Cost Effectiveness Analysis of Real and in Silico Clinical Trials for Stent Deployment Based on Decision Tree(Conference Paper)
- aInstitute for Information Technologies, University of Kragujevac, Jovana Cvijića bb Street, Kragujevac, 34000, Serbia
- bBioengineering Research and Development Centre (BioIRC), 6 Prvoslava Stojanovića Street, Kragujevac, 34000, Serbia
Abstract
The global coronary and peripheral stent market size was valued at 5.91 billion USD in 2019 and is projected to reach 8.08 billion USD by 2027 as new and innovative devices are being invented and developed rapidly. In this process of developing new models of stents, one of the key phases is clinical testing on patients. The aim of in silico medicine is to Reduce, Refine and Replace (3R concept) real clinical trials with an aim to decrease costs and time needed to perform a clinical study. Within the InSilc project (funded by H2020 programme, GA 777119) the platform for designing, developing and assessing stents was developed. The platform consists of several modules, some of which can be used as standalone modules. Characteristics of Mechanical and Deployment Module are presented in this chapter. Pricing strategies for different scenarios are described in order to prove the effectiveness and benefits of in-silico testing. The workflow begins from the Mechanical module, and continues to the prediction of the stenting outcomes for different virtual anatomies and different modules: 3D reconstruction and plaque characterization tool, Deployment Module, Fluid dynamics Module, Drug-delivery Module, Degradation Module and Myocardial Perfusion Module. Cost-effectiveness analysis is done using decision tree for in silico and real clinical trials for coronary stent deployment. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Indexed keywords
| Engineering controlled terms: | Cost benefit analysisCost effectivenessDrug deliveryStents |
|---|---|
| Engineering uncontrolled terms | Clinical trialCoronary arteriesCost effectiveness analysisIn silico clinical trialIn-silicoPeripheral arteriesPricing strategyStent deploymentsStentingStenting outcomeVirtual anatomy |
| Engineering main heading: | Decision trees |
Funding details
| Funding sponsor | Funding number | Acronym |
|---|---|---|
| Horizon 2020 Framework Programme See opportunities by H2020 | 956470,GA 777119 | H2020 |
| Horizon 2020 Framework Programme See opportunities by H2020 | H2020 |
-
1
Acknowledgment. This research is supported by the projects that have received funding from the European Union’s Horizon 2020: InSilc - GA 777119 and DECODE MSCA - GA No 956470. This article reflects only the author’s view. The Commission is not responsible for any use that may be made of the information it contains.
- ISSN: 23673370
- ISBN: 978-303129716-8
- Source Type: Book Series
- Original language: English
- DOI: 10.1007/978-3-031-29717-5_22
- Document Type: Conference Paper
- Volume Editors: Filipovic N.
- Publisher: Springer Science and Business Media Deutschland GmbH
Gačić, M.; Institute for Information Technologies, University of Kragujevac, Jovana Cvijića bb Street, Kragujevac, Serbia;
© Copyright 2024 Elsevier B.V., All rights reserved.