What we do
About our project
Healthy Joints are essential for physical functioning throughout life. Among joint diseases osteoarthritis (OA) has the highest prevalence and disability. In coming decades OA will become the most common chronic disease in the Netherlands. There are still enormous challenges in OA, ranging from poor understanding about the disease to insufficient early diagnostics and ineffective and non-personalized treatment strategies. To move the field forward, we aim to prevent, diagnose and treat OA at an earlier stage, and target personalized management. For this, it is imperative to improve our understanding of OA phenotypes and how these can be detected early, to develop and apply innovative technology at all anatomical scales and phases of the disease, and to develop and test preventive or early-stage personalized interventions. These efforts will be aligned with the stakeholders’ acceptance, and behavioural aspects.
Our research focus
1) Developing precise personalized computational models for healthy joint growth and maintenance, assess joint load in high-risk and early-stage OA groups, enabling artificial testing of new and precise preventive and early-stage interventions
2) Build cellular models for different joint tissues and phenotypes to identify personal drivers of OA, and use joint-on-a-chip to test interventions at cell level
3) Improved and novel diagnostics based on novel hybrid imaging modalities and computational biomechanics enabling the early diagnosis of adverse cartilage load and metabolic joint processes and subsequent targeted therapy
4) Machine-learning techniques to better recognize the early imaging joint tissue changes, and the
phenotype specific patterns
5) Test preventive treatment, early-stage diagnostics and treatment combined with behavioural insights and stakeholder choices.
2) Build cellular models for different joint tissues and phenotypes to identify personal drivers of OA, and use joint-on-a-chip to test interventions at cell level
3) Improved and novel diagnostics based on novel hybrid imaging modalities and computational biomechanics enabling the early diagnosis of adverse cartilage load and metabolic joint processes and subsequent targeted therapy
4) Machine-learning techniques to better recognize the early imaging joint tissue changes, and the
phenotype specific patterns
5) Test preventive treatment, early-stage diagnostics and treatment combined with behavioural insights and stakeholder choices.
Funds & Grants
Funding agency: Convergence (Flagship program)
Our team
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Prof. dr. S.M.A. (Sita) Bierma-Zeinstra
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G.J.V.M (Gerjo) van Osch PhD
professor, principal investigator
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Prof. dr. ir. J. (Jaap) Harlaar
Full professor
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D.E. (Duncan) Meuffels, MD PhD
Associate Professor, orthopaedic surgeon
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R. (Rintje) Agricola, MD PhD
Orthopedic Surgeon and Principal Investigator
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P.K. (Koen) Bos, MD, PhD
Orthopaedic surgeon
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R. (Roberto) Narcisi, PhD
Associate professor
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J.J. (Jaap) Tolk, MD PhD
Pediatric Orthopedic Surgeon
