the group, new methods such as hybrid modelling, and MFA are being used. You can read more about our methods in our method's section. As good models come from great experimental data and biological knowledge, we strive to collaborate with others resulting in a vast international network. From our work and succes we are a growing group with have a lot of different on going projects. You can find a vast vararity of projects and modelling work, including the metabolism, the adipocytes, the brain, biomechanical modelling, and much more. If you just have found out about us and are intressed in our work, please feel free to contact us via mailus@isb.com or check out contact us.

From our work throughout the years, since our start in the 2000s, we have created a vast mechanistic knowledge of the different organs and systems in the body and are now working on our flagship, the digital twin. Using our collective knowledge we want to assemble a digital copy of yourself, to be used as a digital copy for health assessments and motivation. Curious about how your body would respond to a lifestyle change? Test it with your digital twin. Want to test how your meals impact your metabolism or how medicine would work on you? Test it with your twin. The digital twin can become a powerful tool for well-directed medical care but is also useful for a motivation boost to follow your plans and help you navigate the medical landscape to good health.