In Silico World: Lowering barriers to ubiquitous adoption of In Silico Trials

Livrables

Report on the certification of validation data

The report will provide identification of the best certification strategy for each of the initial collections This will be reviewed against best practices also in other fields but also by discussing specific issues regarding regulatory aspects In addition a general certification strategy that could be effective for all validation data collections will be identified and discussed In parallel methods to deal with data uncertainty and missing data in validation collections will be described and analysed using existing data collections

In-depth analysis of legal and ethical requirements

This deliverable further elaborates on the main ethical and legal requirements identified in D9.1, in light of in-depth research including extensive analysis of legislation, case law and doctrine.

Final report on Advanced solutions

Report describing final versions of modelling track solutions.

Report on initial validation data collections

The report will contain an analysis of the data collections FFRValid HFValid TBValid and StentValid with respect to their intended use and a description of the way they are published In addition a general characterisation of data collection types intended use and the implication for storage usability searchability and certification will be defined and published Where possible this report will also contain datasets of other partners who are contributing early collections in termsof requirements and specific guidelines The analysis will also consider the ethical societal and regulatory requirements

Legal and ethical inventory

This deliverable maps the relevant ethical and legal requirements that partners should take into account from the early stages of the project

Policy Brief

The policy brief is a report that is produced based on the preparatory phases of stakeholder outreach activities (networking & desk review). In the report, for each stakeholder group, the results of the data analysis will be presented and discussed and the resulting specific engagement actions will be listed. The final report document will be available by M36.

Publications

Surrogate model based sensitivity analysis of a one dimensional arterial pulse wave propagation model with correlated input

Auteurs: Pjotr Hilhorst
Publié dans: ISW Zenodo Repository, Numéro 3, 2022
Éditeur: UvA
DOI: 10.5281/zenodo.7225277

Serverless Approach to Sensitivity Analysis of Computational Models

Auteurs: Piotr Kica; Magdalena Otta; Krzysztof Czechowic; Karol Zajac; Piotr Nowakowski; Andrew Narracott; Ian Halliday; Maciej Malawski
Publié dans: 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Numéro 7, 2023, ISBN 979-8-3503-0119-9
Éditeur: IEEE
DOI: 10.1109/ccgrid57682.2023.00064

Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility

Auteurs: Flora T. Musuamba, Ine Skottheim Rusten, Raphaëlle Lesage, Giulia Russo, Roberta Bursi, Luca Emili, Gaby Wangorsch, Efthymios Manolis, Kristin E. Karlsson, Alexander Kulesza, Eulalie Courcelles, Jean-Pierre Boissel, Cécile F. Rousseau, Emmanuelle M. Voisin, Rossana Alessandrello, Nuno Curado, Enrico Dall’ara, Blanca Rodriguez, Francesco Pappalardo, Liesbet Geris
Publié dans: CPT: Pharmacometrics & Systems Pharmacology, 2021, ISSN 2163-8306
Éditeur: Nature Publishing Group
DOI: 10.1002/psp4.12669

First blood: An efficient, hybrid one- and zero-dimensional, modular hemodynamic solver

Auteurs: Richárd Wéber, Dániel Gyürki, György Paál
Publié dans: International Journal for Numerical Methods in Biomedical Engineering, Numéro Volume 39, Numéro 5, 2023, ISSN 2040-7939
Éditeur: John Wiley & Sons Ltd.
DOI: 10.1002/cnm.3701

A Credibility Assessment Plan for an In Silico Model that Predicts the Dose–Response Relationship of New Tuberculosis Treatments

Auteurs: Cristina Curreli; Valentina Di Salvatore; Giulia Russo; Francesco Pappalardo; Marco Viceconti
Publié dans: Annals of Biomedical Engineering, Numéro Ann Biomed Eng volume 51, 2023, Page(s) 200–210, ISSN 1573-9686
Éditeur: Springer Nature
DOI: 10.1007/s10439-022-03078-w

Efficient sensitivity analysis for biomechanical models with correlated inputs

Auteurs: Pjotr L. J. Hilhorst, Sjeng Quicken, Frans N. van de Vosse, Wouter Huberts
Publié dans: International Journal for Numerical Methods in Biomedical Engineering, 2023, ISSN 2040-7939
Éditeur: John Wiley & Sons Ltd.
DOI: 10.1002/cnm.3797

Inverse uncertainty quantification of a mechanical model of arterial tissue with surrogate modelling

Auteurs: Salome Kakhaia; Pavel Zun; Dongwei Ye; Valeria Krzhizhanovskaya
Publié dans: Reliability Engineering & System Safety, Numéro Volume 238, October 2023, 109393, 2023, ISSN 0951-8320
Éditeur: Elsevier BV
DOI: 10.1016/j.ress.2023.109393

Boosting multiple sclerosis lesion segmentation through attention mechanism

Auteurs: Alessia Rondinella; Elena Crispino; Francesco Guarnera; Oliver Giudice; Alessandro Ortis; Giulia Russo; Clara Di Lorenzo; Davide Maimone; Francesco Pappalardo; Sebastiano Battiato
Publié dans: Computers in Biology and Medicine, Numéro Volume 161, July 2023, 107021, 2023, ISSN 0010-4825
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.compbiomed.2023.107021

Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling

Auteurs: Dongwei Ye; Pavel Zun; Valeria Krzhizhanovskaya; Alfons G. Hoekstra
Publié dans: Journal of the Royal Society Interface, 19(187):20210864. The Royal Society, Numéro Volume 19Numéro 187, 2022, ISSN 1742-5662
Éditeur: Royal Society
DOI: 10.1098/rsif.2021.0864

