Periodic Reporting for period 1 - O-Health (Scalable systems modelling to simulate body-level interplays among non-communicable diseases)
Periodo di rendicontazione: 2022-11-01 al 2025-04-30
Load-bearing organ non-communicable diseases (NCD) emerge silently. Clinical tests can't capture the underlying complexity, but O-Health proposes multiscale computer models, or "digital twins," can.
While digital twins have advanced, multi-disease modelling is underdeveloped. O-Health addresses this by developing a scalable ecosystem of multiscale NCD models linked by a systemic low-grade inflammation model.
The project models atherosclerosis, intervertebral disc degeneration, knee osteoarthritis, and lung emphysema. Each NCD model cellular/molecular components will feed into an endothelial cell dysfunction interface, which communicates with a body-wide systemic communication model.
The ecosystem uses finite element models for organs, and agent-based and or regulatory network models for cells. High-level interaction graphs will link mechanistic findings with real-world data from population cohorts.
While digital twins have advanced, multi-disease modelling is underdeveloped. O-Health addresses this by developing a scalable ecosystem of multiscale NCD models linked by a systemic low-grade inflammation model.
The project models atherosclerosis, intervertebral disc degeneration, knee osteoarthritis, and lung emphysema. Each NCD model cellular/molecular components will feed into an endothelial cell dysfunction interface, which communicates with a body-wide systemic communication model.
The ecosystem uses finite element models for organs, and agent-based and or regulatory network models for cells. High-level interaction graphs will link mechanistic findings with real-world data from population cohorts.
O-Health pioneers a modelling ecosystem to alleviate non-communicable diseases (NCD) by integrating computational efficiency with biological complexity. It develops scalable technologies to manage conditions like intervertebral disc degeneration, knee osteoarthritis, and atherosclerosis.
A common framework for vertical modelling uses a Parallel Network (PN) methodology and Regulatory Network Models (RNMs) for high-resolution biological descriptions. This is applied to model intervertebral disc and articular cartilage cell behavior. An endothelial interface model, focusing on mechanosensitive endothelial cells, facilitates communication between vertical and transversal NCD models. This model, first applied to arteries, has revealed the role of macrophage activation and oxidized LDL in early atherosclerosis.
Data from large cohorts like the Northern Finland Birth Cohort and the UK Biobank informs the models, identifying factors such as uric acid in knee osteoarthritis and cholesterol transport in atherosclerosis. This data also enables personalized finite element models, stratifying patient cohorts.
O-Health is co-developing a body-wide agent-based model of the vascular system using BioDynaMo software. It has also made progress in modelling the innate immune system, particularly macrophage polarization, using an RNM approach. Advanced spine modelling has already improved surgical planning, with a patent in preparation.
A common framework for vertical modelling uses a Parallel Network (PN) methodology and Regulatory Network Models (RNMs) for high-resolution biological descriptions. This is applied to model intervertebral disc and articular cartilage cell behavior. An endothelial interface model, focusing on mechanosensitive endothelial cells, facilitates communication between vertical and transversal NCD models. This model, first applied to arteries, has revealed the role of macrophage activation and oxidized LDL in early atherosclerosis.
Data from large cohorts like the Northern Finland Birth Cohort and the UK Biobank informs the models, identifying factors such as uric acid in knee osteoarthritis and cholesterol transport in atherosclerosis. This data also enables personalized finite element models, stratifying patient cohorts.
O-Health is co-developing a body-wide agent-based model of the vascular system using BioDynaMo software. It has also made progress in modelling the innate immune system, particularly macrophage polarization, using an RNM approach. Advanced spine modelling has already improved surgical planning, with a patent in preparation.
O-Health's innovative approach to modelling non-communicable diseases (NCD) has yielded significant breakthroughs, pushing the boundaries of current scientific understanding and technological capabilities. By integrating real-world data with advanced simulations, O-Health is transforming the landscape of personalized medicine and healthcare solutions.
Foreseen Developments and Breakthroughs
A notable achievement is the augmentation of real-world data with Regulatory Network Model (RNM) simulations. This integration has shed light on the critical role of oxidative stress control in the symptomatology of knee osteoarthritis (KOA) patients, challenging the traditional focus on pro-inflammatory targets. This insight, coupled with the mining of patient synovial data, has motivated the development of unique macrophage activation and differentiation models. These models not only represent oxidative stress regulation but also incorporate the control mechanisms exerted by anti-inflammatory molecules.
The macrophage model is designed to interface with the articular cartilage RNM-FE model, facilitating a comprehensive coupling of KOA vertical modelling with transversal low-grade inflammation models. This advancement has also spurred further development of the intervertebral disc (IVD) cell regulation pathway RNM, emphasizing the importance of oxidative stress in disease progression.
