Laboratory of the Future

Thorsten Teutenberg, PhD, is the head of the Research Analytics & Miniaturization Department at the Institut für Umwelt & Energie, Technik & Analytik e. V. (IUTA). His scientific work focuses on the development of novel detection and coupling systems based on liquid chromatography, mass spectrometry and vibrational spectroscopy. He is also involved in the establishment of a fully digitalized laboratory of the future (FutureLab NRW).

• List of Contributors xiiiForeword – December 2024 xv1 The Lab of the Future 11.1 Presentation of the FutureLab.NRW Concept 11.1.1 The Inspiration 11.1.2 The Starting Point 11.1.2.1 Instrumental Analysis for Small Molecule Quantification 11.1.2.2 Effect-based Analysis for Identifying Relevant Compounds of Interest 31.1.3 The Transformation of the Lab: New Concepts for the FutureLab. Nrw 41.1.3.1 Instrumental Analysis for Large Molecule Quantification 41.1.3.2 Direct Coupling of Instrumental and Effect-based Analysis 51.1.3.3 Miniaturization 51.1.3.4 Digitalization 51.2 Presentation of the FutureLab.NRW Software Platform 61.2.1 Introductory Remarks 61.2.2 Overall Specifications 71.2.3 Inclusion of the FAIR Data Principles 81.3 The Center for Life Science Automation (CELISCA) – An Interview with Prof. Dr. Kerstin Thurow from the University of Rostock 81.3.1 Personal Introduction 81.3.2 CELISCA’s Approach to Automation 91.3.3 Mobile Robots in the Lab 101.3.4 The Limits of Automation 121.3.5 The Future of Training 132 Electronic Laboratory Notebooks 172.1 Introductory Remarks – FAIR Data and the Reproduction Crisis 172.2 ELN Without LIMS? 172.2.1 A Brief and Not Comprehensive Definition of the Nature of an ELN 172.2.2 Some Important Functionalities of an ELN 192.2.2.1 Introductory Remarks 192.2.2.2 Metadata 192.2.2.3 Accessibility 192.2.2.4 Standardization 202.2.2.5 Data Protection 202.2.2.6 Versioning 202.2.2.7 Data Quality 212.2.2.8 Collaboration 212.2.2.9 Long-term Archiving 212.2.2.10 Data Security 212.2.2.11 Conclusion 222.3 Use-case: Digital Instrument Logs 222.3.1 Introductory Remarks 222.3.2 Implementation 222.4 Chemotion: Developing an Open-source Platform for Data Acquisition and Storage – An Interview with Dr. Patrick Hodapp from the Karlsruhe Institute of Technology 242.4.1 Personal Introduction 242.4.2 Motivation for Developing Chemotion 252.4.3 Meeting the Specific Needs of an Organic Chemistry Laboratory 262.4.4 Overcoming Barriers of Adoption 262.4.5 Improving the Quality and the Output of Publications 262.4.6 Long-term Maintenance of the Platform 272.4.7 Arguments Against Using an ELN 272.5 ELNs Are Dead! Long Live ELNs! – An Interview with Dr. Samantha Pearman-Kanza from the University of Southampton 282.5.1 Personal Introduction 282.5.2 Replacing Paper Notebooks 292.5.3 Choosing an Appropriate ELN 302.5.4 Data Privacy 312.5.5 Continuity of Platform 322.5.6 Further Research on ELNs – Overcoming Current Technical Limitations 322.5.7 Using Advanced AI Tools to Retrieve Valuable Information from the Data Lake 333 Digital Transformation, But How? 353.1 Introduction 353.2 Existing Problems Calling for a Digital Solution 363.2.1 Introductory Remarks 363.2.2 Stringent Standards 363.2.3 Manual Documentation 363.2.4 Data Integrity 373.2.5 Reproducibility 373.3 Challenges on the Road to a Digital Transformed Lab 383.3.1 Missing Guidance 383.3.2 Moon-shot Thinking 393.3.3 Legacy Devices 