Automated Prediction of the Response to Neoadjuvant Chemoradiotherapy in Patients Affected by Rectal Cancer

Auteurs: Giuseppe Filitto; Francesca Coppola; Nico Curti; Enrico Giampieri; Daniele Dall'Olio; Alessandra Merlotti; Arrigo Cattabriga; Maria Cocozza; Makoto Taninokuchi Tomassoni; Daniel Remondini; Luisa Pierotti; Lidia Strigari; Dajana Cuicchi; Alessandra Guido; Karim Rihawi; Antonietta D'Errico; Francesca Di Fabio; Gilberto Poggioli; Alessio Morganti; Luigi Ricciardiello; Rita Golfieri; Gastone Castellan
Publié dans: Cancers; Volume 14; Numéro 9; Pages: 2231, Numéro 10, 2022, ISSN 2072-6694
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers14092231

Statistical Properties of a Virtual Cohort for In Silico Trials Generated with a Statistical Anatomy Atlas

Auteurs: Antonino A. La Mattina; Fabio Baruffaldi; Mark Taylor; Marco Viceconti
Publié dans: Annals of Biomedical Engineering: The Journal of the Biomedical Engineering Society, Numéro Volume 51, pages 117–124, (2023), 2022, ISSN 1573-9686
Éditeur: Springer Nature
DOI: 10.1007/s10439-022-03050-8

Position Paper From the Digital Twins in Healthcare to the Virtual Human Twin: A Moon-Shot Project for Digital Health Research

Auteurs: M. Viceconti, M. De Vos, S. Mellone, L. Geris
Publié dans: IEEE Journal of Biomedical and Health Informatics, Numéro vol. 28, no. 1, pp. 491-501, Jan. 2024, 2024, ISSN 2168-2208
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jbhi.2023.3323688

Possible Contexts of Use for In Silico Trials Methodologies: A Consensus-Based Review

Auteurs: Marco Viceconti; Luca Emili; Payman Afshari; Eulalie Courcelles; Cristina Curreli; Nele Famaey; Liesbet Geris; Marc Horner; Maria Cristina Jori; Alexander Kulesza; Axel Loewe; Michael Neidlin; Markus Reiterer; Cécile F. Rousseau; Giulia Russo; Simon J. Sonntag; Emmanuelle M. Voisin; Francesco Pappalardo
Publié dans: IEEE Journal of Biomedical and Health Informatics, Numéro Volume: 25 Numéro: 10, 2021, ISSN 2168-2208
Éditeur: IEEE
DOI: 10.1109/jbhi.2021.3090469

Toward A Regulatory Pathway for the Use of in Silico Trials in the CE Marking of Medical Devices

Auteurs: Francesco Pappalardo; John Wilkinson; Francois Busquet; Antoine Bril; Mark Palmer; Barry Walker; Cristina Curreli; Giulia Russo; Thierry Marchal; Elena Toschi; Rossana Alessandrello; Vincenzo Costignola; Ingrid Klingmann; Martina Contin; Bernard Staumont; Matthias Woiczinski; Christian Kaddick; Valentina Di Salvatore; Alessandra Aldieri; Liesbet Geris; Marco Viceconti
Publié dans: IEEE Journal of Biomedical and Health Informatics, Numéro Volume: 26, Numéro: 11, 2022, Page(s) 5282 - 5286, ISSN 2168-2208
Éditeur: IEEE
DOI: 10.1109/jbhi.2022.3198145

Mapping the use of computational modelling and simulation in clinics: A survey

Auteurs: Raphaëlle Lesage; Michiel Van Oudheusden; Silvia Schievano; Ine Van Hoyweghen; Liesbet Geris; Claudio Capelli
Publié dans: Frontiers in Medical Technology, Numéro Front. Med. Technol., Volume 5 - 2023, 2023, ISSN 2673-3129
Éditeur: Frontiers
DOI: 10.3389/fmedt.2023.1125524

Experimental validation of a subject-specific finite element model of lumbar spine segment using digital image correlation

Auteurs: Chiara Garavelli; Cristina Curreli; Marco Palanca; Alessandra Aldieri; Luca Cristofolini; Marco Viceconti
Publié dans: PLOS ONE, Numéro September 9, 2022, 2022, ISSN 1932-6203
Éditeur: Public Library of Science
DOI: 10.1371/journal.pone.0272529

Proximal femur bone mineral density in osteoporotic patients a review of placebo groups in clinical trials

Auteurs: Oliviero, Sara
Publié dans: ISW Zenodo repository, Numéro 5, 2022
Éditeur: UNIBO
DOI: 10.5281/zenodo.7248963

Computer modelling and simulation in clinics: mapping usage and opinions for advancing in silico medicine

Auteurs: Raphaelle Lesage; Michiel Van Oudheusden; Martina Contin; Silvia Schievano; Liesbet Geris; Claudio Capelli
Publié dans: ISW Zenodo Repository, Numéro 6, 2022
Éditeur: VPHi KU Leuven
DOI: 10.5281/zenodo.7437507

Proposal for curricula to train and retrain different stakeholders on In Silico Trials

Auteurs: Vander Linden, Klaas; Van Looy, Guy; Davico, Giorgio; Viceconti, Marco; Vander Sloten, Jos
Publié dans: ISW Zenodo repository, 2023
Éditeur: KU Leuven
DOI: 10.5281/zenodo.10400657

Mapping the use of computer modelling and simulation in clinics

Auteurs: Raphaëlle; Michiel; Silvia; Ine; Claudio; Giulia; Martina; Roberta; Goran
Publié dans: ISW Zenodo Repository, Numéro 7, 2023
Éditeur: VPHi
DOI: 10.5281/zenodo.7974392

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