Fraunhofer Institute for Cell Therapy and Immunology IZICultivation and multimodal analysis of cells and biological material
SniffBot
Development of a fully automated health kiosk for analyzing respiratory diseases using respiratory diagnostics
During the coronavirus pandemic, there has been a growing desire to identify infected individuals quickly in order to reduce further transmission. This requires fast and cost-effective tests that can be used for mass screening, e.g., at the entrances to hospitals, nursing homes, or pharmacies. SniffBot's goal is to develop a technical and fully automated solution for this purpose. We rely on the analysis of volatile organic compounds (VOCs) in exhaled air. These are analyzed within 2–4 minutes using ion mobility spectrometry (IMS). This IMS method makes it possible to distinguish between bacterial and viral pathogens or to determine the exact virus type. The project focuses on the development of an automated communication and sampling tool on the one hand and automated data evaluation on the other. Upon completion of the project, a fully automated health kiosk will be available where all steps are performed autonomously and automatically, i.e., no operating personnel are required.
Partners
United Robitics Group GmbH; Dr. med. Thomas Lipp, Praxis Dres. Lipp & Amm; + another industry partner
Duration
05/2024 – 04/2026
BreathAlert
Detection of antibiotic-resistant bacteria using ion mobility spectrometry
In a report, the World Health Organization emphatically describes why the fight against antibiotic resistance is one of the major tasks faced by the global community. By the year 2050, the organization expects 10 million deaths annually that will be attributable to infectious agents [1]. Innovations are necessary not only for therapeutic treatment, but also for the diagnostic detection of pathogens that cause disease to counteract the challenge in the healthcare sector.
The BreathAlert project launched at the end of 2020 aims at improving this situation with a new method for the rapid and non-invasive detection of infectious agents and antibiotic resistance, which analytically analyzes patients’ breath. The project focuses on the further development of ion mobility spectrometry, which is to be used to characterize volatile organic components (VOCs) of microorganisms.
At the Fraunhofer IZI, selected microorganisms are being examined to determine whether they can be differentiated via the VOCs released and whether they can be assigned to the respective types of bacteria. For this purpose, the pathogens are first cultivated and then the headspace, the gas phase above the culture medium, is fed into the device. The VOCs are ionized, separated in an electric field and then detected at different times. Software analyzes the complex data. The aim is to identify specific signals with which bacteria can be reliably differentiated from one another, even under different conditions. The focus is on antibiotic-resistant pathogens, such as enterobacteria, which are increasingly showing resistance to carbapenem and cephalosporin [1].
The characterization of clinical isolates, air samples from infected patients and measurements of the influence of e.g. eating habits on the air we breathe round off the project.
The company Graupner medical solutions GmbH, which develops the medical device technology, works together with the Fraunhofer IZI as a consortium partner. The development work is supported by specialist clinics that provide access to samples and also carry out a final validation. The project results are used economically by the Graupner company.
1] World Health Organization Report 2017: Prioritization of Pathogens to guide discovery, research and development of new antibiotics for drug-resistant bacterial infections, including tuberculosis. WHO/EMP/IAU/2017.12
Duration
12/2020 – 11/2023
M3Infekt
Probandentest zur Atemluftanalyse.
Non-invasive diagnostics by breath analysis
Exhaled air contains substances known as volatile organic compounds (VOCs), which provide information about metabolism. In a variety of diseases, including infections, cancer and neurodegenerative diseases, the metabolism and thus the composition of the exhaled VOCs changes. Detection of these VOCs offers the opportunity to diagnose diseases early and non-invasively.
Ion mobility spectrometry (IMS) can detect VOCs within minutes directly at the point-of-care. The BMBF project ”Breath Alert” investigates whether IMS can be used to detect antibiotic resistance in bacteria. In the Fraunhofer-versus-Corona cluster project ”M3Infekt”, IMS technology was further developed at the Fraunhofer Center Erfurt FZE with the participation of Fraunhofer IZI. Specifically, methods for sampling via mouth and nose, for short-term sample preservation and for sample preparation were established and tested. At the end of the project, the method was tested on 60 healthy volunteers in two clinical studies in Dresden and Magdeburg. In parallel, a functional novel IMS demonstrator was completed at Fraunhofer FZE. This must now be further developed and optimized in follow-up projects to selectively detect diagnostics-relevant VOCs in complex matrices such as exhaled breath.
In the M3Infekt project, the participating nine Fraunhofer Institutes developed further non-invasive and mobile sensors for recording heart rate, ECG, oxygen saturation, respiratory rate and respiratory volume. Concepts for system integration and flexible interfaces were defined and a multimodal AI framework for cross-sensor data evaluation was developed. In addition, requirements regarding conformity to medical regulatory requirements were developed. The overall vision of the project is a close monitoring of relevant clinical parameters for detecting condition deterioration in infectious diseases also outside of intensive care units via a multimodal, modular and mobile sensor system. During the project it has become apparent that several specific solutions for different sub-applications are more useful than a single overall system and thus the benefit of the project results is even increased.
Duration
09/2020 – 09/2021