393.3.4 Heterogeneous Device Landscape 403.4 Digitization Versus Digital Transformation 413.5 Existing Approaches for Digitized Laboratory Environment 423.6 Methodical Approach 443.6.1 Introduction 443.6.2 Stakeholder Acquisition 443.6.3 Defining the Objective 463.6.3.1 Introduction 463.6.3.2 Tier One: Explorative Laboratory 463.6.3.3 Tier Two: Remote Controlled Laboratory 473.6.3.4 Tier Three: Semi-automatic Laboratory 473.6.3.5 Tier Four: Automatic Laboratory 473.6.3.6 Tier Five: AI Laboratory 473.6.3.7 Conclusion 473.6.4 Workflow Analysis 483.6.5 Workflow Abstraction 513.6.5.1 Introduction 513.6.5.2 Digitization of Measured Values 513.6.5.3 Automation 523.6.5.4 Process Control Commands 523.6.5.5 Process Control Variables 533.6.6 Gateway and Cybersecurity 533.6.7 Gateway Connector 543.6.8 Choosing the Middleware 553.6.8.1 Introduction 553.6.8.2 Commercial IoT Platform 553.6.8.3 Software Ecosystem 563.6.9 Choosing Network Protocols 573.6.10 Driver Development 583.6.11 IoT Server 593.6.12 Integrating Inter-Process Software 593.6.13 Workflow Implementation 593.6.14 Functional Integration 603.6.14.1 Introduction 603.6.14.2 Hardware Layer 603.6.14.3 Software Layer 613.7 Final Conclusion 613.8 Lessons Learned: An Interview with Dr. Jochen Tuerk, Head of the Cooperation Laboratory of Ruhrverband and Emschergenossenschaft / Lippeverband 623.8.1 Personal Introduction 623.8.2 Moon-shot Thinking 623.8.3 The Role of Digital Natives 643.8.4 Requirements of Guidelines 653.8.5 LIMS, ELN, or LES, That Is the Question 663.9 The Digital Transformation in the Chemical Industry – An interview with Dr. Joachim Richert from Technical University of Darmstadt 663.9.1 Personal Introduction 663.9.2 The Digital Transformation in Industry 673.9.3 Commitment of Users and Vendors to Achieve the Digital Transformation 683.9.4 Core Stakeholders 703.9.5 Shortcomings of Academic Research in Student Education 704 Communication Standards 774.1 Introduction to Device Communication 774.2 What Is a Communication Layer? 784.3 SiLA 2 and LADS OPC UA 794.3.1 Origins and Development 794.3.2 Communication Paradigms 794.4 SiLA – An Interview with Daniel Juchli from Wega Informatik AG 814.4.1 Personal Introduction 814.4.2 Plug-and-Play Connectivity 814.4.3 The Status Quo of SiLA 824.4.4 There are Many Standards – So Let’s Try to Harmonize, Using a New Standard 824.4.5 The Chicken and Egg Problem 834.4.6 The Role of Open Source in Lab Automation Standards 834.4.7 The Future of Lab Standardization: Trends and Challenges 834.5 LADS – An Interview with Dr. Matthias Arnold 844.5.1 Personal Introduction 844.5.2 Why Another Standard? 854.5.2.1 “Plug-and-Play Connectivity” – Revisited 854.5.2.2 OPC UA Companion Specifications and “Machine Plug and Play” 864.5.2.3 “Human Versus Machine Plug and Play” – LADS OPC UA Example 874.5.2.4 The Role of Ontologies and Taxonomies – FAIR Data and AI Enablement 874.5.3 The Future Perspective of LADS 884.5.4 Tackling Cybersecurity Challenges 894.5.5 Coexistence of the Two Standards 904.6 Digitalization at Roche – An Interview with Tom Kissling from F. Hoffmann – La Roche Ltd. 914.6.1 Personal Introduction 914.6.2 The Role of Standardization 914.6.3 Money Can Buy Everything, Can’t It? 914.6.4 The Concept of Digital Transformation at Roche 924.6.5 Academic Versus Industrial Research 924.7 Summary from the Perspective of a Device Integrator – A Brief Comment from Julian