Oak Brook, IL — As the need for hard-to-measure chemical and biological compound-oriented identification is on the rise, the demand for more accurate measurement tools is greatly increasing. November’s SLAS Technology Auto-Commentary, “On the Way to Efficient Analytical Measurements: The Future of Robot-Based Measurements,” highlights potentially suitable replacement measurement systems and processes as outlined in the book, Automation Solutions for Analytical Measurements: Concepts and Applications.
SLAS Technology auto-commentary authors Heidi Fleischer, Ph.D., (Institute of Automation at the University of Rostock, Germany) and Kerstin Thurow, Ph.D., (Center for Life Science Automation at the University of Rostock, Germany) discuss in more detail the challenges of gathering analytical measurements through the tried and true high-throughput and high-content screening systems of the past along with their potential replacements. Because process-measurement technology needs have expanded to the fields of environmental engineering, biotechnology and medicine, certain hard-to-measure samples like high pressures, temperatures and highly corrosive reagents make it very difficult to gather quality readings using more-standardized measuring tools.
Enter realized-based measurement systems. These systems use robots as central system integrators allowing for a centralized and closed automation system; in the book, they are tested against and with both centralized open and decentralized systems. “Using mobile robots as transportation elements, this system can be extended to a decentralized open system performing a multitude of different applications and thus providing much more flexibility,” Fleischer and Thurow explain. “The highest degree of flexibility and the ability to expand can be achieved with integrated robotics using mobile robots that not only execute transportation tasks but also are used for direct sample manipulation on different locally distributed automation stations.”
In addition, the authors discuss software systems as the highest-level workflow control, sample transportation using mobile robots, automated subsystems and measurement stations.
Fleischer and Thurow conclude that the concept of using integrated robots is promising, but that there are still underlying challenges to overcome before these processes reach the fully automated stage.
Read more about their study in an SLAS Technology Auto-Commentary at journals.sagepub.com/doi/full/10.1177/2472630319886270 through January 19. For more information about SLAS and its journals, visit www.slas.org/journals.
SLAS (Society for Laboratory Automation and Screening) is an international community of 16,000 professionals and students dedicated to life sciences discovery and technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.
SLAS Technology: 2018 Impact Factor 2.048. Editor-in-Chief Edward Kai-Hua Chow, Ph.D., National University of Singapore (Singapore). SLAS Technology (Translating Life Sciences Innovation) was previously published (1996-2016) as the Journal of Laboratory Automation (JALA).
SLAS Discovery: 2018 Impact Factor 2.192. Editor-in-Chief Robert M. Campbell, Ph.D., Eli Lilly and Company, Indianapolis, IN (USA). SLAS Discovery (Advancing Life Sciences R&D) was previously published (1996-2016) as the Journal of Biomolecular Screening (JBS).
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