Laboratory of the Future

Chapter 1: The Lab of the Future

• • 1.1 Presentation of the FutureLab.NRW Concept
• • 1.1.1 The Inspiration
• • 1.1.2 The Starting Point
• • 1.1.2.1 Instrumental Analysis for Small Molecule Quantification
• • 1.1.2.2 Effect-based Analysis for Identifying Relevant Compounds of Interest
• • 1.1.3 The Transformation of the Lab: New Concepts for the FutureLab. Nrw
• • 1.1.3.1 Instrumental Analysis for Large Molecule Quantification
• • 1.1.3.2 Direct Coupling of Instrumental and Effect-based Analysis
• • 1.1.3.3 Miniaturization
• • 1.1.3.4 Digitalization
• • 1.2 Presentation of the FutureLab.NRW Software Platform
• • 1.2.1 Introductory Remarks
• • 1.2.2 Overall Specifications
• • 1.2.3 Inclusion of the FAIR Data Principles
• • 1.3 The Center for Life Science Automation (CELISCA) – An Interview with Prof. Dr. Kerstin Thurow from the University of Rostock
• • 1.3.1 Personal Introduction
• • 1.3.2 CELISCA’s Approach to Automation
• • 1.3.3 Mobile Robots in the Lab
• • 1.3.4 The Limits of Automation
• • 1.3.5 The Future of Training

Chapter 2: Electronic Laboratory Notebooks

• • 2.1 Introductory Remarks – FAIR Data and the Reproduction Crisis
• • 2.2 ELN Without LIMS?
• • 2.2.1 A Brief and Not Comprehensive Definition of the Nature of an ELN
• • 2.2.2 Some Important Functionalities of an ELN
• • 2.2.2.1 Introductory Remarks
• • 2.2.2.2 Metadata
• • 2.2.2.3 Accessibility
• • 2.2.2.4 Standardization
• • 2.2.2.5 Data Protection
• • 2.2.2.6 Versioning
• • 2.2.2.7 Data Quality
• • 2.2.2.8 Collaboration
• • 2.2.2.9 Long-term Archiving
• • 2.2.2.10 Data Security
• • 2.2.2.11 Conclusion
• • 2.3 Use-case: Digital Instrument Logs
• • 2.3.1 Introductory Remarks
• • 2.3.2 Implementation
• • 2.4 Chemotion: Developing an Open-source Platform for Data Acquisition and Storage – An Interview with Dr. Patrick Hodapp from the Karlsruhe Institute of Technology
• • 2.4.1 Personal Introduction
• • 2.4.2 Motivation for Developing Chemotion
• • 2.4.3 Meeting the Specific Needs of an Organic Chemistry Laboratory
• • 2.4.4 Overcoming Barriers of Adoption
• • 2.4.5 Improving the Quality and the Output of Publications
• • 2.4.6 Long-term Maintenance of the Platform
• • 2.4.7 Arguments Against Using an ELN
• • 2.5 ELNs Are Dead! Long Live ELNs! – An Interview with Dr. Samantha Pearman-Kanza from the University of Southampton
• • 2.5.1 Personal Introduction
• • 2.5.2 Replacing Paper Notebooks
• • 2.5.3 Choosing an Appropriate ELN
• • 2.5.4 Data Privacy
• • 2.5.5 Continuity of Platform
• • 2.5.6 Further Research on ELNs – Overcoming Current Technical Limitations
• • 2.5.7 Using Advanced AI Tools to Retrieve Valuable Information from the Data Lake

Chapter 3: Digital Transformation, But How?

