27-28 May 2026 | Congress Center Basel
27-28. Mai 2026 | Kongresszentrum Basel
Conference
Konferenz
Basel, 27 - 28 May 2026
Schedule
Create your personal agenda –check the favourite icon
The Collaboration Blueprint: Creating an Infrastructure of Intelligence via an Autonomous and AI enabled lab ecosystem
Keynote Panel: Bridging boarders: Europe's Role in a New Era of Global R&D
- How to navigate current tariffs structures and trade policy to maintain innovation?
- How is Europe continuing to attract top research talent?
- What are the current public and private investment priorities in R&D?
- How to source funding to maintain innovation in current climate?
- How can partnership encourage development in the science ecosystems and enable R&D scale up?
Keynote Panel: AI Readiness: data, technology, processes and people
- What does it actually mean to be AI-ready (Infrastructure, metadata, labeling, pipelines)?
- Examples of real-world successes linked to data quality & value produced
- How to engage users, employees, and partners to input better data (Incentives, UX design, and education)?
- What can be achieved in the future with these AI tools?
Break
Exhibition Hall
*Title TBC
Senior Representative, JAG
From semantics to knowledge graphs-shifting towards ontology-based data management
Reimagining Laboratory Execution - Intuitive by Design, Seamless at the Bench
What if executing experiments were as seamless as designing it? This session presents a bold new vision for laboratory execution—one that leaves paper behind and transforms protocols into intuitive, digital workflows at unprecedented speed. This includes a landmark collaboration to bring trusted analytical standards into the digital age—making them directly executable as elegant electronic protocols. Designed from the bench up, this approach delivers an exceptional user experience that empowers analysts to work naturally, efficiently, and with confidence. Also get an Agilent design expert’s insights on why UX is a crucial driver for laboratory adoption, productivity, and success, and therefore, is needed to enable the future of laboratory software.
*Title TBC
Senior Representative, Waldner
Gaining momentum with a grass-roots community on sustainability
Driving Lab Innovation Together. The digital lab by design. The challenges and advantages with real live workflows
This session explores how the digital lab, designed with integration at its core, enables collaborative innovation across modern R&D environments. Nvaignostics is using real, end-to-end workflows and showcases the advantages of moving toward an ecosystem-based lab model. Attendees will learn what is required to build a future-ready digital lab, how platforms like Sapio facilitate this transformation, and how AI-driven orchestration reduces complexity while preserving governance and traceability. The session concludes with a concise introduction to the ELaiN ecosystem and a forward-looking perspective on what comes next in digital laboratory innovation.
Enabling Rapid Innovation with Internal Engineering
*Title TBC
GSK’s Digital Blueprint: Integrating Business, Tools, and People
Laboratory Vision- Building Aligned and Reliable Systems through Analytical Sciences
This session will explore how analytical sciences shape the future of laboratories by building aligned, reliable, and efficient systems. We will discuss strategies to enhance data integrity, harmonize methods across laboratories, and foster innovation through advanced technologies. The session will highlight best practices for ensuring quality, consistency, and trust in laboratory results, while also addressing how young professionals can contribute to this evolving vision.
For companies that manufacture and sell laboratory equipment, establishing a strong Laboratory Vision and building aligned, reliable systems through analytical sciences represents a major sales opportunity as well. Such an approach can significantly expand their customer portfolio by enhancing trust and demonstrating added value.
Green Labs at Scale: How Policy and Purchasing Are Driving Industry Adoption
Sustainable laboratory practices are no longer a “nice to have.” Across pharma, biotech, and research institutions, policy frameworks and procurement requirements are rapidly transforming green labs from voluntary initiatives into industry standards. This session explores how regulatory pressure, corporate climate commitments, and supplier tiering programs are accelerating adoption at scale. Drawing on real-world examples from global biopharma and CRO networks, we will examine how transparency, third-party verification, and harmonized purchasing criteria are creating a single sustainability signal across the lab ecosystem - turning ambition into measurable, system-wide impact.
AI’s next step: How to scale quickly and embed AI innovation within organisations and scientific processes
*Title TBC
Senior Representative, Chemspeed
From Data to Impact -Building the Foundations of Innovation
From Biotech to TechBio: How Modern Labs Standardize, Integrate, and Scale
The modern lab is changing fast, from Biotech to TechBio. What does that mean for you? It’s about connected instruments, structured data, and flexible digital workflows that evolve with new tech.
In our presentation, we’ll share how to:
- Standardize your data collection.
- Build integration-ready workflows.
- Implement sustainable, ROI-driven practices.
