In Silico Clinical Trials for Cardiovascular Disease
May 27th, 2022
This protocol demonstrates the workflow of the SILICOFCM platform for automatically generating a parametric model of the left ventricle from patient-specific ultrasound images by applying a multi-scale electromechanical model of the heart. This platform enables in silico clinical trials intended to reduce real clinical trials and maximize positive therapeutic outcomes.
Our protocol demonstrates the workflow of the Silico FCM platform of the left ventricle from patient-specific ultrasound images by applying a multiscale electromechanical model of the heart. Silico FCM platform can investigate drug effects that are prescribed through specific boundary conditions for inlet and outlet flow, ECG measurements and calcium function for heart muscle properties. Application of Silico FCM platform can reduce animal experiments and reduce real clinical trials and maximize positive therapeutic outcomes for cardiomyopathy disease.
Silico FCM can be applied also to another cardiovascular disease like heart failure, cardiac ischemia, arrhythmia, atrial fibrillation. Many workflows in the Silico FCM platform can be used by the first time user because they're very helpful guidelines for leading user through the platform. Visual demonstration of the Silico FCM platform is important because many software tools for visualization of the cardiovascular parameters like part for velocity, pressure, sheer stress, wall stress and information.
Begin by logging into the platform with a username and password. Under virtual population module, choose ultrasound M-Mode or apical view workflow. Then from the list of available workflows select the ultrasound merged workflow.
In the file upload section, upload images and dcom files stored locally on the user's computer, and select either private or public folders as the destination folder for the files. Type the desired comment or note in the comment section before starting the workflow. Select the apical view in M-Mode left ventricle ultrasound images and DICOM files.
Click on the execute button. The interactive platform notifies the user when the running workflow is finished. Visualize the created geometry of the left ventricle directly on the platform.
The available options include shaded and wire frame models. for visualization. Select the workflow and download the template files for the boundary conditions of inlet and outlet velocities using the buttons and the bottom section.
If patient-specific flow boundary conditions are available, download and use these files. Save these files into either private or public folders. Upload these files in a similar way as uploading images.
The prescribed inlet and outlet velocities simulate the drug condition while the mesh options control the density of the finite element mesh. For simulating patient-specific conditions modify the default values of pressure, flow, material properties, and calcium function. Click on the execute button.
A new running workflow will appear in the list. If any of the sections of the workflow are not clear, click on the help file button to view detailed instructions on how to use this workflow and interpret the results. Click on the eye button to view the ejection fraction and global work efficiency values and diagrams of pressure versus volume, pressure versus strain and myocardial work versus time.
Click on the camera button to preview and play animations of the displacement, pressure, sheer stresses and velocity fields. Alternatively, download the results. The results folder contains VTK files, CSV files and animations.
Load multiple VTK files. See several parameters of interest and change the field, for instance, to velocity for visualization Rotate the model or change the color scheme. Choose surface with edges or wire frame for the representation of the surface.
Apply the same methodology to every loaded VTK file. On the homepage, go to execute workflow and then choose torso in the list of available workflows. Add a comment or note in the comment section and execute the workflow.
Click on the input template file button and save the content shown on the webpage as an input dot txt file which will be used for the torso model. In the input file field select the downloaded input dot txt file. After the file is imported, click on the execute button to start the calculation.
Click on the eye or camera buttons in the bottom left corner to visualize the available simulation reports or animations directly on the platform. Alternatively, click on the 3D visualization module to visualize the output online in ParaView glance. Select the open a file button.
Go to the girder tab, enter user credentials if prompted and open the private folder. On the next page, select the workflow outputs folder and open the torso folder. See the list of VTK files that represents the simulation results.
Choose one or more files and click on the select button to load the file in ParaView glance. Manipulate the model geometry using the mouse. Next, choose the wireframe option to see the interior of the torso with a heart incorporated within the torso.
Choose the points option to display a dotted representation of the torso model with full heart mesh. Adjust the point size value to change the display results. Adjust the opacity value to see the interior of the torso and display results inside the heart mesh.
Click on the color by dropdown menu and choose the desired option. Finally, change the default color scale to any of the listed options. To simulate the realistic behavior of the left ventricle model, prescribed functions for velocities at the inlet and outlet valves were used.
An algorithm for the automatic calculation of the fiber direction was applied to this finite element model. The results for one layer and three layered solid representation are shown here. The representative images display the pressure field inside the parametrical left ventricle model during a time cycle of one second.
Five different time steps are presented here. The velocity field inside the parametrical left ventricle model is shown in these images. There are notable value peaks inside the branches caused by fluid flow during the loading unloading cycle.
The images shown here represent the displacement in the parametrical left ventricle model. Similar to the pressure change during the first two steps the displacement are negligible until the contraction when they become maximal at the bottom part of the model. Throughout the remaining time the model slowly returns to its undeformed state.
The resulting pressure volume diagram for the left ventricle fluid structure interaction model is shown here. The vectorial representation of the velocities in the parametrical model of the left ventricle is presented in these images. The representative images show the simulation of the whole heart activation at various time points on the lead two ECG signal.
The trans-membrane potential in millivolts is denoted by the color bar. The images shown here represent the map to the body surface potential in a healthy subject. The progression of ventricular activation in nine sequences corresponding to the ECG signal is displayed in these images.
