QuoData Quality & Statistics is a medium-sized company based in Berlin and Dresden and active in the areas of statistics and analytical quality assurance. Drawing on state-of-the-art statistical methods, we develop software products and provides services for a host of international clientele.
Quality assurance concerns the reliability of your
- production process
- measurement method/instrument
In other words, quality assurance is essential for you to obtain and maintain your customers' trust.
Statistical methods play a central role in all questions relating to quality assurance. Our expertise in the application of these methods translates to greater efficiency, hence to reduced costs - which is what you're interested in.
QuoData is constantly broadening its expertise and business portfolio. Close collaboration with leading scientific institutions guarantees that its methods and procedures are always up-to-date.
QuoData is committed to the highest professional standards in all its activities. The continuous growth of its clientele over and beyond European borders vouches for its success.
QuoData is your competent partner and consultant on matters relating to
- quality assurance and the optimization of measurement methods
- statistical modelling
- software development
- interlaboratory tests
- development of bioassays
Our competence in each of these core areas is underpinned by our expertise in the application of statistical methods and our extensive experience in cooperation with scientific institutions and other partners/customers.
QuoData - We Let Your Data Speak
An open-source tool for video analysis of iPSC-CMs.
There's a tremendous growth noticed in the studies of induced pluripotent stem-cells derived cardiomyocytes (iPSC-CMs). Biomedical image & signal processing techniques are increasingly used in the analysis of stem cell studies, regenerative & therapeutic medicines, organ-on-chip studies, etc.
A paper with contributions of QuoData’s scientists is now published on the Journal of Veterinary Diagnostic Investigation. The paper describes an interlaboratory comparison (ILC), which was performed in collaboration of several institutions (including QuoData), to help the laboratories evaluate their SARS-CoV2 test methods.
SmartGrape - AI-based MIR measuring system for determining quality in viticulture
A new paper in Forensic Chemistry (Vol. 23, Elsevier) describes a study on Gunshot Residue that was sponsored by the European Union. GSR particles in various populations were compared on the basis of carbon stub samples from 1300 individuals.
Non-targeted approaches are being increasingly developed and adopted to detect food fraud. Thorough method validation is critical before using non-targeted methods routinely, to be assured of their performance.
A lack of well-structured and harmonized validation strategies has been one of the hurdles, withholding the broader adaptation of non-targeted methods. A novel paper aims to describe a validation framework for methods that involve binary classification, which are prevalent in non-targeted workflows.
"Estrogenic Effects" is the first EQA scheme in the new QuoData external quality assurance program for in vitro methods for effect-based analysis.
Data-Science and the laboratory of the future
QuoData Web-Seminars 2021: Quality assurance in food microbiology, evaluation of proficiency tests and in-house validation
The popular QuoData web-seminars will take place again in 2021. The events, in which participation will only be possible online, deal with various topics of quality assurance. The web-seminars will focus in particular on:
Quality assurance in food microbiology
Validation, verification and determination of measurement uncertainty for Microbiologists -a QuoData webinar series providing expert knowledge for analytical quality assurance.
In recent years, a number of norms and standards have been developed to define approaches and procedures for quality assurance of microbiological test methods.
In their ongoing work, QuoData's scientists are pleased to share some of the recent developments in their latest paper - "AI-based identification of grain cultivars via non-target mass spectrometry". The paper deals with the use of non-target high-resolution mass spectrometry and the processing of the extensive data using artificial intelligence approaches.