Abstract
The Digital Twin paradigm in medical care has recently gained popularity among proponents of translational medicine, to enable clinicians to make informed choices regarding treatment on the basis of digital simulations. In this paper we present an overview of functional and non-functional requirements related to specific IT solutions which enable such simulations - including the need to ensure repeatability and traceability of results - and propose an architecture that satisfies these requirements. We then describe a computational platform that facilitates digital twin simulations, and validate our approach in the context of a real-life medical use case: the BoneStrength application.
This work was supported by the EDITH, a coordination and support action funded by the Digital Europe program of the European Commission under grant agreement No. 101083771. This work was also supported by the European Union’s Horizon 2020 research and innovation program under grant agreement Sano No. 857533 as well as the Sano project carried out within the International Research Agendas program of the Foundation for Polish Science, co-financed by the European Union under the European Regional Development Fund. This work was (partly) supported by the European Union’s Horizon 2020 research and innovation program under grant agreement ISW No. 101016503. We also gratefully acknowledge Poland’s high-performance computing infrastructure PLGrid (HPC Centers: ACK Cyfronet AGH) for providing computer facilities and support within computational grant No. PLG/2022/015850.
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Notes
- 1.
Repeatability, Replicability, Reproducibility.
- 2.
The PLGrid infrastructure is a joint effort of the largest HPC centers in Poland. It offers coherent management of users, groups and computational grants, as well as unified access to the integrated HPC clusters [28].
- 3.
PLGrid identity provider, which is capable of generating user proxy certificates that delegate user rights to the HPC infrastructure.
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Kasztelnik, M. et al. (2023). Digital Twin Simulation Development and Execution on HPC Infrastructures. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 14074. Springer, Cham. https://doi.org/10.1007/978-3-031-36021-3_2
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