AGENDA
25 June 2024 | Pre-Event Workshops
26-27 June 2024 | Main Event Days
Congress Center Basel
DIGITAL. AUTOMATISIERT. VERBUNDEN.
25. Juni 2024 | Vorabend-Workshops
26-27. Juni 2024 | Hauptveranstaltungstage
Basel, 26 - 27 June 2024
Schedule
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Automation 101: Starting your automation journey
Workshop leader:Martin Winter,CEO, Lab Automation Network
14.00 Back to basics – where to start: Ellen Piercy, Automation Lead Engineer, Unilever
14.30Tips and Tricks – implementing your technological strategy:Dietmar Krewer,Senior SME Automation & Robotic, Bayer AG * TBC
15.00What level of automation does my lab require?:Yousef Baioumy,AutomationEngineer,Adaptive Biotechnologies Corp
15.30So, which technology should I use?:Speaker TBC
16.00 Interactive discussion
Moderator: Martin Winter,CEO, Lab Automation Network
Yousef Baioumy,AutomationEngineer,Adaptive Biotechnologies Corp
Ellen Piercy, Automation Lead Engineer, Unilever
Dietmar Krewer,Senior SME Automation & Robotic, Bayer AG * TBC
Green Supply Chain
Workshop leader:Partha Krishnan,Deputy Director, Health Safety and Environment, Sanofi
14.00 Digital transformation in R&D shipping for green outcomes:Partha Krishnan,Deputy Director, Health Safety and Environment, Sanofi
Emelia Deforce,Program Manager, Sustainable Science & Product Stewardship,Genentech
14:30Route-planning software to improves operationalefficiency:Speaker TBC
15.00 How to create a green supply chain in an SME: Shahzeb Choudhry,Laboratory Manager,Procella Therapeutics AB
15.30Relationship building & collaboration between manufacturing and supply chain–Case study: Mitigating single plastic usage:Emelia Deforce,Program Manager, Sustainable Science & Product Stewardship,Genentech
16.00 Interactive panel discussion
Moderator: Partha Krishnan,Deputy Director, Health Safety and Environment, Sanofi
Shahzeb Choudhry,Laboratory Manager,Procella Therapeutics AB
Emelia Deforce,Program Manager, Sustainable Science & Product Stewardship,Genentech
SiLA & AniML Hackathon
Workshop leaders:Patrick Courtney, Director,SiLA Consortium &Burkhard Shafer,Head of Partnering,SiLA Consortium/AnIML
The Splash! Is a unique event for every digital lab enthusiast. It combines an educational part with a hands-on session to try out standards in action. Pick up the details on the popular SiLA and AnIML standards, understand how they work and where you can put them to use. Our hands-on session lets you experience the standards in action firsthand. We’re bringing real and cloud-based instruments and lots of example data sets. Feel free to bring an instrument of your own data.
This session is co-organised by Terrapinn, SiLA Consortium and the AnIML Society.Attendance is free of charge.
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Keynote Lecture: Perfecting labs with artificial intelligence and IoT
Keynote Panel: Is data driving us or holding us back from utilising AI?
Networking Break
Exhibiton floor
Working Group 1: AI in drug R&D – Data and change management impacts
Working Group 2: *Title TBC
Working Group 3: *Title TBC
Senior Representative, Tecan
Networking Break
Exhibiton floor
Chair
The lab AI revolution: unleashing the power of AI and data to accelerate research and discovery
Leveraging the power of AI in a next generation lab informatics platform
- An AI digital assistant to create experiment content and perform advanced scientific search
- Powering adoption and productivity with AI support assistants and code generation
- Unifying and contextualizing research data to build & apply AI/ML models.
Size matters-extreme miniaturization of automated compound synthesis
In industries where the generation of numerous compounds is essential for optimization, the quantity of compound synthesis is of significant importance. Commonly, the preclinical optimization phase for drug candidates involves the creation and screening of (ten)thousands of derivatives. However, this phase frequently involves the synthesis of unnecessarily large amounts of compounds, leading to substantial toxic waste and unsustainable practices. We believe that besides organic chemistry automation, synthesis scale is of equal importance. Here we discuss the 'discovery stage adapted scale' concept, emphasizing how the extreme miniaturization of automated compound synthesis can not only enhance sustainability but also expedite the discovery of clinical candidates while simultaneously reducing expenses.
Ecosystem building: a case study for hydrogen production and clean energy materials development
Mapping of ontologies and harmonizing (meta)data and terminology services
Optimising laboratory operations for sustainability with digital services. lessons learned and best practices
Real-life examples in large and small laboratories. How to maximise benefits and realise successful outcomes. How Agilent’s CrossLab Connect digital suite can improve efficiency, sustainability, and reduce costs in the laboratory. What are the key requirements for a successful implementation? Considerations for GxP and high-throughput laboratories.
Penzberg's pinnacle: Building tomorrow's lab - Integrating new R&D facilities, digital tech, and sample management
Establishing, short-, mid- and long-term strategies for lab facilities and real estate
First round pitches
First round of start-up pitches at start-up theatre on exhibition floor
Companies pitching include: Swoxid,Cellaven,Accelerated Materials,CDI,Aixelo
Large language model technology in the real word * Title TBC
Living datasets backed by automated experiments and open source methods
Align to Innovate’s Open Datasets Initiative is working to accelerate community-driven use of automated labs to pioneer robust data collection methods with the goal of curating high-fidelity, AI-ready biological datasets. We are identifying the most important datasets that should be collected in life science, creating automated measurement techniques to robustly and scalably collect data, and funding the collection of open datasets. After vetting dataset concepts and establishing our first collaborative teams for data collection, Align is now executing on our first dataset, a high-throughput technique for gathering protein sequence to function data. This talk will cover the on-going work in the Open Datasets Initiative, upcoming datasets, and Align’s suite of programs aimed at creating new paradigms for collaboration on large, data-intensive projects enabled by automation
* Title TBC
Senior Representative, Splashlake
Utilising digital twins to increase efficiencies and reduce processing time, costs and environmental impact
Niels Vandervoort,Senior manager, Pilot Plant data & systems, Johnson & Johnson * TBC
Mixed reality maintenance and repair solutions in the Lab of the Future ecosystem
Join Full Spectrum Lab Services as we delve into the accelerating pace of scientific innovation and the challenges it presents. With the constant evolution of laboratory equipment, quick maintenance and repair have become vital to prevent any disruption in scientific progress. This session will address the widening skills gap and discuss the need for faster response times to equipment malfunctions, which often pose a significant hurdle to research continuity. We will explore how embracing and deploying innovative technologies, such as Mixed Reality, can enhance the appeal of lab services and attract the next generation, including Gen Z, Alpha, and Beta, to consider a career in lab and facilities management. Be part of the conversation on the future of Extended Reality and its potential to bolster support for your end users. This session promises to offer a glimpse into the future of laboratory operations.
