Tailored Bio-image Analysis Software

Due to significant developments in microscopy automation in recent years, large amounts of high-quality images are now efficiently being collected by the pharmaceutical industry for research purposes. However, analyzing these images to extract meaningful insights has become the research bottle-neck. A large portion of these images is not analyzed and not used for insights into the process of pharmaceuticals development.
Quantified Biology, Inc. develops custom-made biological image analysis solutions for R&D units in pharmaceutical companies and academic research groups who perform image-based experimentation for drug discovery. Quantified Biology’s software solutions save time and improve decision-making by quickly processing thousands of images while performing a non-biased, deep analysis. Unlike generic image analysis tools, Quantified Biology`s solutions address the specific research question at hand. With Quantified Biology`s software researchers can easily scale-up their research programs.
Quantified Biology has four patents pending for developed software:
Automatic quantification of myelination levels in oligodendrocyte cells
Automatic quantification of microglia activation in relation to amyloid-beta plaques
Automatic region detection in tissue sections
Automatic quantification of cell migration in phase microscopy
Quantified Biology has four ongoing software agreements with the multinational pharma giant Roche. (F. Hoffmann-La Roche AG)
We develop the first draft of the algorithm to you within one or two weeks free of charge, thereafter you can evaluate it and decide whether to proceed with the software development or not.
Development time of a fully functional, dedicated analysis software is between one and two months. At the end of this time period you receive a custom-made software as a desktop or web-deployed application, as per your preference.
We`re developing software for different types of optical microscopy (fluorescent and non-fluorescent).
Our algorithms mimic what the human eye does when a researcher analyzes an image.
This approach does not require large annotated databases on which to train a model. These types of databases typically do not exist for discovery research.
Our validation process is straightforward and fast – we compare our algorithm with human analysis on a fraction of the data.
Our previous software achieved more than 95% agreement with human scoring. This allows a short development time to a validated, accurate solution.
Contact us for more details so we could start preparing your draft algorithm.