Project description
Heart models to predict response to treatment
Heart failure (HF) and atrial fibrillation (AF) often emerge together in patients. Most patients receive heart rate control treatment as they tend to respond well, but decision mainly relies on empirical data observed once the therapy has been delivered. To identify patients that perform better following sinus rhythm control treatment, the EU-funded PREDICT-HF project proposes to develop patient-specific biophysical cardiac models that simulate HF–AF. Scientists will use these models to determine which condition (HF or AF) preceded the other and combined with patient history advise on optimal therapy selection for individual patients.
Objective
Heart failure (HF) and atrial fibrillation (AF) are common co-morbidities (AF-HF). AF-HF is prevalent in Europe with high rates of hospitalisation and death. AF-HF patients have two treatment options: rate control, where AF is not treated but drugs are used to slow the heart rate, or rhythm control, where AF is treated to restore sinus rhythm. Rate control is the first-line treatment, yet specific patient groups do much better under rhythm control. Identifying patients that will do best under rhythm control remains a significant clinical challenge.
Potential responders to rhythm control can be identified by their disease history, however, this is often unknown, or their response to treatment, which can only be observed once the therapy has been delivered. We propose to address these challenges by developing patient specific biophysical cardiac models to infer patient history and predict patient response to treatment to inform optimal therapy selection for individual patients.
A model for simulating AF-HF in human hearts, representing all four cardiac chambers, will be created. Bayesian uncertainty quantification techniques will be used to combine physical laws, physiology, population data and measurements from individual patients into cardiac models that account for data uncertainty in model parameters and simulation predictions.
Patient specific cardiac models will be used to answer three critical clinical questions in prospective studies. Models will be used to predict: if AF led to HF, or HF led to AF in AF-HF patients where the index disease is unknown, response to rhythm control therapy in AF-HF patients and in which AF-HF patient’s rate or rhythm control is best.
This proposal outlines an ambitious high risk/return program to address key technical challenges in bringing predictive patient specific models into clinical studies and will apply these innovative techniques to address important clinical questions on the treatment of patients suffering AF-HF.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-COG - Consolidator Grant
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2019-COG
See all projects funded under this callHost institution
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
SW7 2AZ London
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.