Next generation laboratory infrastructure-overcoming the challenges
This presentation delves into the transformative landscape of next-generation laboratory infrastructure, addressing the pivotal challenges faced by modern laboratories and elucidating the myriad benefits of emerging designs and technologies. Central to this discourse is the enhancement of safety, comfort, flexibility, efficiency, sustainability, and resilience within lab environments, each a cornerstone in the evolution of laboratory operations.
We will explore how innovative designs and advanced technologies contribute to heightened safety, significantly reducing the risk of accidents, thereby ensuring the well-being of laboratory personnel. The aspect of comfort is emphasized through ergonomic design and ambient improvements, which are shown to boost productivity and mental well-being of the staff. Flexibility is another key theme, as adaptable spaces and modular equipment cater to the dynamic nature of scientific research, enabling laboratories to rapidly pivot in response to changing research needs or technological advancements.
The presentation will highlight how these next-generation laboratories achieve greater efficiency through the integration of automated systems and cutting-edge instruments, facilitating accelerated and more precise experimental workflows. In terms of sustainability, we will discuss the incorporation of green technologies and practices, reducing the environmental footprint of laboratories while also curbing operational costs. Resilience, especially in the face of natural disasters, technological disruptions, and public health emergencies, is addressed through robust design and contingency planning, ensuring continuity and reliability of laboratory operations under diverse circumstances.
Finally, we will examine the profound impact of these advancements on the quality and reliability of test results. Enhanced precision, reduced error margins, and the ability to conduct more complex experiments not only advance scientific knowledge but also have significant implications for industries reliant on laboratory services. By synthesizing these elements, the presentation will provide an overview of how next-generation laboratory infrastructure is not only overcoming existing challenges but is also paving the way for more robust, efficient, and effective scientific exploration.
Impact of automation and digital tools on the future of data and machine learning
The coatings industry is evolving at an unprecedented pace in the digital world, providing new and improved ways to develop coatings, deliver better products to market, and meet customer demands for personalization, sustainability, and efficiency. To stay competitive in this dynamic environment BASF is embracing this transformation by not only focusing on digitalization and automation technologies but also by leveraging high-quality data being generated. However, the challenge lies in liberating data from silos and ensuring its quality and compliance with FAIR principles. We believe that data-driven innovation will unlock new capabilities that can fundamentally alter what a company can achieve.We at BASF are benefiting from state-of-the-art technology by moving away from trial-and-error methods to precise, data-driven models, we are not only reducing time-to-market, but also delivering innovative and fast-paced product development.
2D-drone swarm - an open source Amazon-like automation for laboratories
Complete laboratory automation requires not only the traditional, already well-developed automation of scientific instruments, but also the ability to efficiently transfer samples from one machine to another and possibly also to automate some preparatory tasks. It is also possible to robotize more complex tasks within dedicated automated stations or using versatile robots. Finding a good combination that is easily deployable, safe for people and scientific equipment, and flexible enough to accept dynamically generated workflows is essential to make the fully automated laboratory a reality. In this talk, we will first discuss different possible strategies for global laboratory automation and then present in detail the 2D drone swarm laboratory automation system that we have developed and deployed at the Swiss CAT+ at EPFL, which is an open source small autonomous mobile robot sample transfer system combined with multi-tasking robotic arms. A global laboratory automation strategy that is cost-effective, easily scalable, and safe for both humans and scientific equipment.
Laboratory device connectivity at scale
As laboratories strive for comprehensive digitalization, integrating a vast array of diverse laboratory instruments can be a daunting task. This intricate process plays a pivotal role in shaping the data pipeline and enhancing its accessibility to AI/ML algorithms. Labforward, with extensive experience in developing drivers for communication with proprietary interfaces, simplifies this process. We discuss the importance of interoperability standards in ensuring compatibility and streamlining device driver development. The crux of AI-readiness relies on more than just data acquisition and storage but rather involves (1) picking data, (2) standardizing it, and (3) forwarding it to its destination in an easily readable format. Ultimately, Labforward’s Lab Execution System (LES) - Laboperator, transforms the device data handling process, for a data management strategy that enables seamless communication, enhances accessibility and compliance, and allows scientists to harness AI's transformative potential.
Data, process, systems and architecture - the gateways to DIGITAL SCIENCE
Parameter control in laboratory processes
Panel: Driving innovation and maintaining standards in facility design and development
Addtional Panelists TBC
Algorithmic experimental design for automated labs
* Title TBC
Senior Representative, Chemspeed
Encapsulating ideas from the inside-out and outside-in to develop the lab of the future
Eco-smart automated assay processing
Automating intricate wet lab processes within R&D workflows with Mosaic Sample Management Software streamlines the overall research procedure, yet manually managing the resulting data poses a significant bottleneck. We'll showcase how our collaboration withGenedataScreener, facilitates the digitalization of Titians automation workflows.
We will illustrate an autonomous unattended cascade of follow-up assay results triggered by response hits, added to Mosaic assay requests to allow eco-optimisedliquid handler runs. Through the integration of Screener and Mosaic, we'll demonstrate how Screener autonomously supplies the hits to be pursued, while Mosaic automatically manages sample plate handling and initiates the follow-up assay.
Bridging lab sciences to consumer science through advanced analytics
From analog to automated: A step-by-step guide to the future-proof laboratory
In an era of rapid technological advances, laboratories worldwide face the challenge of transitioning from traditional analog methods to fully automated and digitalized systems. This abstract outline a step-by-step guide for laboratories to master and future-proof this transformation successfully. With the ever-evolving demands of the laboratory environment, it is essential to modernize processes and workflows to increase efficiency, accuracy, and reproducibility. The transition from analog to automated laboratory systems presents several challenges. The main problems include the high initial investment in hardware and software, the need to train staff to use new technologies, and ensuring data integrity and protection in digitalized systems. Added to this is the complexity of integrating new technologies into existing laboratory processes, which often requires a comprehensive reorganization of workflows. To overcome these challenges, a systematic approach is required that includes the following steps, starting from needs analysis and goal setting, where existing processes and workflows are analyzed to identify specific needs and clear goals for digitization and automation are set. Based on this analysis, hardware and software solutions are selected to meet current and future requirements. Introducing new technologies should be incremental, starting with a pilot phase that allows processes to be tested and adapted before being rolled out across the laboratory. The following steps include training programs for laboratory staff to ensure that everyone involved is familiar with and can use the new systems effectively. If both systems and users are prepared, a seamless roll-out of the new system can be realized, followed by a possible expansion of the integration with devices for datamanagement and security to guarantee the integrity and protection of sensitive information. Transforming from analog to automated labs is a complex but essential task to remain competitive in today's fast-paced scientific landscape. By following a step-by-step, well-thought-out plan, laboratories can overcome the challenges of this transformation and create an efficient, accurate, and future-proof environment. Ultimately, the automation and digitalization of laboratories enable increased productivity and quality and a profound change in scientific research and development.
