IVD software integrated with ATR-FTIR spectrometer

Windows Desktop Application in C#, .NET Framework, WPF, MVVM architecture, SQLite

Alifax S.r.l. specializes in development, production and distribution of clinical diagnostic instrumentation for laboratory automation. They are innovating in the field of automated microbial identification, using a novel approach with the I•dOne® next generation microorganism identification software.

I∙dOne analyses the spectrum produced by the interaction between intact microbial cells and IR light through the vibrational state of their chemical bonds. The software is an IVD registered product.

Download the full case study about IVD software development

Are you curious about the complete approach to IVD software development, integrated with ATR-FTIR?

Download the case study and learn how we defined the four key stages of the project, and successfully automated the spectra acquisition process.

Download the case study

BioSistemika developed the software for I•dOne® next generation microorganism identification instrument and integrated Alifax‘s software algorithm that can identify a vast amount of microorganisms in 1 minute.

Each species produces a unique fingerprint-like ATR-FTIR (fourier-transform infrared spectroscopy) spectrum. Results are reported as Microorganism ID along with relative matching score that represents the reliability of the identification to known vibrational profiles of species present in the reference database.

The IVD software was developed according to IEC 62304 standards to meet IVD 98/79/CE Directive.

Software screens

I•dOne® software is a Windows desktop application developed in C#/.NET that interfaces with the third party manufacturer ATR-FTIR spectrometer via USB connection. The integration is using the instrument API in conjunction with an off-the-shelf ATR-FTIR spectrometer. Data of the application is stored within an SQLite database.

The application manages the entire spectra acquisition and minimal user intervention is needed. It performs data processing and classifies the data through a machine learning algorithm. The results are then visualized via graphical user interface.

The software also manages data connections to a LIMS system to import sample data and export results.