• • 3.1 Introduction
• • 3.2 Existing Problems Calling for a Digital Solution
• • 3.2.1 Introductory Remarks
• • 3.2.2 Stringent Standards
• • 3.2.3 Manual Documentation
• • 3.2.4 Data Integrity
• • 3.2.5 Reproducibility
• • 3.3 Challenges on the Road to a Digital Transformed Lab
• • 3.3.1 Missing Guidance
• • 3.3.2 Moon-shot Thinking
• • 3.3.3 Legacy Devices
• • 3.3.4 Heterogeneous Device Landscape
• • 3.4 Digitization Versus Digital Transformation
• • 3.5 Existing Approaches for Digitized Laboratory Environment
• • 3.6 Methodical Approach
• • 3.6.1 Introduction
• • 3.6.2 Stakeholder Acquisition
• • 3.6.3 Defining the Objective
• • 3.6.3.1 Introduction
• • 3.6.3.2 Tier One: Explorative Laboratory
• • 3.6.3.3 Tier Two: Remote Controlled Laboratory
• • 3.6.3.4 Tier Three: Semi-automatic Laboratory
• • 3.6.3.5 Tier Four: Automatic Laboratory
• • 3.6.3.6 Tier Five: AI Laboratory
• • 3.6.3.7 Conclusion
• • 3.6.4 Workflow Analysis
• • 3.6.5 Workflow Abstraction
• • 3.6.5.1 Introduction
• • 3.6.5.2 Digitization of Measured Values
• • 3.6.5.3 Automation
• • 3.6.5.4 Process Control Commands
• • 3.6.5.5 Process Control Variables
• • 3.6.6 Gateway and Cybersecurity
• • 3.6.7 Gateway Connector
• • 3.6.8 Choosing the Middleware
• • 3.6.8.1 Introduction
• • 3.6.8.2 Commercial IoT Platform
• • 3.6.8.3 Software Ecosystem
• • 3.6.9 Choosing Network Protocols
• • 3.6.10 Driver Development
• • 3.6.11 IoT Server
• • 3.6.12 Integrating Inter-Process Software
• • 3.6.13 Workflow Implementation
• • 3.6.14 Functional Integration
• • 3.6.14.1 Introduction
• • 3.6.14.2 Hardware Layer
• • 3.6.14.3 Software Layer
• • 3.7 Final Conclusion
• • 3.8 Lessons Learned: An Interview with Dr. Jochen Tuerk, Head of the Cooperation Laboratory of Ruhrverband and Emschergenossenschaft / Lippeverband
• • 3.8.1 Personal Introduction
• • 3.8.2 Moon-shot Thinking
• • 3.8.3 The Role of Digital Natives
• • 3.8.4 Requirements of Guidelines
• • 3.8.5 LIMS, ELN, or LES, That Is the Question
• • 3.9 The Digital Transformation in the Chemical Industry – An interview with Dr. Joachim Richert from Technical University of Darmstadt
• • 3.9.1 Personal Introduction
• • 3.9.2 The Digital Transformation in Industry
• • 3.9.3 Commitment of Users and Vendors to Achieve the Digital Transformation
• • 3.9.4 Core Stakeholders
• • 3.9.5 Shortcomings of Academic Research in Student Education

Chapter 4: Communication Standards

• • 4.1 Introduction to Device Communication
• • 4.2 What Is a Communication Layer?
• • 4.3 SiLA 2 and LADS OPC UA
• • 4.3.1 Origins and Development
• • 4.3.2 Communication Paradigms
• • 4.4 SiLA – An Interview with Daniel Juchli from Wega Informatik AG
• • 4.4.1 Personal Introduction
• • 4.4.2 Plug-and-Play Connectivity
• • 4.4.3 The Status Quo of SiLA
• • 4.4.4 There are Many Standards – So Let’s Try to Harmonize, Using a New Standard
• • 4.4.5 The Chicken and Egg Problem
• • 4.4.6 The Role of Open Source in Lab Automation Standards
• • 4.4.7 The Future of Lab Standardization: Trends and Challenges
• • 4.5 LADS – An Interview with Dr. Matthias Arnold
• • 4.5.1 Personal Introduction
• • 4.5.2 Why Another Standard?
• • 4.5.2.1 “Plug-and-Play Connectivity” – Revisited
• • 4.5.2.2 OPC UA Companion Specifications and “Machine Plug and Play”
• • 4.5.2.3 “Human Versus Machine Plug and Play” – LADS OPC UA Example
• • 4.5.2.4 The Role of Ontologies and Taxonomies – FAIR Data and AI Enablement
• • 4.5.3 The Future Perspective of LADS
• • 4.5.4 Tackling Cybersecurity Challenges
• • 4.5.5 Coexistence of the Two Standards
• • 4.6 Digitalization at Roche – An Interview with Tom Kissling from F. Hoffmann – La Roche Ltd.
• • 4.6.1 Personal Introduction
• • 4.6.2 The Role of Standardization
• • 4.6.3 Money Can Buy Everything, Can’t It?
• • 4.6.4 The Concept of Digital Transformation at Roche
• • 4.6.5 Academic Versus Industrial Research
• • 4.7 Summary from the Perspective of a Device Integrator – A Brief Comment from Julian Luebke, Chief Business Officer at Labforward GmbH