The Silico FCM platform can give more information in comparison with the current medical standards including biomarkers, patient specific geometry, flow and pressure, condition, raw material properties, and drug response. The Silico FM platform can use patient specific geometry to test and optimize drug response with different combination for other cardiovascular disease. The Silico FCM computational platform will open a new avenue for In-Silico clinical trials specifically for cardiac disease and risk prediction for the patient-specific condition.
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Overview
This protocol demonstrates the workflow of the Silico FCM platform for generating a parametric model of the left ventricle from patient-specific ultrasound images. It applies a multi-scale electromechanical model of the heart, facilitating in silico clinical trials to enhance therapeutic outcomes.
Key Study Components
Area of Science
- Cardiovascular modeling
- Electromechanical modeling
- In silico clinical trials
Background
- The Silico FCM platform models the left ventricle using ultrasound images.
- It investigates drug effects through specific boundary conditions.
- It aims to reduce animal experiments and real clinical trials.
- Applicable to various cardiovascular diseases.
Purpose of Study
- To demonstrate the workflow of the Silico FCM platform.
- To maximize positive therapeutic outcomes for cardiomyopathy.
- To provide guidelines for first-time users of the platform.
Methods Used
- Application of a multi-scale electromechanical model.
- Utilization of patient-specific ultrasound images.
- Investigation of boundary conditions for flow and ECG measurements.
- Visualization of cardiovascular parameters.
Main Results
- Successful generation of a parametric model of the left ventricle.
- Demonstrated reduction in the need for animal experiments.
- Maximized therapeutic outcomes for various cardiovascular diseases.
- Provided user-friendly workflows for platform navigation.
Conclusions
- The Silico FCM platform is effective for modeling cardiac function.
- It supports the investigation of drug effects in a virtual environment.
- It has potential applications in multiple cardiovascular conditions.
Frequently Asked Questions
Executive Industry Relevance
Integrating patient-specific imaging, genetic, and physiological data, the SILICOFCM platform enables in silico clinical trials for cardiovascular disease, supporting predictive modeling of drug effects and cardiac function. This approach enhances early mechanistic de-risking and target validation, reducing reliance on animal studies and traditional clinical trial resources. The platform's quantitative outputs and simulation capabilities position it as a strategic asset for translational research and portfolio decision-making in cardiovascular drug development.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables mechanistic interrogation of cardiac drug effects using patient-specific models.
- Supports biological de-risking by simulating genetic and physiological variability.
- Facilitates functional target validation through quantitative electromechanical outputs.
- Improves predictive confidence for candidate selection in cardiovascular pipelines.
Screening & Assay Development
- Prepares validated computational models for downstream drug screening workflows.
- Standardizes simulation of boundary conditions and physiological responses.
- Generates reproducible, quantitative readouts such as pressure-volume and myocardial work diagrams.
- Enables scalable, reusable platform for compound evaluation across diverse cardiac phenotypes.
Translational & Preclinical Research
- Aligns in silico outputs with disease-relevant biomarkers and patient-specific endpoints.
- Provides continuity from discovery through preclinical risk assessment and optimization.
- Supports risk-adjusted advancement decisions by modeling drug response variability.
- Delivers predictive de-risking for late-stage cardiovascular assets.
Pipeline & Workflow Integration
The SILICOFCM platform bridges early discovery, lead identification, and preclinical validation by providing a unified computational environment for hypothesis testing and drug effect simulation.
- Discovery Biology: Enables hypothesis-driven modeling of cardiac function and drug response using patient-specific data.
- Screening: Delivers standardized, quantitative simulation outputs for comparative analysis of candidate compounds.
- Analytics: Provides pressure-volume, pressure-strain, and myocardial work-time diagrams for robust statistical evaluation.
- Translational Research: Connects in silico predictions to clinical biomarker alignment and patient stratification strategies.
- Enterprise Reuse: Offers a scalable, modular platform adaptable to multiple cardiovascular indications and research teams.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in cardiovascular drug development.
- Operational Value: Standardizes simulation workflows, enhances reproducibility, and supports scalable analyses.
- Strategic Value: Enables informed go/no-go decisions and capital-efficient portfolio management.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of cardiovascular assets.
Implementation Considerations
- Requires expertise in computational modeling, cardiac physiology, and data integration.
- Demands access to advanced imaging, genetic, and simulation infrastructure.
- Necessitates cross-team standardization of input data and simulation parameters.
- Adaptable to various cardiovascular disease models with appropriate parameterization.
- Dependent on quality and completeness of patient-specific input data for optimal predictive value.
Biopharma FAQs
Chapters in this video
0:04
Introduction
1:30
Workflow for Ultrasound M‐Mode or Apical View DICOM Image Analysis and LV Parameter Extraction
2:34
PAK Finite Element Solver for Fluid‐Structure (FS) Simulations
4:30
Determination of Ventricular Activation Sequence from ECG Measurement
6:27
Results: Fibers Direction, Velocity, Pressure Field, and Displacements in the Parametrical LV Model, Simulation of Whole‐Heart Activation, and Maps of Body Surface Potential
8:17
Conclusion