The validation of the Parallel Network (PN) methodology, particularly in IVD modelling, has significantly enhanced the capacity for virtual data augmentation. This, combined with the rapid generation of IVD cohort models and the integration of PN in finite element (FE) solvers, enables advanced stratification of IVD degeneration (IDD) cases. This breakthrough has led to the adaptation of the Disease State characterisation methods based on machine learning, and key predictors of pain were identified, such as sleep difficulties and depression.
Unplanned Developments and Innovations
The development of fast, personalized organ 3D FE modelling has expanded O-Health's modelling capabilities beyond the initial focus on IVD and knee joints, extending to the thoracolumbar spine. This unplanned advancement has given rise to SimOSpine, a novel technology for the planning and prognosis of corrective spine surgery (CSS) through real-time modelling and simulation. Backed by robust technological foundations and successful preclinical validations, SimOSpine has secured competitive funding, facilitating tangible transfer of technology and entrepreneurship actions.
Future Prospects
As O-Health continues to consolidate its objectives, particularly in endothelial interface modelling and data-driven approaches, further breakthroughs are anticipated. The integration of biological descriptors informed by metabolic and innate immune system regulation models will drive these advancements, paving the way for more precise and personalized healthcare solutions.
Literature References:
Regulation of proteoglycans and collagen types in IVD: doi:10.1101/2022.08.08.503195 (Author preprint)
Regulation of protease inhibitors under mechanical loads: doi:10.1002/jsp2.70051
Modelling of normal and catabolic IVD cell behavior: doi:10.1038/s41540-024-00479-6
Articular cartilage chondrocyte response modelling: doi:10.3389/fbioe.2023.1006066
Synovial joint proteomics and patient cohort data mining: doi:10.1038/s41598-024-62212-x
Personalized FE models for spine and knee joint: doi:10.1007/978-3-031-72104-5_55
Biomechanical stratification of patient cohorts: doi:10.3389/fbioe.2024.1384599
Prognosis and planning for corrective spine surgery: doi:10.1097/BRS.0000000000004630
Modelling and simulation for spine surgery: doi:10.1016/j.xnsj.2025.100770
Foreseen Developments and Breakthroughs
A notable achievement is the augmentation of real-world data with Regulatory Network Model (RNM) simulations. This integration has shed light on the critical role of oxidative stress control in the symptomatology of knee osteoarthritis (KOA) patients, challenging the traditional focus on pro-inflammatory targets. This insight, coupled with the mining of patient synovial data, has motivated the development of unique macrophage activation and differentiation models. These models not only represent oxidative stress regulation but also incorporate the control mechanisms exerted by anti-inflammatory molecules.
The macrophage model is designed to interface with the articular cartilage RNM-FE model, facilitating a comprehensive coupling of KOA vertical modelling with transversal low-grade inflammation models. This advancement has also spurred further development of the intervertebral disc (IVD) cell regulation pathway RNM, emphasizing the importance of oxidative stress in disease progression.
The validation of the Parallel Network (PN) methodology, particularly in IVD modelling, has significantly enhanced the capacity for virtual data augmentation. This, combined with the rapid generation of IVD cohort models and the integration of PN in finite element (FE) solvers, enables advanced stratification of IVD degeneration (IDD) cases. This breakthrough has led to the adaptation of the Disease State characterisation methods based on machine learning, and key predictors of pain were identified, such as sleep difficulties and depression.
Unplanned Developments and Innovations
The development of fast, personalized organ 3D FE modelling has expanded O-Health's modelling capabilities beyond the initial focus on IVD and knee joints, extending to the thoracolumbar spine. This unplanned advancement has given rise to SimOSpine, a novel technology for the planning and prognosis of corrective spine surgery (CSS) through real-time modelling and simulation. Backed by robust technological foundations and successful preclinical validations, SimOSpine has secured competitive funding, facilitating tangible transfer of technology and entrepreneurship actions.
Future Prospects
As O-Health continues to consolidate its objectives, particularly in endothelial interface modelling and data-driven approaches, further breakthroughs are anticipated. The integration of biological descriptors informed by metabolic and innate immune system regulation models will drive these advancements, paving the way for more precise and personalized healthcare solutions.
Literature References:
Regulation of proteoglycans and collagen types in IVD: doi:10.1101/2022.08.08.503195 (Author preprint)
Regulation of protease inhibitors under mechanical loads: doi:10.1002/jsp2.70051
Modelling of normal and catabolic IVD cell behavior: doi:10.1038/s41540-024-00479-6
Articular cartilage chondrocyte response modelling: doi:10.3389/fbioe.2023.1006066
Synovial joint proteomics and patient cohort data mining: doi:10.1038/s41598-024-62212-x
Personalized FE models for spine and knee joint: doi:10.1007/978-3-031-72104-5_55
Biomechanical stratification of patient cohorts: doi:10.3389/fbioe.2024.1384599
Prognosis and planning for corrective spine surgery: doi:10.1097/BRS.0000000000004630
Modelling and simulation for spine surgery: doi:10.1016/j.xnsj.2025.100770