Chapter 5: Data and Data Processing Standards

• • 5.1 Introduction
• • 5.2 Data Standards
• • 5.2.1 Introduction
• • 5.2.2 The Basics of Data Standards
• • 5.2.3 Use Cases for Open Data Standards
• • 5.2.3.1 Introduction
• • 5.2.3.2 Basic Parameters
• • 5.2.3.3 Multidimensional Analytical Data
• • 5.2.4 Software to Read, Write, and Process Open Data Standards
• • 5.3 Data Processing
• • 5.3.1 Introductory Remarks
• • 5.3.2 Data Competences
• • 5.3.3 Vendor Versus Open-source Processing Software
• • 5.3.4 Reproducible Workflows with StreamFind
• • 5.3.5 Automated Use of Results in Broader Smart Laboratory Workflows
• • 5.4 An Overview About Important Data Standards: AnIML, ASM, and ADF – An Interview with Dr. Philip Wenig from Lablicate GmbH
• • 5.4.1 Personal Introduction
• • 5.4.2 Open-Source Versus Proprietary Software
• • 5.4.3 A Brief and General Overview about AnIML, ASM, and ADF
• • 5.4.4 The Future Perspective of Data Standards
• • 5.5 Data Processing with a Focus on Advanced Data Analysis and Quality Assurance – An Interview with Dr. Gerrit Renner from University of Duisburg-Essen
• • 5.5.1 Personal Introduction
• • 5.5.2 Challenges of Data Processing with Vendor Software
• • 5.5.3 Quality Assurance in Vendor and Open-source Software
• • 5.5.4 Transparency in Data Processing
• • 5.5.5 Opportunities from Advances in Data Science

Chapter 6: Smart Digital Workflows

• • 6.1 General Introduction
• • 6.2 Temperature Monitoring
• • 6.2.1 Introduction
• • 6.2.2 First Approach: Off-the-shelf Software
• • 6.2.3 Second Approach: DIY Low Cost
• • 6.2.4 Notifications and Alarms
• • 6.2.5 Conclusion
• • 6.3 Labeling Workflow
• • 6.3.1 Introduction
• • 6.3.2 Implementation
• • 6.3.3 Conclusion
• • 6.4 Stock Solution Workflow
• • 6.4.1 Introduction
• • 6.4.2 Implementation
• • 6.4.2.1 Digital SOP
• • 6.4.2.2 Device Integration and Communication
• • 6.4.2.3 Process Comparison and Efficiency Gains
• • 6.4.3 Conclusion
• • 6.5 Automation and Orchestration of Atline Analysis
• • 6.5.1 Introduction
• • 6.5.2 Implementation
• • 6.5.2.1 Orchestration
• • 6.5.2.2 Dataflow
• • 6.5.2.3 Device Integration
• • 6.5.3 Conclusion
• • 6.6 Inventing the Smartlab – An Interview with Prof. Dr. Sascha Beutel from the Institute of Technical Chemistry at the Leibniz University of Hannover
• • 6.6.1 Personal Introduction
• • 6.6.2 A Look Back at the Beginning of the Digital Transformation
• • 6.6.3 Promoting Interdisciplinary Education of Students
• • 6.6.4 The Transformative Power of Machine Learning and Artificial Intelligence
• • 6.6.5 The Future of Academic Research

Chapter 7: Flexible Automation

• • 7.1 Introduction
• • 7.1.1 History of Laboratory Automation
• • 7.1.2 Market Data
• • 7.1.3 Flexible Laboratory Automation in the Context of FutureLab.NRW
• • 7.2 Automation Components
• • 7.2.1 Collaborative Robots
• • 7.2.2 End Effectors
• • 7.2.2.1 Introduction
• • 7.2.2.2 Handling End Effectors
• • 7.2.2.3 Process Tools
• • 7.2.2.4 Sensors
• • 7.2.2.5 Tool Changer
• • 7.2.3 Cobot Programming
• • 7.2.4 External Instruments
• • 7.2.5 Monitoring Systems
• • 7.2.6 Control Unit
• • 7.3 Considerations for Implementation