Chair
Elevating data quality in the era of self-driving labs
Implementing cobots into your lab
API is integral to connectivity, so let’s get it right!
Simplified assay data management based on FAIR principle with CDD Vault
Digital transformation: Ensuring people and business process centricity overcomes the technology hype
Digital transformation is a multifaceted concept. A journey marked by numerous stops, and to the surprise of many, one that never truly ends.
In recent years, across the spectrum of activities in life sciences research and manufacturing companies, are observing an evolution in digital / IT initiatives from capturing data in monolithic systems of records and compiling insights into electronic documents, towards establishing data platforms that support business collaborative workflows by enabling data to be captured, transformed and exchanged within and between team, departments and organizations.
It appeared that the focus was positive and shifting towards people working with data within systems, relying on diverse technologies, rather than the reverse order. Or so it seemed, before the AI hype that brought technology back to the driving seat.
In this presentation we will discuss use cases and how to ensure a people and business process-centric approach in IT / Technology projects, avoiding mismatches between efforts on technology implementations and real business needs.
Lab Space & Asset Management (LSAM) – Optimisation via sensor and non-sensor data
LSAM is a solution to support data driven decision making to optimize the right size and right amount of instruments in a lab by using sensor data in combination with static inventory information.
Holistic concept for the Laboratory of the Future, encompassing flexilab, digital and robotic solutions * TBC title
First round pitches
First round of start-up pitches continue at the start-up theatre on exhibition floor 14:00-15:05
The lab of the future is self-driving
Chemical space includes an incredibly large number of potential molecules, exceeding 1060. This space is far too large for scientists to enumerate, let alone evaluate.AI-driven autonomous labs (self-driving labs or SDLs) are needed tooptimize the exploration of diverse material compositions to discover novel materials efficiently. Even when the exploration space is constrained, SDLs can improve the reproducibility of results and reduce the number of experiments and resources required, thereby reducing the cost and time required for discovery.
AlthoughSDLs have been used to study classes of materials with high-dimensional spaces, such as high-entropy metals, many challenges must be addressed to produce generalizable, scalable SDLs. These range from small material datasets for training machine learning systems to the difficulty of synthesizing materials withcomplex reactions and steps and autonomy testing a wide range of material properties.
This talk will discuss how the Acceleration Consortium is addressing these challenges and provide examples of how SDLs have deployed to dramatically accelerate materials discovery.
Fully automated workflows using mobile robots in the analytical laboratory
Enabling multi-step chromatographic processes with integrated software and hardware
EasyDrive - Document management, radically simplified
Switching document management systems may be necessary from time to time, but the disruption it causes to the business can be avoided!
Find out how we at Roche Pharma Manufacturing unified all relevant systems in a single interface, providing guidance and flexibility at the same time.
Digital transformation of knowledge generation in the lab of the present
The primary role of life science R&D laboratories is knowledge generation: data is produced through experimentation and processed into knowledge during primary analysis. Proprietary knowledge accumulated over time will then form the foundation for intellectual property and new products.
The Lab of the Future is expected to make the knowledge generation process faster and more efficient through digitalization and automation. Digital transformation initiatives mostly focus on digitalization of experimental data management while lab automation projects achieve two- to three- fold increase in productivity, without fundamental changes to experiment planning, execution and throughput. While these efforts represent steps in the right direction, the lab of the future still feels out of reach.
We developed walk-away automated workflows for serological assays using BSL-2 enclosed, fully integrated systems, producing titers that pass equivalence across two different systems, allowing for them to serve as backup, or ramp up capacity across different sites. We also fully digitalized and automated experiment planning, data capture and analysis. Our digitally transformed knowledge generation pipeline increased productivity 10x in 96-well format, with a direct path towards 30x increase by scaling down to 384-well, capable of producing 300,000 titers/year using a single operator and a single automated system with ~10m2 footprint.
Our example shows that the right combination of walk-away automation and digitalization using readily available hardware and software systems can already yield exponential increases in knowledge generation. Such “knowledge factories” could become global laboratories of the future, powering novel data science and AI/ML approaches with proprietary data at the required scale.
Orchestrating, running and optimizing the full lab to increase lab personnel, fleet productivity, and unlock better scientific outcomes
Lab-tory: Lab and factory facilities in one, for continuous processing food development
The fusion of "laboratory" (a place of experimentation and innovation) with "factory" (a place of production) suggests a facility that is both a site of scientific discovery and technological development as well as a place of efficient production and manufacturing. A place where experimental food technologies are not only developed and tested but also applied to create food products at scale. By combining these two concepts, the word "Labtory" implies an integrated approach to food production where research and development happen in tandem with manufacturing, driving the evolution of Exponential Food Technology. "Exponential Food Technology enables the convergence of efficiency, sustainability and health. The future of food production is here, and it is exponential." Exponential Food Technology is an interdisciplinary, data-driven approach that leverages existing and new processing technologies with developments in machine learning, real-time analytics and sensor technologies to move from a standardized to a categorized system of food production. This innovative framework facilitates the transition from static recipes to dynamic compositions based on real-time data analytics and customer/consumer preferences. By replacing traditional batch processing with continuous processing methods, this technology exponentially increases efficiency (e.g. time, yield, space, labor), reduces waste and improves value-added ingredient content (by avoiding time/temperature/oxidation stress for sensitive substances). Through these synergistic improvements, the technology represents an adaptive, self-optimizing network capable of aligning food production with changing consumer demands and sustainability goals while enabling non-linear, disproportionate advances in speed, quality, capacity, simplification and cost. The first application of this technology is in the field of cocoa processing. The extraction procedure, especially at comparatively lower temperatures, favors the retention of the primary aroma of the cocoa beans, which represents the specific characteristics such as variety, region and vintage of the raw material. The use of water during extraction significantly reduces the concentration of acetic acid and other volatile acids. Bitter and tannins can be separated or altered in such a way that the composition of the end product can be adapted to the specific target group. This, in turn, makes it possible to achieve enjoyment with regard to the sensation of harmony with little added sugar. The process results in the extraction of four essential elements: Cocoa butter, flavor, cocoa powder and dry cocoa extract. These components can be further processed in different configurations to produce a variety of food and functional products. Furthermore, extraction enables additional value creation by promoting wider acceptance and use of all products produced. In particular, this is achieved by saving the monomeric polyphenols, which are partially thermally destroyed in the conventional process and play an important role in the health benefits of cocoa and cocoa-containing products. Plant cell cultures are another exponential process. Research into energy production and conversion in cellular organisms has given rise to the innovative paradigm of "delegated photosynthesis". First, plants carry out photosynthesis in order to produce a specialized complex nutrient medium. This medium then serves as the basis in a bioreactor in which plant cell cultures (e.g. cocoa or avocado) carry out further molecular upcycling. Interestingly, this process is refined in both stages, with the territorially bound plants from the field providing primary photosynthetic derivatives and the subsequent cell cultures improving the nutrient composition for human consumption. The current findings highlight the potential of delegated photosynthesis in addressing global nutritional challenges and present a model that could revolutionize human nutrition. The developed methods for media production and propagation of plant cell cultures are fully compatible with continuous processing.
