Periodic Reporting for period 1 - DCPM (Digitalized Clone for Personalized Medicine)
Période du rapport: 2020-01-01 au 2023-10-31
Health consumes ~10% of GDP in the OECD, and grows an unsustainable 7-11% per year, and is ~1% of GDP for intensive care alone, driven by chronic diseases and aging populations. Limited funding leads to an ‘equity gap’ in health funding, where more people go untreated, less treated (rationing), and/or rely on private insurance and care, creating and exacerbating inequality. This labor-intensive sector has not made productivity gains, and the increasing demographic demand for intensive care is multiplied by a growing need for personalized, precision solutions to care.
DCPM project aims to reverse this trend by linking engineering, medicine, and industry to improve the quality, precision, and productivity of intensive care and create a template for other areas of care. Model-based methods and novel system identification technologies will be applied to create validated virtual patient models for use in personalizing care to enhance its quality and productivity. The project results will be translated to clinical use to provide precision, next-generation productive, intensive care solutions.
DCPM project aims to reverse this trend by linking engineering, medicine, and industry to improve the quality, precision, and productivity of intensive care and create a template for other areas of care. Model-based methods and novel system identification technologies will be applied to create validated virtual patient models for use in personalizing care to enhance its quality and productivity. The project results will be translated to clinical use to provide precision, next-generation productive, intensive care solutions.
Research highlights on the three main research areas of DCPM:
Development of Glycemic Control for Insulin Insufficient Individuals (GC):
• Development of a Discrete Spectrometric NIR Reflectance Glucometer
• Artificial Intelligence Based Insulin Sensitivity Prediction for Personalized Glycaemic Control in Intensive Care
• Estimating (unidentifiable) Enhanced EGP in Glycaemic Control Modelling
• Insulin Resistance in ICU Patients: Women Have Stronger Metabolic Response
Development of Next-Generation Cardiovascular System Monitoring & Management (CVS):
• Finite Element Simulation Based Analysis of Valve-Sparing Aortic Root Surgery
• Clinical Application of a Model-Based Cardiac Stroke Volume Estimation Method
• Minimally Invasive Model Based Stressed Blood Volume as an Index of Fluid Responsiveness
Development of Virtual Patient Model of the Human Lung (MV):
• Comparison between Single Compartment Model and Recruitment Basis Function Model on NICU Patients
• Non-Invasive Measurement of Tidal Breathing Lung Mechanics Using Expiratory Occlusion
• Virtual Patient Modeling and Prediction Validation for Pressure Controlled Mechanical Ventilation
The DCPM consortium made significant contributions to the leading conferences in the field:
21st IFAC World Congress, July 11-17, 2020, Berlin, Germany
The 21st IFAC World Congress with 3000+ papers and 250+ sessions on the topic Quality of Life and Health Care. Two special sessions were organized by the DCPM project participants with ~100 publications (20+ presentations were given by the DCPM partners):
• Control, Mechatronics, and Imaging for Medical Devices and Systems in Medicine,
• Physiological Control Systems in Medicine.
