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2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE), 2021

DOI: 10.1109/bibe52308.2021.9635321

Journal of the Serbian Society for Computational Mechanics, 2(16), p. 105-116, 2022

DOI: 10.24874/jsscm.2022.16.02.08

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Cost-Effectiveness Analysis of in Silico Clinical Trials of Vascular Stents

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Today, it takes ten to twelve years on average to complete a clinical trial before a new drug is approved and brought to marktet. Moreover, the evaluation of the efficacy and safety of drugs or devices has been performed in the linear and sequential manner with limited change over the past decade. The InSilc project is an EU funded project (www.insilc.eu) within which the InSilc platform was developed for designing, developing and assessing coronary stents. The InSilc platform contains the following modules: Mechanical Modelling Module, 3D Reconstruction and Plaque Characterization Tool, Deployment Module, Fluid Dynamics Module, Drug Delivery Module, Degradation Module, Myocardial Perfusion Module, Virtual Population Physiology and Virtual Population Database. We analyze the cost of three different in silico scenarios for clinical study. In Scenario 1, two different stent designs are compared according to the ISO standard for in silico mechanical tests. Scenario 2 predicts the stenting outcome for a virtual anatomy where design/material could be changed. Scenario 3 compares two stents using the same virtual anatomies from the Virtual vessel database. Cost-effectiveness analysis was performed for real clinical trials with metallic and BVS stent and in silico clinical trials. It was observed that in silico clinical trials are almost 90 times cheaper than real clinical trials for 1000 patients. In Silico clinical trials will not completely replace real clinical studies but the evidence shows that they can significantly reduce the cost of a real clinical study which will open a new avenue for future hybrid real and in silico clinical trials.