Processing and visualization of imaging- and analytical data for optimized result evaluation in high-content-cell-analysis with deep-learning. Clever measuring tech-nique- and vendor-independent data handling.
Data is the raw material of the 21st century. As a basis for the algorithms of artificial intelligence, however, its value-creating potential is still used far too little, especially in the process analysis in laboratories. Olympus, BSSN Software and essentim are using a cytotoxicity test to demonstrate how the morphology of cell cultures can be visualised with the help of self-learning microscopy employed in Olympus' fully automated high content screening (HCS) system scanR.
Morphological or digital imaging as well as chemical or physical data are automatically recorded, linked with atmospheric measurement data – such as incubation temperature and light intensity, which are determined by the sensor units of the essentim scopes—and clearly displayed on a dashboard. This creates completely new conditions for modern life science research. Images alone are always only selective snapshots and often lack a basic protocol description as well as the valuable overall context. Especially in live cell analysis, a well-founded workflow analysis and monitoring as well as a complete documentation—based on a comprehensive database—are of decisive importance for every laboratory and especially for pharmaceutical development processes and contract research.
The system shown here provides researchers with a unique cross-supplier and cross-system solution for complete documentation and optimal process analysis of their experiments.
In a short, one-time training phase, the software of the HCS system scanR uses a series of quickly acquired images to generate reference data for the learning process without any manual annotations. On this basis, Deep Learning is used to autonomously create robust algorithms that can analyse large image series within a very short time. Using the AnIML data format, the Seahorse Scientific Workbench from BSSN Software then combines the image and analysis data from the Olympus ScanR and the sensor data from the essentim scopes—the sensor units for individual sample monitoring—to create a valuable overview on a modern dashboard.
Experience on the Hands-on Island how data from different sources can be combined with each other in a standardised data set and be presented in a user-optimised visualisation. Also, how complex processes can be documented, analysed and archived more efficiently, safely and easily.
Olympus’ newly launched scanR 3.1 high-content screening (HCS) station fully embraces the capabilities of artificial intelligence (AI) to enable next generation's life science research. It combines the modularity and flexibility of a microscope-based setup with the automation, speed, throughput and reproducibility of HCS applications. Using the ‘self-learning microscopy’ concept, scanR 3.1 makes it easy to gather data quickly from large live cell populations for reliable, well-supported experimental results.
Spectroquant® Prove 300 is an incredibly robust UV/VIS spectrophotometer, optimized for sensitive measurements such as the analysis of drinking water and beverages. Programmed for over 180 reagent tests and free methods, capable of both UV and VIS measurements, and equipped with a long-lasting xenon lamp, Prove 300 is the ideal tool for rapid, reliable results.
Sea Star Lab Information Hub is an open integration layer for all your analytical and biological laboratory data. It combines a massively scalable file store and a comprehensive meta data repository. Now you can surface and navigate cross-functional R&D and production data in FAIR and accessible formats. The AnIML data format unifies data across vendors and techniques - beautifully presented by Sea Star on the web, desktop and mobile. Sea Star runs in the cloud and scales from small labs to the enterprise.
essentim provides a wireless sensor system to monitor biological processes directly at the culture vessel without interfering with the established workflow. Thereby an uninterrupted real-time monitoring of relevant climatic parameters is enabled and allows immediate failure detection. Furthermore, operating procedures are recognized and automatically documented along with the trial specific measurements.