Future opportunities and challenges of machine learning for self-driving labs
The talk will discuss the current state-of-the-art of AI and machine learning methods used in self-driving labs. Itwill cover examples of recent self-driving labs and outline current challenges and new developments in autonomous data analysis as well as decision-making and optimization methods.
JAG brings 50 years of leading-edge process automation knowhow to LAB & GMP robotics
PyLabRobot – A universal open-source interface to liquid-handling robots
Liquid-handling robots and other automation equipment often ship with idiosyncratic proprietary interfaces that hinder integration with external hardware and software resources, and don’t allow for scripting with programming languages like Python. Proprietary interfaces are also generally not freely available for testing, demonstration, or education. PyLabRobot is an open-source interface to liquid-handling robots that provides a generic framework for interfacing with any liquid-handling robot based on the universal operations of aspirating and dispensing from defined resources within a Cartesian coordinate system. PyLabRobot provides an OS-agnostic programmatic interface to robots which previously only had Windows-based GUIs, and enables standardized interfaces for custom robots to be easily developed. The universal nature of the PyLabRobot interface enables development of cross-platform applications such as simulators, orchestration tools, and general-purpose libraries, which can be sourced from the community of open-source contributors. PyLabRobot models the 3-dimensional environment of the robot deck and associated labware with a generic JSON-formatted tree model that enables straightforward querying and modification. The PyLabRobot deck model can be integrated into other applications such as devices for transporting labware, enabling labs with robot arms and plate movement devices to more easily coordinate these with liquid handling operations. The standardized open-source nature of the PyLabRobot ecosystem provides a foundational layer for standardization of the next generation of automated lab environments and vastly improves the accessibility for programming liquid-handling robots.
Preparing for laboratory automation's next wave: The crucial role of a 'no data left behind' approach
As the landscape of Laboratory Automation evolves, one of the most transformative trends is going to be the incorporation of Artificial Intelligence (AI) and Machine Learning (ML) into automated workflows. This evolution stands to enhance lab operations with improved efficiency, reliability, and analytical depth. Traditional automation excels in routine task management but often fails to adapt to new data sets or changing conditions. The adoption of AI and ML is poised to fill this gap, offering labs the ability to not just complete tasks, but also to refine and evolve workflows with incoming data streams.
The shift toward this innovative approach calls for a comprehensive and considered strategy to capture and utilize the full spectrum of laboratory data, including environmental conditions, user interactions, instrument performance, and the intricate specifics of samples and experimental results. It's imperative to document the what, why, who, as well as the where and when—you must ensure that no data is left behind.
In this presentation, we will discuss the practical steps towards creating such a nuanced system and the opportunities it may present. We'll consider a future where intelligent algorithms could manage routine sample categorization and data analysis, potentially freeing up scientific personnel to focus on the more complex aspects of research and discovery.
Achieving this level of integration involves leveraging centralized data services, like GBG Data Services, which streamline the consolidation of operational data into a singular, accessible repository. This centralization supports informed decision-making and fosters connectivity across various lab instruments and systems, thus optimizing workflow efficiency. GBG Data Services acts as a comprehensive hub, systematically recording, storing, and disseminating data, facilitating AI-driven optimization and detailed reporting while maintaining compatibility with diverse management systems such as LIMS and ELN.
This initiative towards a data-rich, AI and ML-integrated environment is one that promises to enhance the capabilities of any lab. By adhering to a 'no data left behind' ethos, we lay the groundwork for the intelligent, evolving laboratories of the future.
Digitizalising and automating synthetic chemistry and analytics
Self-driving and cloud-connected labs for accelerating integration of energy materials
This presentation introduces a decentralised and adaptable future lab concept that speeds-up the development, integration, and innovation path for clean energy materials and technologies. By orchestrating from a single platform for selected hydrogen technologies, the platform is expected to find wide adoption in the clean technology field in the longer run, including energy harvesting, conversion, and storage; clean water technologies; and the synthesis of value-added chemicals and fuels.
Utilising soft robotics and LLMs to change how we use robots in the labs
Harmonizing data with an open-source approach and interoperable format
In response to the escalating complexity of instrumental analysis data, current processing solutions, such as monolithic software and microservices, face challenges in user adoption. Non-target screening (NTS) for environmental analysis faces additional challenges, as proprietary software lacks flexibility for diverse use cases. The StreamFind platform addresses these challenges by integrating open source software for data processing. Developed as an R library with a microservices architecture, StreamFind aims to enhance users' data literacy by providing a flexible and understandable solution for assembling data processing workflows. Core components, such as MassSpecData and RamanData, are specifically designed for mass spectrometry and Raman data, utilizing open source tools and native algorithms for efficient data processing. Central to StreamFind is the ProcessingSettings class, ensuring harmonization of processing methods for consistency and reproducibility. A demonstration of the StreamFind library showcases its capabilities, featuring an NTS workflow applied to mass spectrometry data from wastewater treatment. The StreamFind structure facilitates user-friendly scripting and automation, enabling command line deployment for reproducibility and data sharing. Future development will focus on enhancing processing capabilities with advanced and open source algorithms, and expanding processing engines to accommodate various data types. This approach aims to support interdisciplinary studies. The StreamFind R library is available for installation from the ODEA project's GitHub repository (https://github.com/odea-project/StreamFind), accompanied by comprehensive documentation, tutorials, and examples. Collaborative contributions to the project and the integration of additional open source tools are encouraged, fostering a collective effort towards advancing environmental data processing.