Luebke, Chief Business Officer at Labforward GmbH 925 Data and Data Processing Standards 955.1 Introduction 955.2 Data Standards 955.2.1 Introduction 955.2.2 The Basics of Data Standards 975.2.3 Use Cases for Open Data Standards 995.2.3.1 Introduction 995.2.3.2 Basic Parameters 995.2.3.3 Multidimensional Analytical Data 1015.2.4 Software to Read, Write, and Process Open Data Standards 1015.3 Data Processing 1025.3.1 Introductory Remarks 1025.3.2 Data Competences 1055.3.3 Vendor Versus Open-source Processing Software 1065.3.4 Reproducible Workflows with StreamFind 1085.3.5 Automated Use of Results in Broader Smart Laboratory Workflows 1095.4 An Overview About Important Data Standards: AnIML, ASM, and ADF – An Interview with Dr. Philip Wenig from Lablicate GmbH 1115.4.1 Personal Introduction 1115.4.2 Open-Source Versus Proprietary Software 1125.4.3 A Brief and General Overview about AnIML, ASM, and ADF 1125.4.4 The Future Perspective of Data Standards 1135.5 Data Processing with a Focus on Advanced Data Analysis and Quality Assurance – An Interview with Dr. Gerrit Renner from University of Duisburg-Essen 1145.5.1 Personal Introduction 1145.5.2 Challenges of Data Processing with Vendor Software 1155.5.3 Quality Assurance in Vendor and Open-source Software 1165.5.4 Transparency in Data Processing 1175.5.5 Opportunities from Advances in Data Science 1186 Smart Digital Workflows 1216.1 General Introduction 1216.2 Temperature Monitoring 1226.2.1 Introduction 1226.2.2 First Approach: Off-the-shelf Software 1246.2.3 Second Approach: DIY Low Cost 1256.2.4 Notifications and Alarms 1266.2.5 Conclusion 1276.3 Labeling Workflow 1276.3.1 Introduction 1276.3.2 Implementation 1286.3.3 Conclusion 1296.4 Stock Solution Workflow 1296.4.1 Introduction 1296.4.2 Implementation 1306.4.2.1 Digital SOP 1306.4.2.2 Device Integration and Communication 1316.4.2.3 Process Comparison and Efficiency Gains 1326.4.3 Conclusion 1336.5 Automation and Orchestration of Atline Analysis 1336.5.1 Introduction 1336.5.2 Implementation 1346.5.2.1 Orchestration 1346.5.2.2 Dataflow 1356.5.2.3 Device Integration 1366.5.3 Conclusion 1376.6 Inventing the Smartlab – An Interview with Prof. Dr. Sascha Beutel from the Institute of Technical Chemistry at the Leibniz University of Hannover 1386.6.1 Personal Introduction 1386.6.2 A Look Back at the Beginning of the Digital Transformation 1396.6.3 Promoting Interdisciplinary Education of Students 1406.6.4 The Transformative Power of Machine Learning and Artificial Intelligence 1416.6.5 The Future of Academic Research 1427 Flexible Automation 1457.1 Introduction 1457.1.1 History of Laboratory Automation 1457.1.2 Market Data 1477.1.3 Flexible Laboratory Automation in the Context of FutureLab.NRW 1477.2 Automation Components 1487.2.1 Collaborative Robots 1487.2.2 End Effectors 1517.2.2.1 Introduction 1517.2.2.2 Handling End Effectors 1527.2.2.3 Process Tools 1547.2.2.4 Sensors 1547.2.2.5 Tool Changer 1557.2.3 Cobot Programming 1567.2.4 External Instruments 1587.2.5 Monitoring Systems 1607.2.6 Control Unit 1617.3 Considerations for Implementation 1637.3.1 Introduction 1637.3.2 Notes on Installation 1637.3.3 Practical Experiences 1647.3.4 Safety Considerations 1677.4 Outlook 1687.5 Lab Automation in the Chemical Industry – An Interview with Dr. Marcel Vranceanu from BASF 1687.5.1 Personal Introduction 1687.5.2 Industrial Automation 1697.5.3 The Role of