Equipment utilisation, CapEx decisions, and hidden capacity: what 12 million equipment bookings reveal about R&D lab operations
*Title TBC
AI Operational Excellence in Drug Discovery: Turning Models-as-a-Service into Actionable Science
Operationalizing artificial intelligence in medicinal chemistry requires closing the gap between computational models and experimental workflows.Revvity’sSignalsXynthetica™embeds AI models directly into the environment where scientific data is captured and analyzed, creating a continuous learning loop that improves predictions over time. As a Models-as-a-Service platform, it delivers in-silico design and property prediction alongside real-world validation, without requiring organizations to build ormaintaincomplex AI infrastructure. Through a strategic collaboration with Eli Lilly, SignalsXyntheticanow provides access to LillyTuneLab™models,trained on extensive proprietary research data,via privacy-preserving approaches, democratizing high-value predictive capabilities for discovery teams. For medicinal chemists, this operationalizes AI-augmented discovery at scale, accelerating design cycles for both traditional small molecules and emerging modalities whilemaintainingrobust governance and scientific rigor.
Operating automated systems for labs – doing more with less
*Title TBC
Senior Representative, CDD
Closing the gaps in digital R&D
Despite numerous digitalization projects in R&D, gaps between different software solutions often remain. Experiment planning, inventory management, analytical devices, statistical tools, and regional processes frequently stay disconnected. These gaps lead to double work, manual transfers, data errors, and lower engagement among the many colleagues who focus primarily on scientific work rather than IT. Data scientists and lab experts also struggle to combine related data from different sources. Closing these gaps helps unlock the full potential of digitalization by enabling smoother workflows, higher data quality, more efficient use of resources, and stronger adoption of digital ways of working.
Sustainable Scaling: Navigating Growth from 60 personnel to 300
From automation to agentic systems - a new paradigm for software engineering
Beyond Legacy Automation: Designing Labs for What Comes Next
This talk explores why legacy, fixed lab systems struggle to keep pace with modern science and what must change to enable AI-driven, agentic models. It examines how leading labs are shifting toward software-defined, data-centric automation built on open architectures. We’ll outline what’s required to support autonomy, orchestration, and continuous learning without compromising reliability, interoperability, or compliance, and share practical frameworks to assess whether current automation infrastructure is ready for what comes next.
Driving performance and governance in routine labs through Data & Analytics
Data is the key ingredient to unlock greater performance, transparency, and trust in routine laboratories, where efficiency, reliability, and turnaround times are key. This presentation shares the journey of the Data & Analytics Program at Mars, used to manage its network of internal and external Q&FS laboratories. Since 2021, the program has improved performance monitoring, optimization, and governance within a complex operational ecosystem. Alongside outcomes, the session shares challenges encountered, from data harmonization to change management, and lessons learned. Attendees will gain practical insights into applying data and analytics to improve decision-making, transparency, and customer satisfaction in routine laboratory environments.
Connected Labs, Connected Minds: Orchestrating a Global ELN Rollout
A global ELN rollout is more than an IT project—it's a strategic enabler for digital transformation. This talk outlines how to align goals across regions, simplify processes, and connect teams through a unified digital platform. We highlight key success factors and also discuss common risks and pitfalls. Leaders will gain a concise roadmap for turning a global ELN into a catalyst for efficiency, data quality, and smarter decision‑making across the organization.
From Downtime to Dashboards to Predictive Insights - How Labs are Accelerating Productivity and Sustainability with CrossLab Connect digital services.
- This session shows how CrossLab Connect gives lab leaders real‑time visibility across operations, turning downtime and fragmented data into actionable insight.
- Through real customer examples, we highlight how data‑driven decisions improve productivity, reduce risk, and support cost control and sustainability.
- We conclude with what’s new and what’s next, including how AI is enabling earlier fault detection and predictive insight for future‑ready laboratories.
Kick off your lab sustainability journey with EPFL CO2 Calculator
The CO₂ Calculator is a groundbreaking initiative developed in EPFL to enable research labs to measure and reduce their environmental impact and will be deployed in summer 2026. It provides a rigorous yet practical way to assessthe carbon footprint ofenergy use, travel, equipment, and procurement.
This toolwill be used to cover the first stage of a three-step sustainability journey currentlyimplementedat the pilot scale inEPFLfaculties:
- Evaluate
- Plan:developan action plan and strategyto mitigate the footprint,including the use of certifications
- Transform: implement the action plan throughout the lab value chain
Break
Exhibition Hall
Workflow Integration Demonstration
Sponsored by Bruker, SciY, ZONTAL, Chemspeed
Panel: Agentic AI: Shifting from Data Processor to Autonomous Scientific Partner
- What is Agentic AI in the context of the lab, and how does it go beyond traditional AI & FAIR data in achieving autonomous discovery?
- What are the biggest pain points in today’s lab environment from an operational perspective, (LIMS, ELN, document repositories) and a data (perspective vast raw data, GMP double verification)?