Predicting organic solubility–A journey through automated workflows, data, & models
Organic solubility is one of the key properties in small molecules development as it impacts reaction conditions, purification and isolation processes, affecting yields and scalability. The presentation will delve into the creation and refinement of automated workflows designed to streamline the collection, preprocessing, and analysis of large datasets pertinent to organic solubility. Highlighting the challenges and successes encountered in data curation, we will discuss the importance of quality, diversity, and representativeness in building robust models. Furthermore, the talk will cover the success stories and learning opportunities encountered during the project using real-world examples.
Accelerating time to market through digitalization of automation workflows * TBC Title
Improving productivity in biopharma applications using the power of automatization of new OpenLab CDS 2.8
OpenLab CDS 2.8 comes with a lot of new features to enable the automatization of biopharma workflows. If you want to know how Spectral Deconvolution of your biopharma samples can be automated, or if you are interested about the tools to automate the analysis of Single Stranded Synthetic Oligos, or if you simply want to learn about the general tools OpenLab CDS 2.8 provides to automate your workflows, we got you covered.
During this presentation you will find out how these tools are enabling Agilent to help our customers improving their Lab Operations.
* Title TBC
James Blount, Principal,Ellenzweig * TBC
Networking Break
Exhibiton floor
Chair
Making the hype a reality-AI for identifying molecule’s predictive behaviours
Full integration of ML into an ontology guided automated robotic workflow
BIOVIA Symposium: Unleash your lab's power: Instrument connectivity in the cloud
Is your lab struggling with manual data capture from instruments, and siloed data? Join us to discuss the challenges of direct data capture in complex workflows, and ensuring seamless communication between instruments.
This presentation explores how cloud-based lab informatics solutions can help:
- Connecting your lab instruments: streamline workflows with direct data capture, for increased efficiency and reduced errors
- Simplify data governance: standardizing data into a single format, and using the same data model all across the product development lifecycle improves consistency and reproducibility
- Unlocking Collaborative Research: Explore how instant data sharing can foster collaboration and accelerate your research efforts.
Panel: Should we ever delete data?
Unlocking the value of digital transformation
Getting down to business: pragmatic solutions for laboratory automation
The high-rise lab
More and more buildings for research and education must be developed on limited sites with limited budgets. Conventional low-rise labs with large footprints give way to compact urban high-rises with ample spaces for collaboration and computational research. Initiatives such as the ETH Zurich Masterplan Hönggerberg 2040, new international urban lab projects, and a patent-pending innovation are overcoming challenges and offering solutions for creating compact, flexible, and sustainable research environments.
AI-powered chemistry for selective molecular glue degraders
Small molecule molecular glue degraders (MGDs) repurpose E3 ligases to induce the degradation of disease-associated proteins. We’ve discovered how to rationally design MGDs, including glueable target discovery, matching to E3 ligases, MGD design, and virtual screening, and combined that with our large proteomics dataset, to rapidly discover and advance selective MGDs.
How are labs getting ready for the future today?
Lab of the future is an evolving concept. This presentation presents some of its challenges and how these can already be addressed today and what this means for our future. In what ever direction the lab of the future is evolving, HighRes stands aside as your trusted partner.
Case study: outgrowing and upgrading your ELN
Electronic Lab Notebooks (ELNs) are the cornerstone of data capture and organization within a cell and gene therapy company. However, as cell and gene therapy companies progress, the complexity of research data can rapidly outpace the capabilities of a basic ELN system. This presentation explores the challenges faced by R&D teams when their ELN becomes insufficient for managing the unique data demands of cell and gene therapy development. We will discuss limitations in data capture, integration, and collaboration capabilities that can hinder data capture and reporting. Additionally, the presentation will explore strategies for selecting and implementing a more scalable ELN solution that can effectively support the needs of a growing cell and gene therapy company.
Keeping on track: Implementation and management strategies
A deep dive into the Material Innovation Factory
Senior Representative,Material innovation Factory at University of Liverpool
BIOVIA Symposium: The lab is a knowledge factory: transforming research through connected data
The role of the lab is changing, into a place where tests are performed in part to generate high-quality data to improve organizations’ virtual modeling and simulation efforts. In this presentation we will explore how connected data can transform your lab into a powerhouse of knowledge.
- Optimize your data collection process for seamless integration with machine learning algorithms.
- Develop robust data pipelines to ensure the quality and consistency of your research data.
- Leverage real-world data to refine and validate virtual models for more accurate predictions.
The Lab is a Knowledge Factory, and we're here to help you unlock its full potential.
Accelerating the development of cancer treatments with ML: from bench to spin-off
The development of drugs is a time consuming and expensive process, typically involving trial and error. Although technology and high-throughput screening platforms allow the generation of large amounts of data, their availability is still very much confined to specific areas of chemical space and/or proprietary. Taken together, low data is the norm in drug development. In this talk, we will focus on a research program where machine learning operating on low data played a pivotal role uncovering the mode of action of an anti-proliferative natural product and establishing the link between molecular structure–drug target–disease. The roadmap from early stage discovery to clinical candidate will be discussed.
How automation software can enable smart imaging
Advances in manufacturing, science and technology increase the demands for complex experiments. The performance of microscopes and computers are often not the limiting factor anymore, but the time a researcher needs to spend in front of them. Nikon Healthcare - Life Science provides solutions allowing full automation of microscopy imaging. The graphical experiment designer called JOBS in NIS-Elements enables custom experimental setups, as easy or complex as the experiment requires. The full implementation of analysis workflows and artificial intelligence allow automation where it is needed with a user-friendly interface. Here we want to show a use case of how feedback microscopy facilitates large scale image acquisition.
Does the future of data storage lie in DNA?
