This book reviews the advances in data gathering and processing in the biotech laboratory environment, and it sheds new lights on the various aspects that are necessary for the implementation of intelligent laboratory architecture and infrastructure. Smart technologies are increasingly dominating our everyday lives and have become an indispensable part of the industrial environment. The laboratory environment, which has long been rather conservative, has also set out to adapt smart technologies with regards to Industry 4.0 and the Internet of Things (IoT) for the laboratory. Due to the heterogeneity of the existing infrastructure and the often complex work processes, standardization is slow, e.g. to implement device interfaces or standardized driver protocols, which are urgently needed to generate standardized data streams that would be immanent for post-processing of data.

Divided into 9 chapters, this book offers an authoritative overview of the diverse aspects in the generation and recording of uniform data sets in the laboratory, and in the processing of the data and enabling seamless processing towards machine learning and artificial intelligence. In the first part of the book, readers will find more about high throughout systems, automation, robotics, and the evolution of technology in the laboratory. The second part of the book is devoted to standardization in lab automation, in which readers will learn more about some regulatory aspects, the SiLA2 standards, the OPC LADS (Laboratory and Analytical Device Standard), and FAIR Data infrastructure

Reviews the latest smart technologies in the biolab Addresses intelligent laboratory architecture and infrastructure Discusses standardization in lab automation

Autorentext

Sascha Beutel is Group Leader at the Institute of Technical Chemistry and Head of the Central Unit for Dangerous Goods and Waste at the Leibniz University of Hannover (LUH), Germany. His research activities are mostly focused on biotechnological topics, e.g. bioprocess engineering for prokaryotic cultivations, downstream processing, bioanalytics and sensor developments. One further area of interest is the digitalization of laboratory infrastructure, ranging from basic integration of lab devices to interaction means for the collaboration of the operator with the system. He has authored +100 peer-reviewed research articles, book chapters and patents. Since 2021 he is supernumerary Professor for Technical Chemistry at the LUH.

Felix Lenk leads the research group SmartLab Systems at the Dresden University of Technology (TUD), Germany, and holds a Ph.D. in Bioprocess Engineering from the same university. His research focuses on the next generation of sensor systems (NGS), the Computer Vision for biological samples, laboratory automation around the culture dish, as well as technology for the Lab of the Future. Until 2009, he studied automation and control at the TUD, Germany, and the University of Calgary, Canada. From 2009 to 2010, he joined the plant automation industry. He has authored several peer-reviewed publications as well as two book chapters and holds numerous patents. In 2017 he has been recognized with the Bionection Transfer Trophy. Dr. Felix Lenk represents the TUD at the Society for Laboratory Automation & Screening (SLAS), and at the Society for Standardization in Laboratory Automation (SiLA).

Inhalt
Data gathering part.- Automation for Life Science Laboratories.- Evolution of Artificial Intelligence-Powered Technologies.- A Comprehensive IT Infrastructure for an Enzymatic Product Development in a Digitalized Biotechnological Laboratory.- HumanDevice Interaction in the Life Science Laboratory.- Flexible Digitization of Highly Individualized WorkflowsDemonstrated Through the Quality Control of Patient-SpecificCytostatic Application Bags: Digitization from the Perspectiveof Small and Medium-Sized Laboratories.- Data processing part.- Standards comparison.- Comparison of Laboratory Standards.- SiLA 2: The Next Generation Lab Automation Standard.- Laboratory and Analytical Device Standard (LADS): A Communication Standard Based on OPC UA for Networked Laboratories.- FAIR Data infrastructure.