bpd
Diagnostics and process analytics on a new level using artificial intelligence
Visit our website for THEYA LED and other Raman devices too: https://www.raman-products.de/en/
Biophotonics Diagnostics offers technologies and services for the rapid identification and classification of substances and microbes.
With our Raman spectroscopy applications you can simplify your daily laboratory routine. Raman spectroscopy makes it possible to investigate material properties, cell structures of microorganisms or (bio)chemical processes quickly and without contact. By combining it with AI-based software, it is possible to evaluate even complex data reliably, quickly and inexpensively. Our machine-learning software and database systems offer you a clear and efficient tool with the highest level of convenience, making analysis in the field of chemical, biochemical and medical diagnostic applications many times easier.
We will be happy to advise you individually or send you access to a demo account.
Raman spectroscopy and AI - for faster and more reliable results
How it works
The solution lies in the combination
"Biophotonics Diagnostics has set itself the goal of developing and marketing innovative solutions for Raman spectroscopy. Demanding Raman spectroscopy applications such as process monitoring or infection diagnostics can be processed more easily and reliably thanks to our products. Artificial intelligence applied to Raman data is an essential key here."
Prof. Dr. Jürgen Popp
Scientific Director Leibniz Institute for Photonic Technology and co-founder of Biophotonics Diagnostics
Great potential for process analysis and medicine
We develop and sell system solutions with which material properties, microorganisms, chemical and biochemical processes can be analysed. For this purpose, we use the advantages of Raman spectroscopy, with which data with high information content can be obtained quickly and without contact. By combining this with AI-based software, an effective tool has been created for a wide range of applications.
With this system, data with high information content can now be obtained contactlessly and efficiently, evaluated more reliably and quickly, and analysis costs can also be reduced. Further advantages for you are:
- No time-consuming sample preparation, such as the creation of cultures
- No special statistical knowledge required
- No additional programming necessary
Products & Projects
Faster Tests for Bacterial Infections Using Urine Samples
Thuringia Consortium RUnfAST: Parallelizable Confocal Raman Sensing for Urine Diagnostics
Runtime: 01.08.2025 - 31.07.2028
In the Thuringia consortium project RUnfAST, Leibniz-IPHT is researching a parallelizable confocal Raman sensing system for urine diagnostics. The goal is to further develop Raman spectroscopic analyses so that multiple samples can be evaluated simultaneously. This is expected to significantly shorten diagnostic processes and make them more easily integrated into clinical workflows. At the core of the work is a new parallelization concept based on a GRIN detection module. This module enables the simultaneous readout of multiple measurement points, thereby reducing the time required for the spectroscopic characterization of bacterial pathogens. The sensor detects changes in the Raman spectra that indicate bacterial responses to antimicrobial substances. The faster availability of this information allows timely assessment of pathogen sensitivity to antibiotics. On this basis, the selection of suitable active agents can be more targeted. The project thus contributes to rational antibiotic therapy and helps avoid unnecessary or ineffective treatments. Another focus is the integration of automated sample preparation. This is intended to ensure that the Raman-based sensing system can be reliably used under clinical conditions, while also creating the foundation for a scalable application in in vitro diagnostics. The project is funded by the Free State of Thuringia under the number 2024 VFE 0093 and co-financed by the European Union through the European Regional Development Fund (ERDF).