More than an ELN-An integrated ELN and LIMS
Real-life utilization examples of hybrid automated laboratory infrastructure
GSK carbon neutral laboratory for sustainable chemistry
Located on the University of Nottingham’s award winning Innovation Park, the GSK Carbon Neutral Laboratory building provides unrivalled facilities for chemistry. The focus on sustainability is reflected in the building itself, which incorporates the latest technologies to allow it to be carbon-neutral over its lifetime. The laboratory is built from natural materials, and energy required to run the laboratory is met by renewable sources, such as solar power and sustainable biomass. Excess energy created by the building provides enough carbon credits over 25 years to pay back the carbon used in its construction. The building occupies 4500 square metres over two floors and in addition to laboratory space for around 100 researchers, it contains dedicated instrument rooms, a teaching laboratory for advanced undergraduate classes, and space for a range of outreach activities. In April 2017, the building was awarded the BREEAM Outstanding and LEED Platinum certifications – the highest levels of green building certifications.
Traditionally, chemical laboratories are highly energy-intensive and most are operational 24 hours a day, due to complex temperature needs for the manufacture and storage of chemicals. For example, energy-intensive cooling systems are required to stop temperatures reaching levels where solvents will evaporate. Meanwhile, recovering excess heat from processes can be challenging due to the risk of chemical and fume corrosion on the ventilation systems. Throughout the project development, cooling systems were only incorporated where absolutely required – for example, the Nuclear Magnetic Resonance lab, which is mechanically ventilated. A single lab in the centre of the building has been fitted with a natural ventilation system, to test its viability elsewhere. Chemicals at the facility are held in special storage units, meaning individual laboratories can shut down operations at night, leading to substantial energy reductions in ventilation and cooling requirements. A 125kWe biofuel combined heat and power (CHP) system was built on-site, providing the majority of heat needed for the buildings. As well as lowering carbon emissions, the CHP system exports excess heat to adjacent buildings on the University of Nottingham campus. A 230.9kWp solar array covers approximately 45% of the main building’s roof, while LED lighting has been fitted throughout, at an average of 5.4 Watts/sq.m. Overall, the building is estimated to deliver power savings of more than 60% and will use just 15% of the heat needed for a more traditional building design.
Enabling late-stage drug diversification by high-throughput experimentation and geometric deep learning
Creating new chemical entities is a pivotal yet challenging task in the discovery of small molecule drugs, often representing the primary bottleneck that affects both time and cost. In particular, C-H activation reactions applied in the optimization process of lead compounds frequently necessitate extensive high throughput experimentation (HTE) to determine the appropriate conditions and substrates. Machine learning techniques, particularly those that effectively process three-dimensional (3D) molecular data, have been shown to be valuable across various chemical research areas. In this talk, we present the application of graph transformer neural networks (GTNNs) to C-H alkylation and borylation reactions. We highlight the significance of 3D structural data in predicting regioselectivity and assess the influence of electronic data on the accuracy of predictions. Furthermore, we demonstrate that GTNNs, once trained, can facilitate the virtual screening of chemical libraries to pinpoint suitable substrates efficiently. The ability to identify synthesizable chemical entities with the desired characteristics rapidly advances the exploration of chemical spaces relevant to drug development.
Q&A session
Moderator: TBC
Archiving lab records * Title TBC
Exhibition onsite drinks reception sponsored by Smart Labs Ecosystem (Siemens | H.Ludi AG)
Location: Exhibiton floor
Offsite Drinks reception Sponsored by BIOVIA
Location TBC
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Keynote Panel: Can we hold the life science industry accountable for end-to-end sustainability throughout the whole development life-cycle?
Nicola Onofri,Director UE/UK R&D Procurement, GSK
Addtional Panelists TBC
Keynote Presentation: Is the new era of bioconvergence possible?
- What role does bioconvergence play in creating a synergised lab community?
Keynote Panel: How do we create a synergised lab community at the forefront of science, innovation and digital technology?
Networking Break
Exhibiton floor
Chair
Chair
Chair
Creating value by connecting standalone instruments: a fundamental step towards a data-centric lab
Senior Representative, Inniti
The pharmaceutical sector is increasingly adopting AI for improved drug development and patient care. Despite advancements in one end by AI/ML offering promising solutions for analysing vast datasets, challenges persist in the starting point of the origin of data due to disparate data sources, data silos, and inconsistent data quality.Instrument connectivity addresses this gap by facilitating seamless data integration from various manufacturer-agnostic lab instruments, ensuring reliability, standardisation, and consistency.Automating data generation at the source enables accurate, data-centric insights while ensuring regulatory compliance in audit trials, optimising lab efficiency by eliminating manual data logging processes. Connecting standalone instruments thus represents a crucial step forward in aligning data-driven capabilities with the industry's evolving data needs.
*Title TBC
Senior Representative, Aurora Microplates
Digital transformation in pre-clinical R&D
In this session, we explore the application of Labforward’s Lab Execution System (LES) - Laboperator, within the realm of experimental workflows in pharmaceutical R&D. In response to the escalating demand for more streamlined processes and a reduction in time-to-market, this collaborative project serves as a milestone in reshaping conventional laboratory practices. We uncover invaluable insights into navigating the digitalization of complex experimental workflows, adeptly addressing challenges posed by diverse device requirements, large data volumes, and integrating with existing 3rd party software. Furthermore, we highlight success metrics, showcasing benefits such as time savings, reduction in documentation load, error prevention, and increased standardization and reproducibility.
Second round pitches
Second round of start-up pitches at the start-up theatre on exhibition floor 11.00am-12.00pm
Enabling scientists to drive innovation: digital transformation as a key foundation for a successful journey
During this presentation, we will explore how laboratory digital transformation can help scientists overcome the challenges and barriers that hinder their innovation and growth potential. We will also provide examples and share best practices of how digital transformation – and the implementation of a LIMS - can enable organizations not only to achieve greater efficiency and productivity but make an impact in their fields.
Making reaction data machine readable with the Open Reaction Database
*Title TBC
More than a lab-creating a community in shared lab spaces * Title TBC
Panel: Digitalisation, connectivity and industrial IoT-Is this lab 5.0 or are we missing something?
Panel: Retention vs resignation – how to ensure your lab techs want to stay?
Multimodal foundation models for more reproducible scientific experimentation and data capture
Following a surge in the interest in large language models for scientific discovery, there is ample opportunity for foundation models to support the laboratory of the future by capturing and processing multiple data modalities. In this contribution, we report the use of large vision-language models for action recognition in first-person, egocentric scene recording and evaluate the feasibility of automatically transcribing laboratory procedures in real-time. Leveraging an in-house dataset of egocentric videos of prototypical chemistry actions, we present benchmarks of different approaches for action recognition: zero-shot predictions by large models trained on broad data, action classification by fine-tuned models, and the effect of including addition visual cues in the data such as gaze coordinates. We conclude by discussing the potential benefits and challenges of implementing the technology in the fields of research and education.