No-code and Low-code Programming 1707.5.4 The Impact of Automation 1717.5.5 Mobile Robots in Action 1727.6 Automation in an Academic Environment – An Interview with Dr. Tim Meyer from University Medical Center Goettingen 1737.6.1 Personal Introduction 1737.6.2 Automation as an Interdisciplinary Approach in Science 1747.6.3 High Staff Turnover in Academic Research Institutes 1757.6.4 The Role of Nonproprietary Communication Protocols 1767.6.5 Future Research Perspectives 1777.7 Small Automation Lexicon 1778 Miniaturization in the Laboratory: Size Matters, But Smaller Is Better! 1818.1 The Time Has Come 1818.2 The Diversity of Miniaturization in Liquid Chromatography 1828.2.1 Introduction 1828.2.2 Why the Focus on Chromatographic Methods? 1828.2.3 The Current State in Commercial Miniaturization 1838.2.4 Capillary Chromatography – the Greener Alternative 1858.3 Opening Up New Possibilities with Miniaturized Detectors 1858.3.1 Introduction 1858.3.2 LEDs Enhancing Sensitivity in Compact Systems 1868.3.3 Miniaturization Enabling Field Analysis 1878.4 Good Things Come on Small Chips 1888.4.1 Introduction 1888.4.2 Making LoC Accessible with Additive Manufacturing 1898.4.3 The Classical Approach 1898.4.4 Additive Manufacturing for Printing Modular and Highly Flexible LoC Systems 1908.5 The Potential Use Cases of 3D-printed Microfluidic Devices 1928.5.1 Introduction 1928.5.2 Sensor Platforms for Accelerating Bioprocess Development 1938.6 A Glimpse into the Future 1948.6.1 Introduction 1948.6.2 Technical and Scientific Challenges 1958.6.3 Short-term: Overcoming Current Problems 1958.7 Concluding Remarks, with a Personal Touch 1969 The Sustainable Laboratory of the Future 2019.1 Personal Reflection – The Last 10 Years 2019.2 Sustainability Trends in the Lab 2039.2.1 Sustainability in Science – from the Big Picture to a Common Understanding 2039.2.2 A Holistic Approach to Science and Sustainability 2049.2.3 Science Has a Big Impact 2059.2.4 Sustainability in the Lab – Our Current State 2119.3 Automation and Digitalization of the Lab from a Sustainability Perspective 2209.3.1 General Introduction 2209.3.2 Digitization as a Lever for Resource Conservation, Waste Reduction, and Process Optimization 2219.3.3 Automation, the Internet of Things, AI, Machine Learning and Deep Learning are Revolutionizing the Way We Do Research 2239.3.4 How Digitalization and AI Are Revolutionizing Analytical Methods 2259.3.5 The Downside of Digitalization – and How to Use It Sustainably 2289.4 Outlook: A Reflection About the Sustainable Lab of the Future 2319.5 Sustainability as a Pivotal Pillar of the Future Lab – An Interview with James Connelly, Chief Executive Officer of My Green Lab 2329.5.1 Personal Introduction 2329.5.2 Academic Versus Industrial Labs 2329.5.3 Education and the Importance of Grassroots Initiatives 2339.5.4 Greenwashing 2339.5.5 Open Access 23410 Cybersecurity 24310.1 Introduction 24310.2 Cybersecurity Risks, Threats, and Mitigation Strategies 24410.2.1 IT Services 24510.2.2 Risks 24610.2.3 Threats 24710.2.4 Mitigation Strategies 24810.3 Architectures, Concepts, Organizational and Technical Measures 25010.3.1 Architectures of Remote Labs 25010.3.2 Cybersecurity Threats in the Context of Remote Lab Architectures 25110.3.3 Organizational and Technical Measures 25210.3.3.1 Organizational Measures 25210.3.3.2 Technical Measures 25510.4 General Conclusion 259Index 263