3Rs Stimulus Fund: computer models predict risk4 weeks ago
Aurore Lyon is a Postdoctoral Researcher who is using computer simulations of the heart to improve predicting the risk of sudden death in patients. Toon van Veen is an Associate Professor and Vice Chair of the Department of Medical Physiology at the UMC Utrecht. He supervises Aurore’s research. They received a grant from the 3Rs Stimulus Fund.
What is your research about?
Aurore: In our research, we focus on people who have a genetic mutation that can lead to cardiac disease, a cardiomyopathy. This disease affects their heart muscle and can lead to heart failure. Some patients with this mutation die a sudden death, sometimes pretty young. At the moment, we don’t know how to predict which patients are the most at risk of death. To improve this prediction, we need to understand what can lead to this sudden death.
Toon: Ideally, you want to adapt a patient’s treatment to the stage of their disease. For example, by implanting an ICD (Implantable Cardioverter-Defibrillator, ed.), a small device to monitor and regulate problems with the electrical signals in the heart (arrhythmias). Currently, it is difficult to predict which patients need an ICD, and implanting an ICD is a costly procedure.
Aurore: Animal models are used to get a better understanding of the mechanisms of a disease, but the problem is that translating the results to humans is difficult. We proposed a different approach, using computer models. Using computer models, we can simulate the heart function of virtual patients. By varying the different parameters of the model, you can find out how they affect the outcome of the simulation and the risk of arrhythmia or heart failure in the patient.
Toon: In our project funded by the stimulus fund, we combined a model based on cells in a mouse heart with data from an experimental mouse model. That is how we ended up with a computer model that can help us understand what leads to heart disease in a mouse. We are currently using the same experimental data in a computer model based on the human body to find out how we can translate this to humans. We also have clinical data, which was collected by routine monitoring of patients. We are developing a human computer model that can simulate the heart from cell to whole organ. If our simulations match the clinical data that we have, the model works and can help monitor the patients. We can then predict how their disease will progress. Additionally, thanks to the model, a patient’s treatment plan can be adapted more accurately to their individual disease progression.
Why do you use computer models?
Aurore: We think that the case for using a computer model is strong. There are other models available to investigate disease and risk, such as IPS cells (Induced Pluripotent Stem cells, ed.) Like the computer models, IPS cells do not require the use of any animals but they show some limitations.
Toon: IPS cells are induced from skin cells or blood cells of a patient. Molecular techniques are used to derive these cells into heart cells. The drawback is that the level of maturity of these cells is not sufficient. Another important benefit of computer modelling is that it can capture different levels of complexity. In the future, we are going to scale up from single cells to the whole heart. That is impossible with in vitro models.
What are the challenges you face?
Aurore: Scaling up to the whole heart is one of the things that makes the project challenging. Fortunately, we have already come a long way. The particular challenge lies in combining different models with different scales and complexity. We have data from different cell types, animal models, IPS cells and clinical data. A computer model is especially useful because it allows us to combine these data and understand how they relate to each other. There are some other technical challenges.
How does your research fit into the 3Rs?
Aurore: There are two Rs that are especially applicable to our project: reduction and refinement. We can help reduce the number of animal experiments because we provide an alternative platform to test a hypothesis. Additionally, with a computer model we can help translate the results from the animal experiments to human physiology. That fits in with refinement. Our end goal is to improve patient management by predicting the risk of death and improving a patient’s personalised treatment plan.
What has the 3Rs Stimulus Fund made possible for you?
Aurore: It allowed me to conduct this research. The researchers in Toon’s group have a lot of expertise in conducting experiments. It was interesting to see where the data that I’m using in my computer model comes from. The grant also helped me create connections with both experimental and clinical groups. My research in Utrecht was crucial for establishing these collaborations. We presented the results of this work at different conferences and we also published a paper. All of this was made possible by the grant.
Toon: For you, Aurore, I think it also helped specify your own identity in research and the field of computational modelling. There are multiple groups working on computer models in different forms of cardiac disease. The research groups focusing on the specific cardiac disease we are looking into are not that heavily involved in computer modelling so far. For the future of Aurore as a researcher and for the future of our field, this research was very important.
Aurore: We will also apply for future funding, focusing on expanding this research from the cell to the whole heart.
What is your hope for the future?
Aurore: Computer modelling is becoming increasingly important in cardiovascular research. What we have developed is new for this specific cardiomyopathy and can be applied to other cardiac diseases. This research will help us understand the mechanisms in patients and predict their risk. My hope for the long term is that we will be able to better identify patients who are at risk of sudden death and give them individualised treatments.
Toon: Eventually, we hope that patient specific risk management and treatment will improve their quality of life. That is what we want to achieve in the end.