A smartlab network to foster digitalization and automation through open standards
The aim of the smartlab.network is to foster digitalization and automation in academic and industrial laboratories through the development of open and cost-efficient soft- and hardware solutions. It provides a platform for collaboration, training and discussion between students, teachers, end-users, soft-, and hardware developers. I will present the approach using recent cell- and tissue culture examples from our lab.
Creating a research infrastructure to harness innovation
The digital transformation affects bioprocesses and the bioprocessing industry just like everything else in our lives. Such transformation holds promises of significant business advantages for the companies. New mindsets, methods, and technology are being introduced at a rapid pace. Digital technologies can mitigate these work environmental challenges by partially automating trivial tasks and generating better decision-making. At the same time, it should be recognized that enabling technologies may introduce potential challenges for users.
Testa Center has an authentic production environment for the development, testing, and verification of operational technology, information technology, automation, and all other products and services that help us enhance quality, efficiency, user experience, and usability.
In Testa Center, we interact with researchers and companies working at the intersection of life science, software, and hardware development. We help to bridge the gap between people and technology, as well as between research and commercialization, so that the potential for innovative digital technologies is based on user needs. Closing this gap means that people can work faster and more efficiently with innovative digital technologies and a perceived sense of meaningfulness and self-fulfillment in the process of drug discovery. It also means that new innovations can be tested and verified in a real environment, hence shortening the time-to-market.
EPFL’s CO2 Calculator: Assessing lab emissions and identifying opportunities for reduction
In the Sustainability Office of the School of Life Sciences at EPFL, one of the key missions is to reduce the greenhouse gas emissions of 50+ research laboratories and core facilities. EPFL has developed an online emissions calculation tool to assess the carbon footprint of a research lab and identify leverage points to take action. This talk will present EPFL’s CO2 Calculator, delve into the challenges faced in quantifying, and the many reduction opportunities that were identified. Depending on the type of research conducted, footprints differ greatly from one lab to another. There is no one solution that fits all but meaningful emissions reduction can be reached with joint efforts at the individual, laboratory, and institutional levels.
The laboratory automation plug & play initiative
Robotized laboratory automation systems are becoming more and more complex, which hinders compatibility and easy implementation. The Laboratory Automation Plug & Play framework serves as a reference architecture model, including a hierarchical decomposition of lab workflows, outlining the corresponding layers and elements of the control architecture, and introducing a taxonomy for lab robot activities. By advancing the standardization and democratization of these technologies a more streamlined integration can be achieved. We will present the basics of the concept proposal and introduce the newly formed cross-company initiative that targets its implementation as a global guidance.
Rethinking connecting communities across different stages of development from innovation to application-The device translation & integration (DTI) scale
Multi omics * Title TBC
Alessandra Ruggiero, Assistant Professor, University of Verona
*Title TBC
Senior Representative, ThermoFisher
Applying low-cost VR and AI technology for cost-effective global training and collaboration
In recent years, the convergence of emerging technologies has revolutionized scientific research, enabling new possibilities for exploration and discovery. This talk will delve into the captivating realm of blurring boundaries between reality and virtual reality, with a particular focus on the integration of Virtual Reality (VR) and Artificial Intelligence (AI) into scientific laboratories. Traditionally, laboratories have relied on physical experiments and tangible materials. However, the advent of 3D printing presented an exciting opportunity to bridge the gap between the digital and physical realms. My research began by exploring the integration of 3D printing technology into laboratories, revolutionizing prototyping and enabling rapid fabrication of complex scientific equipment. This breakthrough allowed researchers to accelerate their experiments and enhanced their ability to iterate and refine their designs. Building upon the transformative power of 3D printing, my investigations have since ventured into the immersive world of Virtual Reality. VR offers a unique medium to simulate and explore experimental setups and environments that may not be easily accessible or feasible in the physical realm. By harnessing the potential of VR, scientists can visualize and interact with their experiments in unprecedented ways, transcending the limitations of traditional laboratory setups. This immersive experience not only enhances experimental understanding but also promotes collaborative research and knowledge sharing among geographically dispersed teams. Furthermore, the integration of Artificial Intelligence amplifies the capabilities of VR-driven laboratory environments. AI algorithms can be employed to analyse complex experimental data, enabling real-time insights and facilitating the discovery of meaningful patterns and correlations. Leveraging AI in VR-based laboratories opens doors to intelligent automation, predictive modelling, and augmented decision-making, empowering scientists to extract deeper knowledge and achieve breakthrough discoveries. During this talk, I will present case studies and practical implementations of the integration of VR and AI in my laboratories. By embracing these technologies, researchers can transcend traditional boundaries, accelerating the pace of scientific inquiry and fostering interdisciplinary collaboration.
Implementing change in manufacturing to reduce consumables and single use plastics
Emelia Deforce,Program Manager, Sustainable Science & Product Stewardship,Genentech
Networking Break
Exhibiton floor
Chair
Chair
What are the limits of AI? Applying AI and smart tools to flavour creation and beyond
Alexandre Matos, Technical Director Taste,Kerry * TBC
Growing beef with robots: Building a robust lab automation pipeline for cultured meat research
Mosa Meat is developing cultured beef, using cells taken painlessly from a live cow to grow a burger. Our process involves meticulously growing fat and muscle cells to replicate the taste and nutritional profile of conventional burgers. To assist the scientists and engineers in optimizing fat and muscle differentiation for production, the Automation Team at Mosa Meat serves hardware needs across the company, from high-throughput screening to large custom cell cultivators. In this session, we will focus on the smaller scale, looking at the pivotal role of the lab automation group in developing screening pipelines. In close collaboration with researchers, we've automated processes otherwise validated in suspension culture in well plate assays using off-the-shelf liquid handlers like the Opentrons OT-2 and the Tecan Fluent. We'll share insights into enhancing the traceability and reliability of our liquid handling work using tools such as Google Sheets, Google App Scripts, Python, and GitLab and share challenges we faced along the way. Furthermore, we'll take a deep dive into how liquid handlers and rapid prototyping tools have been instrumental in optimizing our fat differentiation media.Lastly, we will look into custom-manufactured systems created in-house at Mosa to answer questions beyond well plate assays, such as questions about media reduction and cell feeding strategies for larger cultures. We are continuously improving the cost and quality of our cultured burgers, and lab automation has become an integral part of this work.
