Periodic Reporting for period 1 - SimCardioTest (Simulation of Cardiac Devices & Drugs for in-silico Testing and Certification)
Período documentado: 2021-01-01 hasta 2022-06-30
Cardiovascular disease (CVD) is the leading cause of death worldwide. Almost 50 million people in Europe live with CVD, among which 15 million patients suffer from heart failure, whose prevalence continue to rise. Beyond its associated risk of sudden death, heart failure, has not only a significant and lasting impact on the health and well-being of patients, but has also become a societal and economic burden. In particular, despite the current huge investments in healthcare, the number of newly approved and more effective drugs has not increased. The search for new drugs and devices is particularly challenging due to the significant R&D costs and the complexity of regulatory procedures; thus, hampering the commercialisation of new solutions and putting many patients at risk of not receiving timely and adequate therapy. Additionally, the dramatically increasing attrition rate across all phases of drug and device development pipeline highlights the lack of reliability of both existing preclinical animal models and the current design strategies for clinical trials, urging the need for new predictive tools.
An innovative and non-invasive solution to these critical problems is offered by computer modelling and personalised simulations, which have the capacity to create scientific evidence based on controlled investigations, including satisfying demands for safety, efficacy & improved access. Cardiac simulations have previously demonstrated great potential in generating clinically relevant predictions of heart function in certain pathologic conditions, providing the clinicians with powerful insights for more accurate diagnosis, an improved personalized therapy planning, and a better outcome (i.e. higher success in response to therapy).
SimCardioTest takes the mature field of cardiac simulations and brings it further through a web-based platform to perform standardised in-silico trials for testing the efficacy and safety of drugs and devices in 3 concrete use cases.
The main objective of SimCardioTest is to create a unique, digitised, personalised testing environment for cardiac devices and drugs.
An innovative and non-invasive solution to these critical problems is offered by computer modelling and personalised simulations, which have the capacity to create scientific evidence based on controlled investigations, including satisfying demands for safety, efficacy & improved access. Cardiac simulations have previously demonstrated great potential in generating clinically relevant predictions of heart function in certain pathologic conditions, providing the clinicians with powerful insights for more accurate diagnosis, an improved personalized therapy planning, and a better outcome (i.e. higher success in response to therapy).
SimCardioTest takes the mature field of cardiac simulations and brings it further through a web-based platform to perform standardised in-silico trials for testing the efficacy and safety of drugs and devices in 3 concrete use cases.
The main objective of SimCardioTest is to create a unique, digitised, personalised testing environment for cardiac devices and drugs.
THE REPRESENTATIVE USE CASES
The main goal of USE CASE 1 is to quantify mechanical and electrical properties of cardiac stimulation devices (i.e. pacing devices and leads), using computer modelling and simulations. In particular, the UC1 focuses on bradycardia leads and aims at designing a numerical workflow that can be later extended to other implantable devices. To date, two distinct computational pipelines have been built by our teams: one aims to address several critical questions on the electrical pacing and sensing performances of the lead, while the other investigates the navigation possibilities of the lead, as well as long-term mechanical fatigue. Ongoing efforts are focusing on investigating the behaviour of the pacing/stimulation lead, which has been explicitly modelled to estimate key metrics (such as the strain/stress quantities), whereas the anatomy (i.e. geometry of lead, tissue and surrounding structures of interest) was approximated by a simple compliant behaviour.
The main goal of USE CASE 2 is to generate in-silico personalised hemodynamic indices of left atrial geometries, complementing their morphological analysis. Furthermore, this case aims: to identify the risk of thrombus formation in atrial fibrillation patients; to improve patient selection for the implantation of left atrial appendage occluders (LAAO); and, to optimise their settings (e.g. size, positioning). To date, a computational modelling pipeline has already been designed and is able at-present to generate patient-specific meshes and patient-specific boundary conditions in a large number of cases. In addition, extensive sensitivity analyses and model calibrations are also being currently tested in order to determine the optimal methodological choices for simulations pertaining computational fluid dynamics prior to, during and after LAAO implantation. Ongoing in-silico tests also concern detailed verification and validation (V&V) investigations which will enable us to assess the credibility of these developed models, as well as distinct aspects relevant to the clinical translation in silico LAAO studies to realistically predict the risk of stroke in relation to the device implantation.
