Overview: Digital Transformation Forum
At Analytica 2020, we were invited to participate in a number of virtual workshops to showcase how BSSN Software can interoperate with other technologies in the lab to deliver more efficient, automated processes.
This virtual workshop focuses on holistic data integration and Internet of Things (IoT) connected lab technologies including the Olympus ScanR high-content imaging system, Essentim Scope sensors, and our BSSN Hub software. The video transcript is presented in full below.
Optical Analysis: Olympus, Essentim, and BSSN Software
Welcome to the “Optical Analysis” webinar of the Digital Transformation Forum at Analytica Virtual. In the next few minutes, we will present a possible integrated workflow of a live cell analysis and how this generates significant added value for the user based on the digital solutions of the workstation partners Olympus, Essentim, and Merck KGaA, Darmstadt, Germany.
I would like to briefly explain the structure of our workstation, dive into today’s challenges with this application, and then present our solutions for working with living cells.
The linchpin of our optical analysis is the Olympus ScanR—a high-content imaging system that, thanks to the latest addition of artificial intelligence, enables undreamt-of analyses for both living cells and other samples.
The SCOPE SENSOR from our partner ESSENTIM monitors the sample handling process across all relevant stations. It records ambient parameters such as temperature, humidity, air pressure, movement, and brightness with direct reference to the sample. Starting with the initial sample preparation through various protocol and analysis steps, everything is transparently documented.
BSSN Software, now part of Merck KGaA, Darmstadt, Germany since 2019, provides a cloud-based, open integration layer for all types of analytical and biological laboratory data with the Sea Star Lab Information Hub [BSSN Hub].
By using the open AnIML data format, analytical data can be made accessible from laboratory devices from a wide variety of manufacturers and are therefore available for the various processes along the entire data processing pipeline.
As a holistic data management system, the BSSN Hub maps the entire process chain according to FAIR data principles and supports approaches of extended data analysis as well as artificial intelligence and machine learning.
Cell culture experiments require special care in handling. Slight fluctuations in relevant process parameters such as temperature, humidity, or even exposure to light can have a negative effect on the reproducibility of the analysis during the incubation process.
In order to precisely assess the captured analytical results, it is therefore important to know the relevant cross-influences during the sample handling process. So far, however, this information is often missing. At the same time, users should not be overwhelmed by a flood of information.
The required access to several different data sources and systems leads to an unnecessary increase in complexity. We address precisely this information gap in the integrated workflow of our workstation.
We use the ScanR system from Olympus as a typical source for image data and enhance this with AI-supported image analysis.
The Essentim Scope sensor provides additional environmental parameters for monitoring and evaluating the sample handling directly from the multiwell microtiterplate.
The data collected in this way are merged into a holistic data set in the BSSN Hub and can be easily visualized. This integration of the source data via a uniform interface means that all data relevant to the user can be easily accessed and are available in a central dashboard. The user can concentrate on the essentials and the data management happens automatically in the background.
The data from both sources are matched via a uniform sample ID and stored in AnIML format in the data lake of the BSSN Hub. The ScanR is connected directly to the Hub by means of an instrument connector.
The Essentim backend automatically downloads the corresponding AnIML file for the relevant sample from the hub and updates it with the recorded sensor data. The Hub’s metadata store extracts relevant data from the data lake. This data is then available for further processing steps or can be viewed by the user via the user interface.
The data structure and the abstraction of the data were chosen in such a way that it is compatible with the other workstations and are available centrally and easily in an agile laboratory environment. The entire system can then be scaled accordingly and connected and integrated via the standardized interface.
I would like to thank you very much for your interest and if you need more information about our workstation or the partners, please do not hesitate to contact us. Until then, stay safe and goodbye!