The path to a world class lab operations programme
- Key considerations
- The value of partnerships
- Adapting to change
Panel: Going above and beyond FAIR data-Is our research reproducible?
Breaking barriers: The role of digital lab platforms in scientific advancements
Sustainable product development starts in the lab
Low-cost integrated AI and automated ultrasonication platform for high-precision fungal cell disruption
Workplace experience “Are our labs the best places to work? Insights from experience surveys across Roche Diagnostics R&D lab portfolio"
Survey assesses how well the facilities, services and technology support the scientists activities. Findings show which factors contribute most to knowledge exchange, productivity, & company pride, and how the insights translate into actions.
Bringing people along on the journey
Bringing people along on the digital transformation journey is about the importance of Change Management, and knowing your people. We cover the challenges facing digital transformation of a traditional R&D organisation and how that might relate to the people in your organisation. We share how to build trust, inspire people, and give them the power to change.
Start-up pitch winner announcement
Head to the Start-up Theatre for the winner announcement of the start-up pitches
Cost efficient lab automation solutions for SMEs and smaller laboratories: novel software and hardware concepts
European research and innovation opportunities for your company or institute to collaborate with EU partners and get funding
You've certainly heard about Horizon Europe, the large EU Framework Programme for research and innovation.
If you don't really know what's in there and how to access funds, join this 30min talk to get an overview of the different parts of the programme that fund research and innovation in your thematic fields.
Additionally, you will also learn about the current situation of Switzerland in the Horizon Europe programme and you will be delighted to hear how much funding opportunities are available for Swiss based entities. Finally, you will be offered advice how to get started.
Making your lab smart with connected lab assistant * Title TBC
Shifting mindsets in larger organizations for open and constructive working
AI4Green-An open source ELN for green and sustainable chemistry
Digital tools will be a critical part of making chemistry research laboratories more sustainable. However, there are many barriers, including hardware, software and change management. The newly released, open-source AI4Green electronic laboratory notebook,https://ai4green.app, combines features, including data archival, collaboration tools. AI4Green is a web-based application and free to use. As users plan their reactions and record them in the electronic laboratory notebook, green and sustainable chemistry is encouraged by calculating green metrics and colour-coding hazards, solvents, and reaction conditions. A Summary Table is automatically generated by AI4Green, showing Red-Amber-Green colour-coded metrics from CHEM21 and other considerations related to the Design Principles of Green Chemistry. Several metrics are calculated automatically, like the sustainability of the chemical elements used in the reaction and the atom efficiency. Other metrics must be inputted by the user, such as the temperature of the reaction, batch or flow reaction conditions, the isolation method, the use of a catalyst, and whether that catalyst was recovered. A risk assessment section allows users to identify standard protocols, disposal of waste materials, spillage procedures, and any other risks. An overall risk score is computed by self-assessment of the reaction’s hazards, risks, and consequences.Theapplication's design facilitates the development of auxiliary sustainability applications. AI4Green features a user-friendly sustainable solvent selection tool, which comprises the Solvent Guide and the Solvent Surfer. Future deployments of AI4Green will use inputted reaction data to make intelligent sustainability suggestions. This may be to suggest using a less hazardous solvent or reagent, predict milder suitable reaction conditions, or simulate Life Cycle Analysis for process scale-up.
Networking Break
Exhibiton floor
Chair
Assessing the landscape for AI- industry trends and where is investment going?
International health networks in the lab automation eco system
Collaborate to innovate: ecosystem-based approaches in the industry
Tech showcase-launching and developing products
Sponsored showcase speaking slots available
How to communicate change from the top to the bench * TBC Title
The benefits of creating a culture of sustainability across our laboratories
A bioSASH and SiLA journey-Implementing advanced laboratory automation technologies
Closing panel: Exploring innovative and transformative technologies in drug discovery and beyond
Developed in collaboration with ELRIG
TraceBOT project- Steamling sample testing with smart laboratory automation
Utilising a co-funding model develop a bespoke solution and in turn a commercially available product * Title TBC
Reserved: Senior Representative, AST
Automated metadata and FAIR
Making science greener: Researcher perspectives & solutions
As the environmental sustainability of research has come into the spotlight more, members of the Royal Society of Chemistry wanted to get a picture of the current situation for scientists and their organisations: How much are people thinking about the environmental impacts of their research? What changes are they making? What is preventing them from taking action and what do they think would help them to do more? To start to answer these questions we surveyed 700 practising scientists globally and published the results, combined with desk research and insights from expert working groups, in our Sustainable Labs report. We found that 84% of respondents want to do more to reduce the environmental impacts of their research but that there is lot of variation in the extent to which people are taking action to reduce these impacts. In this talk (with Q&A) we will also share what we heard about the concrete actions that people are taking, as well as their perspectives on barriers and opportunities at different scales. We will draw on examples from the projects that we are supporting via our Sustainable Labs grants scheme, which aims to enable groups of researchers to accelerate the journey towards more environmentally sustainable research.
Closing panel: Research roadmap for laboratory community-automating discovery: high throughput experimentation, diagnostics and robotics/AI
Since the earliest days, laboratory users have benefited from increasing automation. This has been achieved by suppliers adopting and adapting technologies such as robotics, and more recently artificial intelligence.Public bodies such as the European Commission have facilitated this funding technologies but requires guidance on future needs of the sector. This session will present the latest update to the research roadmap developedwith contributions from over 100 lab professionals, from research, academia and industry. This builds on the first white paper published in 2016 which resulted in the lab being recognised as a distinct sector
Case study of collaboration in academia and industry–Inacube Challenge
FAIRification Speedboat concept: Consolidating legacy data across different labs into a companywide strategy * Title TBC
Closing panel: Interactive discussion-Q&A with presenters
Circular economy in labs–possibilities and limitations
Thorsten Nölle, Green Lab Switzerland
Labs are per definition special, individual and complex. These require special buildings, sophisticated infrastructure, multiple devices and instruments and tons of consumables. How is it possible to establish circular concepts for all of these dimensions to reduce waste, minimize costs and boost efficiency while limiting the environmental impact?
Green Lab Switzerland has been developing a position paper covering the best practices of different industrial and academia leaders and providing guidance about the possibilities and limitations.
Die Technologie ist in aller Munde... aber wie können diese Technologien in der Arzneimittelforschung eingesetzt werden, um Industrien außerhalb der Biowissenschaften zu verbessern und die Entwicklung von selbstfahrenden Laboren zu ermöglichen?
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