11th IFAC Symposium on Biological and Medical Systems, Sept 19-22, 2021, Ghent, Belgium
The BMS2021 was organized in hybrid mode with around 100 attendees where three tracks were organized by the DCPM participants closely related to the three topics of the DCPM work packages:
• Pulmonary Dynamics (2 sessions, 12 papers, 10 from DCPM partners)
• Diabetes Dynamics (2 sessions, 8 papers, 3 from DCPM partners)
• Cardiovascular Dynamics (1 session, 6 papers, 1 from DCPM partners)
IFAC World Congress 2023, July 9-14, 2023, Yokohama, Japan
2 Open Invited Tracks are organized by the lead of DCPM partners:
• Digital twins to improve medical care (16 papers – 11 from DCPM)
• Control, mechatronics, and imaging for medical devices and systems in medicine (23 papers - 19 from DCPM )
Development of Glycemic Control for Insulin Insufficient Individuals (GC):
• Development of a Discrete Spectrometric NIR Reflectance Glucometer
• Artificial Intelligence Based Insulin Sensitivity Prediction for Personalized Glycaemic Control in Intensive Care
• Estimating (unidentifiable) Enhanced EGP in Glycaemic Control Modelling
• Insulin Resistance in ICU Patients: Women Have Stronger Metabolic Response
Development of Next-Generation Cardiovascular System Monitoring & Management (CVS):
• Finite Element Simulation Based Analysis of Valve-Sparing Aortic Root Surgery
• Clinical Application of a Model-Based Cardiac Stroke Volume Estimation Method
• Minimally Invasive Model Based Stressed Blood Volume as an Index of Fluid Responsiveness
Development of Virtual Patient Model of the Human Lung (MV):
• Comparison between Single Compartment Model and Recruitment Basis Function Model on NICU Patients
• Non-Invasive Measurement of Tidal Breathing Lung Mechanics Using Expiratory Occlusion
• Virtual Patient Modeling and Prediction Validation for Pressure Controlled Mechanical Ventilation
The DCPM consortium made significant contributions to the leading conferences in the field:
21st IFAC World Congress, July 11-17, 2020, Berlin, Germany
The 21st IFAC World Congress with 3000+ papers and 250+ sessions on the topic Quality of Life and Health Care. Two special sessions were organized by the DCPM project participants with ~100 publications (20+ presentations were given by the DCPM partners):
• Control, Mechatronics, and Imaging for Medical Devices and Systems in Medicine,
• Physiological Control Systems in Medicine.
11th IFAC Symposium on Biological and Medical Systems, Sept 19-22, 2021, Ghent, Belgium
The BMS2021 was organized in hybrid mode with around 100 attendees where three tracks were organized by the DCPM participants closely related to the three topics of the DCPM work packages:
• Pulmonary Dynamics (2 sessions, 12 papers, 10 from DCPM partners)
• Diabetes Dynamics (2 sessions, 8 papers, 3 from DCPM partners)
• Cardiovascular Dynamics (1 session, 6 papers, 1 from DCPM partners)
IFAC World Congress 2023, July 9-14, 2023, Yokohama, Japan
2 Open Invited Tracks are organized by the lead of DCPM partners:
• Digital twins to improve medical care (16 papers – 11 from DCPM)
• Control, mechatronics, and imaging for medical devices and systems in medicine (23 papers - 19 from DCPM )
The proposed/delivered research significantly extends the existing models and ICU treatment methodology in all three important ICU treatment areas:
Glycaemic Control (GC):
Inter- and intra-patient variability are the single greatest challenge in glycaemic control of insulin-insufficient intensive care patients. DCPM partners developed unique, clinically validated models of metabolism and used them to create very successful ICU GC protocols implemented as standard care with ULG and BME. The existing 2D stochastic model of insulin sensitivity is used to enhance patient state prediction and manage future variability directly. Neural network-based insulin sensitivity prediction could make more personalized stochastic models. In addition, moving to higher-dimensional stochastic modelling (replacing current 2D) can provide significant improvements in the patient-specificity of predicted future variability, improving safety and performance in clinical care.
Cardiovascular Systems (CVS):
Cardiovascular dysfunction is a leading cause of ICU admission, stay, cost, and death. Managing circulation support is based on intuition and experience because no current measures exist to provide real-time diagnosis or response to care that are better than 50-60% accurate. Thus, they drive blind, and there is no way to effectively guide therapy, increasing the variability and cost of care.
Patient-specific CVS models can be identified from existing ICU measurements to provide real-time measures of stroke volume (SV) and stressed blood volume (SBV), true measures of heart function to guide monitoring and care in response to drug or fluid treatment in a patient-specific fashion. These have long been demanded by clinicians. There are currently no such measures. However, the two in concert will enable patient-specific and simultaneous optimization of CVS dynamics using inotrope (SV) and fluid (SBV) therapy, where currently these are misapplied very often due to the inability to determine if the heart needs to beat harder (inotropes) or there is a lack of fluid (fluid therapy). Hence, these are novel metrics meeting stated clinical needs, with significant clinical potential, but no validation at this time.
