Periodic Reporting for period 2 - Disc4All (Training network to advance integrated computational simulations in translational medicine, applied to intervertebral disc degeneration)
Periodo di rendicontazione: 2022-11-01 al 2025-05-31
The European community requires a new generation of researchers who can work across traditional disciplinary boundaries, integrating experimental and in silico approaches to understand and manage highly prevalent multifactorial disorders, such as musculoskeletal disorders. The Disc4All training network addressed this need by focusing on intervertebral disc degeneration (LDD), a key contributor to low back pain (LBP), as a relevant case for integrating data and computational simulations in translational medicine. The project enabled rational interpretations of the complex interactions that lead to symptoms.
LBP is the leading cause of morbidity worldwide and the 4th leading cause of DALYs among non-communicable diseases for individuals aged 25–49, according to the 2019 Global Burden of Disease Report. Despite its impact, specific causes remain unclear, resulting in limited treatment options and poor prognosis. LDD accounts for around 50% of LBP in young adults, yet the interplay of genetic, environmental, cellular, psychological, and social factors is still not fully understood. Integrating these factors into a comprehensive model of degenerative processes and risk remains a challenge that current biomedical and translational training programs often fail to address.
Disc4All tackled this challenge through collaboration among clinicians, computational physicists and biologists, geneticists, computer scientists, cell and molecular biologists, microbiologists, bioinformaticians, and industry partners. The project offered interdisciplinary training in data curation and integration; experimental and computational modelling; algorithm and tool development; and simulation platforms to support clinical insights. Additional training covered dissemination, project management, research integrity, ethics, regulation, policy, business strategy, and public and patient engagement. All project objectives have been successfully achieved. The ESRs trained now represent a new generation of international professionals with unique, interdisciplinary skill sets to advance translational research in multifactorial disorders.
LBP is the leading cause of morbidity worldwide and the 4th leading cause of DALYs among non-communicable diseases for individuals aged 25–49, according to the 2019 Global Burden of Disease Report. Despite its impact, specific causes remain unclear, resulting in limited treatment options and poor prognosis. LDD accounts for around 50% of LBP in young adults, yet the interplay of genetic, environmental, cellular, psychological, and social factors is still not fully understood. Integrating these factors into a comprehensive model of degenerative processes and risk remains a challenge that current biomedical and translational training programs often fail to address.
Disc4All tackled this challenge through collaboration among clinicians, computational physicists and biologists, geneticists, computer scientists, cell and molecular biologists, microbiologists, bioinformaticians, and industry partners. The project offered interdisciplinary training in data curation and integration; experimental and computational modelling; algorithm and tool development; and simulation platforms to support clinical insights. Additional training covered dissemination, project management, research integrity, ethics, regulation, policy, business strategy, and public and patient engagement. All project objectives have been successfully achieved. The ESRs trained now represent a new generation of international professionals with unique, interdisciplinary skill sets to advance translational research in multifactorial disorders.
The project reached major milestones in creating an advanced digital platform for biomedical research, focusing on spine conditions like disc degeneration. The platform is fully operational, scalable, and built to support future growth. It integrates cutting-edge tools for managing complex workflows, ensuring data privacy, and providing secure access, allowing researchers to work flexibly and safely with sensitive data. A key technical achievement was adopting BioExcel Building Blocks, a Python-based framework that streamlines the integration and execution of diverse scientific workflows. Designed for open science and collaboration, the platform supports interoperability with other research infrastructures. One standout innovation was the use of privacy-preserving methods to create synthetic versions of sensitive medical data, including MRI images. These synthetic datasets allow wider data sharing without compromising patient privacy and are shared through BSC infrastructure. Secure access is managed via the INB Identity Portal. The platform runs actively, with backend and frontend services supported by container orchestration via Portainer and proxy systems, enabling efficient deployment and management of research tools. On the scientific front, new tools developed at OULU and KCL extract quantitative imaging phenotypes linked to spinal disc degeneration. These link imaging with genetic and molecular data to model disease progression in clinical cohorts, improving tools like SpineNet by moving from simple grading to advanced patient stratification. The project also had strong impact beyond spine research. ESRs at UPF adapted tools to generate personalized knee joint models for osteoarthritis and created precise 3D spine models from X-rays for surgical planning. GALGO enhanced anatomical modeling with neural network–based 2D–3D methods. UPF repurposed simulations to study osteoarthritis cell behavior, while IMIM’s network embedding pipeline predicted comorbidities and drug interactions, aiding personalized medicine. Results were widely shared via public web portals, scientific publications, and cross-disciplinary collaborations, emphasizing open science. Overall, the project delivered a robust, scalable platform and practical tools, advancing precision healthcare by integrating imaging, omics, and AI technologies.
Beyond being a training programme that has successfully fostered a new generation of translational researchers, Disc4All has significantly contributed to the structuring of doctoral training and has strengthened the research and innovation landscape at the European level. More than just a research initiative, Disc4All has delivered concrete, exploitable results that benefit both its consortium and society at large—particularly in the realms of data integration and computational simulations in translational medicine. A key achievement of the project is the development of a simulation platform that provides access to integrated models and datasets, enabling users to run simulations and conduct further analyses. For its primary users—researchers, regulators, and clinicians—this platform delivers substantial value through modelling and simulation, pathway and data integration, knowledge extraction, and biomarker identification. Looking ahead, this platform has potential to serve a diverse customer base, including government bodies, healthcare providers, medical equipment manufacturers, and the broader scientific community. In the immediate term, however, the Disc4All infrastructure is already making a significant contribution to open science, offering tools that are directly applicable in both scientific research and clinical settings, particularly in the study of intervertebral disc degeneration. Throughout the project, new insights into the origin, biology, and treatment of low back pain and disc degeneration have emerged, driven by the interdisciplinary collaboration and ‘cross-pollination’ among the 15 early-stage researchers involved. Their collective efforts have enhanced our understanding of these complex conditions and opened new avenues for innovation. Disc4All has also promoted career development in translational research, equipping a new generation of internationally mobile professionals with the skills and capabilities needed to address complex medical challenges using data-driven technologies. Among the project's tangible outcomes is the creation of tools for the advanced diagnosis and stratification of low back pain patients. These tools leverage medical imaging, pain assessment, and molecular data—enhanced by simulations and modelling—to support more targeted and effective therapies. On a socio-economic level, Disc4All has actively raised awareness around low back pain and spinal health. It has encouraged self-monitoring and improved self-management practices for prevention and treatment alike. This includes empowering individuals with knowledge and tools to act on modifiable factors—such as lifestyle habits—that can influence both the onset of symptoms and the outcomes of clinical interventions. In summary, Disc4All has not only fulfilled its training mission but has also laid the groundwork for long-term impact in healthcare, research, and society.