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Cell-based assays
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Microscopy technologies are generating vast quantities of images containing a wealth of data that needs to be extracted and understood in order to support the right scientific decisions.
Automating image analysis for HCA is a common technique used to support this process. However, most solutions fail to extract all the information held within image data. Technologies are often narrow in scope, platform dependent, proprietary and only provide satisfactory result on basic tasks. Additionally, proprietary image data cannot be compared along the drug development cycle, which slows down the industry’s translational medicine aspirations.
In contrast, Definiens software is independent of any specific instrument or process, allows analysis to be conducted on any image data from any image source, and improves data correlation with other drug development stages.
Definiens Cellenger® is designed to simplify and automate assay execution for end users without requiring image analysis and programming skills. All analysis tasks are defined as independent modules such as detection, classification and quantification of cells, nuclei, sub-cellular structures, for example the Golgi apparatus, labeled proteins, and many other objects of interest. Users combine the modules to create the precise analysis process they require.
Definiens Cellenger® is the only truly platform-independent image analysis system designed specifically for high-content assays which also allows cell-based assay data to be combined with data from other systems. In case cell analysis demands extend beyond the routine, Definiens Developer offers the most powerful image analysis development environment available, capable of creating entirely unique routines. |
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Medical imaging
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Medical Imaging is a vital tool in the diagnosis and treatment of patients as well as in the clinical stages of drug development and validation. It is an area challenged by two key factors – the limited number of experts to interpret images and a fairly high level of inconsistency in interpretations. Computer Aided Detection (CAD) systems have helped to address these challenges by pre-examining images and identifying areas of interest, making it possible for the clinical expert to reach an accurate diagnosis much faster.
Definiens Cognition Network Technology® is the only technology that classifies and analyzes imagery using all the semantic information required to interpret objects correctly. It improves the quality and accuracy of image analysis, and supports trained observers to interpret images. Results are not just more accurate but also delivered faster – one study shows that a specialists’ interpretation time was cut by more than 40%.
Definiens also makes precise volumetric measurements of tumors. This is a much more accurate method of measuring the progress of cancer than the standard RECIST measure, a one-dimensional criteria based on the maximum diameter of a tumor or nodule. Volumetric measurements enable researchers to build up an accurate picture of the progression of a tumor and its response to treatment, giving a precise indication of the efficacy of a drug candidate.
Read here about Definiens liver segmentation, lymph nodes, mammography. Click here |
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Tissue-based diagnostic
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The interest in identifying biomarkers in tissue-based studies has created a growing demand for automated solutions to quantify biomarker expression in images. This is very challenging, as many detection systems lack capacity in the most crucial part of the task – the extraction of morphological entities.
Definiens Cognition Network Technology overcomes this challenge by automatically identifying relevant morphological entities with precise and repeatable results. This is fundamental to the significance and quality of the data generated.
Definiens' technology opens new avenues of research enquiry. The flexible and adaptable nature of the technology allows for analysis of various stains or tests of protein expression (IHC, fluorescence, quantum dots) or gene probes (FISH, SISH). Multiplexing enables researches to undertake a variety of tests on the same morphological units – a highly promising area for tissue-based diagnostics. The relationship between different biomarkers can be explored as well as correlated with clinical and/or molecular data, facilitating a far more nuanced understanding of disease progression and personalized treatment.
Click here to read about Definiens biomarker/her2 case |
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Tissue-based drug discovery
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Conventional manual pathology screening processes are labor intensive and costly. The risk of human error in identifying efficacy and toxicity profiles is inevitable given the increasing volumes of data for manual analysis and the shortage of qualified pathologists. Compounding the challenge are increasingly stringent statutory regulations, demanding more accurate and consistent data.
These factors create a bottleneck that slows time to market and heightens risk of late stage candidate failures.
Definiens’ automated digital pathology solutions deliver accurate and consistent results and the scalable platform can handle image analysis tasks of any size, quickly, accurately and consistently.
A processes of image segmentation extracts objects which are classified into hierarchical levels. The resulting network of objects enable a wide range of morphological parameters to be measured and exported, including spectral statistics, shape, size, position, texture and relations to other objects. This approach achieves a previously unattainable depth of analysis in automated digital pathology.
In pre-clinical studies where Definiens’ technology has been deployed, it has contributed to an image analysis cost reduction of as much as 60-90%. And that is without considering the vast savings made where image analysis contributes to the early identification of a failed candidate, averting an unnecessary clinical trial.
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