Author(s):
1. Nenad Filipović, Univerzitet u Kragujevcu, Serbia

Abstract:
Abstract Today digital twin technology become a new concept in many areas of science, starting from basic computer science, material science, engineering, finance, medicine, food development etc. In silico clinical trials are a new paradigm for development of a new drug and medical device. SILICOFCM project is multiscale modeling of familial cardiomyopathy which considers a comprehensive list of patient specific features as genetic, biological, pharmacologic, clinical, imaging and cellular aspects. The ventricle wall model is simulated by the muscle material model. Muscle fiber orientation is defined by direction vector in 3D prescribed through input data. The outlet blood pressure is used as the boundary condition. At the same time, the wall muscle fibers are activated according to the activation function taken from specific patient measurements. Computational Platform for Multiscale Modelling in biomedical engineering is results of SGABU project that is served as an educational tool for students and researchers. The platform integrates already developed solutions and various datasets related to cancer, cardiovascular, bone disorders and tissue engineering into one multiscale platform. This will enable further validation and parameterization of models, creation of environment for future trends, e.g. in silico clinical trials, virtual surgery, development of prediction models. Digital twin technology connects basic experimental research with clinical study and bioinformatics, data mining and image processing tools using very advanced computer models for drug, medical device, new design materials and patient database in order to reduce animal and clinical studies. Acknowledgement: This paper is supported by the projects that have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952603 (SGABU project). This paper reflects only the author's view. The Commission is not responsible for any use that may be made of the information it contains.

Key words:
digital twin,material science,bioinformatics,insilico clinical trials,machine learning,cardiovascular disease

Thematic field:
SYMPOSIUM B - Biomaterials and nanomedicine

Date of abstract submission:
05.07.2023.

Conference:
Contemporary Materials 2023 - Savremeni materijali

Applied paper from author