UOC and ULG have developed unique, clinically validated CVS models for critical illness based on extensive ULG animal studies and data, all of which offer the opportunity to significantly personalise care in real time for common, clinically relevant clinical issues that are currently “holy grail” problems in ICU care.
Mechanical Ventilation (MV):
Mechanical ventilation care is inconsistent, resulting in increased cost and mortality. The main problem is how to determine the lung status in real-time by an x-ray free (non-invasive) method to better monitor and guide care. UOC and HFU teams developed a wide range of unique, clinically validated pulmonary mechanics models to guide MV therapy. These models can be merged with anatomically denser UOA models to create the first Virtual Patient Model of the human gas-exchange system from “breath to blood,” thus providing the ability to address the direct goal of MV, oxygenation of blood and tissues, which is not currently possible. In addition, radiation-free imaging based on Electrical Impedance Tomography, which was intensively studied on ICU and home care environments to support mechanical ventilation some citations to be added will be coupled with MV models.
Overall, this modeling research would provide the first ability to guide care at the bedside and titrate it in a personalized and patient-specific manner, optimized by virtual patients. It would thus bring to MV what has been achieved in GC with prior model-based protocols. Hence, it brings world leaders together to achieve outcomes; no other single group might achieve.
Glycaemic Control (GC):
Inter- and intra-patient variability are the single greatest challenge in glycaemic control of insulin-insufficient intensive care patients. DCPM partners developed unique, clinically validated models of metabolism and used them to create very successful ICU GC protocols implemented as standard care with ULG and BME. The existing 2D stochastic model of insulin sensitivity is used to enhance patient state prediction and manage future variability directly. Neural network-based insulin sensitivity prediction could make more personalized stochastic models. In addition, moving to higher-dimensional stochastic modelling (replacing current 2D) can provide significant improvements in the patient-specificity of predicted future variability, improving safety and performance in clinical care.
Cardiovascular Systems (CVS):
Cardiovascular dysfunction is a leading cause of ICU admission, stay, cost, and death. Managing circulation support is based on intuition and experience because no current measures exist to provide real-time diagnosis or response to care that are better than 50-60% accurate. Thus, they drive blind, and there is no way to effectively guide therapy, increasing the variability and cost of care.
Patient-specific CVS models can be identified from existing ICU measurements to provide real-time measures of stroke volume (SV) and stressed blood volume (SBV), true measures of heart function to guide monitoring and care in response to drug or fluid treatment in a patient-specific fashion. These have long been demanded by clinicians. There are currently no such measures. However, the two in concert will enable patient-specific and simultaneous optimization of CVS dynamics using inotrope (SV) and fluid (SBV) therapy, where currently these are misapplied very often due to the inability to determine if the heart needs to beat harder (inotropes) or there is a lack of fluid (fluid therapy). Hence, these are novel metrics meeting stated clinical needs, with significant clinical potential, but no validation at this time.
UOC and ULG have developed unique, clinically validated CVS models for critical illness based on extensive ULG animal studies and data, all of which offer the opportunity to significantly personalise care in real time for common, clinically relevant clinical issues that are currently “holy grail” problems in ICU care.
Mechanical Ventilation (MV):
Mechanical ventilation care is inconsistent, resulting in increased cost and mortality. The main problem is how to determine the lung status in real-time by an x-ray free (non-invasive) method to better monitor and guide care. UOC and HFU teams developed a wide range of unique, clinically validated pulmonary mechanics models to guide MV therapy. These models can be merged with anatomically denser UOA models to create the first Virtual Patient Model of the human gas-exchange system from “breath to blood,” thus providing the ability to address the direct goal of MV, oxygenation of blood and tissues, which is not currently possible. In addition, radiation-free imaging based on Electrical Impedance Tomography, which was intensively studied on ICU and home care environments to support mechanical ventilation some citations to be added will be coupled with MV models.
Overall, this modeling research would provide the first ability to guide care at the bedside and titrate it in a personalized and patient-specific manner, optimized by virtual patients. It would thus bring to MV what has been achieved in GC with prior model-based protocols. Hence, it brings world leaders together to achieve outcomes; no other single group might achieve.