The main goal of USE CASE 3 is to assess efficacy and safety of drugs in populations of electrophysiological and electromechanical models. A specific pipeline has been defined for this purpose, with the ultimate goal of integrating it in a cloud-based platform to implement in silico trials of efficacy and safety. To date, several stages in the pipeline are considered, starting with the construction of pharmacokinetic models for selected drugs. These models can provide the user with the precise drugs concentration that is needed to be considered in the next second and third stage of the pipeline (i.e. models at molecular/cellular levels, as well as 3D electrophysiological and electromechanical models at organ/body levels). An important and realistic aspect of our population of models is that gender, age and pathology is properly considered. Moreover, the credibility of the models used through the pipeline is presently assessed by following a detailed verification and validation process, including sensitivity analyses and uncertainty quantification. Importantly, a crucial step in the assessment of efficacy and safety of drugs is the definition of biomarkers derived from our simulations, which will help in building accurate classifications tools and next generation models.
The main goal of USE CASE 1 is to quantify mechanical and electrical properties of cardiac stimulation devices (i.e. pacing devices and leads), using computer modelling and simulations. In particular, the UC1 focuses on bradycardia leads and aims at designing a numerical workflow that can be later extended to other implantable devices. To date, two distinct computational pipelines have been built by our teams: one aims to address several critical questions on the electrical pacing and sensing performances of the lead, while the other investigates the navigation possibilities of the lead, as well as long-term mechanical fatigue. Ongoing efforts are focusing on investigating the behaviour of the pacing/stimulation lead, which has been explicitly modelled to estimate key metrics (such as the strain/stress quantities), whereas the anatomy (i.e. geometry of lead, tissue and surrounding structures of interest) was approximated by a simple compliant behaviour.
The main goal of USE CASE 2 is to generate in-silico personalised hemodynamic indices of left atrial geometries, complementing their morphological analysis. Furthermore, this case aims: to identify the risk of thrombus formation in atrial fibrillation patients; to improve patient selection for the implantation of left atrial appendage occluders (LAAO); and, to optimise their settings (e.g. size, positioning). To date, a computational modelling pipeline has already been designed and is able at-present to generate patient-specific meshes and patient-specific boundary conditions in a large number of cases. In addition, extensive sensitivity analyses and model calibrations are also being currently tested in order to determine the optimal methodological choices for simulations pertaining computational fluid dynamics prior to, during and after LAAO implantation. Ongoing in-silico tests also concern detailed verification and validation (V&V) investigations which will enable us to assess the credibility of these developed models, as well as distinct aspects relevant to the clinical translation in silico LAAO studies to realistically predict the risk of stroke in relation to the device implantation.
The main goal of USE CASE 3 is to assess efficacy and safety of drugs in populations of electrophysiological and electromechanical models. A specific pipeline has been defined for this purpose, with the ultimate goal of integrating it in a cloud-based platform to implement in silico trials of efficacy and safety. To date, several stages in the pipeline are considered, starting with the construction of pharmacokinetic models for selected drugs. These models can provide the user with the precise drugs concentration that is needed to be considered in the next second and third stage of the pipeline (i.e. models at molecular/cellular levels, as well as 3D electrophysiological and electromechanical models at organ/body levels). An important and realistic aspect of our population of models is that gender, age and pathology is properly considered. Moreover, the credibility of the models used through the pipeline is presently assessed by following a detailed verification and validation process, including sensitivity analyses and uncertainty quantification. Importantly, a crucial step in the assessment of efficacy and safety of drugs is the definition of biomarkers derived from our simulations, which will help in building accurate classifications tools and next generation models.
SimCardioTest is challenging today’s huge burden of cardiovascular diseases on the population worldwide, through advanced in-silico testing approaches which are non-invasive and can provide superior technological solutions. Overall, this project has the exceptional potential to transform the existing system of clinical trials, while reducing their costs and accelerating the availability of medical drugs/devices.
SimCardioTest will demonstrate that such approach can help develop better devices and more effective drugs, as well as to reduce the cost and time to market, while gaining the trust of scientists, companies, regulatory bodies, physicians and patients. Last but not least, another important objective is to impact the whole design of clinical trials by replacing several invasive aspects of the current trials, and possibly provide novel biomarkers for more accurate diagnostic methods or more effective personalized therapies.
Among other benefits, this testing platform shall demonstrate the possibility to perform experiments in controlled conditions and populations, repeat experiments as often as needed, and test effective treatments that are tailored for patient-specific pathologies.
SimCardioTest will demonstrate that such approach can help develop better devices and more effective drugs, as well as to reduce the cost and time to market, while gaining the trust of scientists, companies, regulatory bodies, physicians and patients. Last but not least, another important objective is to impact the whole design of clinical trials by replacing several invasive aspects of the current trials, and possibly provide novel biomarkers for more accurate diagnostic methods or more effective personalized therapies.
Among other benefits, this testing platform shall demonstrate the possibility to perform experiments in controlled conditions and populations, repeat experiments as often as needed, and test effective treatments that are tailored for patient-specific pathologies.