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CMS4Vent - Alternative methods: In silico methods in ventilation technology - Model development

  • Rostalski, Philipp (Principal Investigator (PI))
  • Schädler, D. (Project Staff)
  • Selpien, Helene (Project Staff)
  • Männel, Georg (Project Staff)
  • Bilda, Franziska (Project Staff)
  • Hennigs, Carlotta (Project Staff)
  • Danielson, Charlott (Project Staff)
  • Spitzenberger, Folker (Project Staff)
  • Hackelberg, Niklas (Project Staff)

Project: Projects with Federal FundingFederal Funding: BMFTR (Research, Technology and Space)

Project Details

Description

Intelligent assistance and automation functions in ventilation technology and other areas of medical technology are currently leading to high demand for animal testing, particularly in the large animal sector, as part of preclinical testing of the safety and reliability of medical devices. Preclinical evaluation of such functions using verified and validated digital patient models (in silico trials) offers the potential to significantly reduce the number of animal experiments required.

The aim of the CMS4Vent project is to promote the development of a normative and regulatory framework for the application of computer-based modeling and simulation methods (CM&S) in the preclinical evaluation of medical devices at the European level. The project focuses on the development of a digital patient simulator for conducting in silico trials in ventilation technology, with the aim of replacing animal testing in this area of application as completely as possible. The digital patient simulator for artificial ventilation is intended to serve as a leading example for other areas of medical technology in reducing animal testing.
StatusActive
Effective start/end date01.04.2431.03.27

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Funding Institution

  • Federal Institutions

Research Areas and Centers

  • Centers: Center for Artificial Intelligence Luebeck (ZKIL)

DFG Research Classification Scheme

  • 4.43-04 Artificial Intelligence and Machine Learning Methods
  • 2.22-32 Medical Physics, Biomedical Technology

KDSF Research Field Classification Scheme

  • 073 - Artificial intelligence and big data

ASJC Subject Areas

  • Artificial Intelligence
  • Biomedical Engineering

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