- How is Agentic AI mitigating these?
- What is the industry doing to drive active use of agentic AI in the lab and what might the future hold?
WeChemSynOntology: Semantic Modeling of Wet Chemical Syntheses in a Self-Driving Lab for Nano-and Advanced Materials
*Title TBC
Senior Representative, Zifo
Unlocking Digital Maturity: IDMP as the Catalyst for Connected, Intelligent Labs
IDMP is already being adopted across the pharmaceutical industry as acore enablerof digital transformation - not just a regulatory requirement. By providing a harmonized, machine‑readable structure for medicinal product data, IDMP unlocks true interoperability across regulatory, safety, manufacturing, and supply‑chain systems, enabling consistent data exchange and lifecycle continuity. The EMA notes that IDMP ensures reliable, unambiguous communication of product information, forming the backbone of digital operations.
Industry benchmarks confirm that 89% of companies now consider IDMP central to their digitalization strategy, driving AI readiness, automation, and mature data governance.
This session explores how IDMP transforms compliance into scalable digital capability.
From Manual to Automated: Revolutionizing Molecular Biology with Sustainable Practices
Climbing the Knowledge Pyramid: How AstraZeneca's Operations Knowledge Fabric Transforms Pharma Operations Through Connected Data
Enterprise AI is failing at scale: despite massive investment, only a small fraction of organizations generate real value. The core problem is context. While generative AI can reason fluently, it lacks the semantic grounding required to operate reliably in complex enterprise environments. Knowledge graphs are often treated as databases rather than executable context, leading to brittle systems and confident hallucinations.
In pharma operations, where regulatory, supply chain, and safety constraints are non-negotiable, semantic precision is essential. AstraZeneca’s Operations Knowledge Fabric shifts from data lakes to semantic-first data products, living ontologies, and graph-native infrastructure. By embedding meaning directly into data, we enable faster AI deployment, higher-quality decisions, and a foundation for autonomous, domain-aware systems.
Digitalization in the Chemical Industry: A Consulting Blueprint for Strategy, Skills, and Supply Chain Transformation
This session will explore how a consulting-driven approach can support organizations in developing a future-ready blueprint for digitalization in the chemical industry—one that integrates strategic alignment, workforce capability, and supply chain excellence. The presentation will highlight how agentic ways of working are expected to empower consultants, planners, and transformation teams to collaborate effectively with artificial intelligence, enabling meaningful improvements in supply chain operations. It will demonstrate how developing a shared understanding of goals and processes and investing in targeted upskilling can enhance human capabilities for AI-augmented decision-making. The session will also emphasize the importance of embedding agentic behaviours and work patterns into daily operations, rather than treating AI as a stand-alone technology deployment. Attendees will gain a practical, people-centric roadmap for scaling digital transformation across complex chemical supply chains—ensuring that technological advancements translate into sustainable, enterprise-wide impact.
The impact of AI on lab operations and efficiency
Championing Sustainability Across the Lifecycle of Laboratory Devices
How can research laboratories shift from a linear “buy-use-discard” approach to a more circular economy model for their devices? Transitioning from a linear to a circular model requires rethinking how these assets are managed throughout their lifecycle. This talk integrates laboratory management, quality considerations, and sustainability initiatives to demonstrate how the Value Hill framework can uncover opportunities for value retention and optimization. Supportive emerging solutions will be highlighted, including My Green Lab’s and I2SL’s Freezer Challenge. Evotec’s active participation demonstrates how improved practices related to ultra-low temperature (ULT) freezers can reduce environmental impact while safeguarding performance and compliance.
*Title TBC
Senior Representative, Benchling
Building partnerships between industry and academia, to advance innovation in robotic in Switzerland
*Title TBC
Senior Representative, Capgemini
Why do Digital Lab Initiatives Struggle? How Astrix’s Lab of the Future Blueprint turns Vision into Impact
*Title TBC
Turning plastic scrap into pyrolysis oil to produce new plastic polymers
Reac-Discovery, your AI drive platform
Panel: Why Quality Data Isn’t Enough: Building the Architecture for Scalable AI-Ready Data?
- Why does event "high-quality" data often fail to produce reliable AI models?
- Is the real bottleneck for AI the lack of data, or is it a fundamental failure in our data governance and structuring foundations?
- Why are standard IT data models failing in pharma R&D?
- How do you build a sustainable data foundation for tomorrow’s AI when you are still struggling with "siloed" legacy data from a decade ago?
Panel: From Molecule to Manufacturing - Empowering digital twins via data and AI
- What are today’s real-world implementations beyond simulation?
- How AI and real-time data enhance digital twins?
- How can we bridge the gap between research and real-world deployment?
- How does having access to structured, verifiable data build the trust necessary for scientists to adopt AI?
How can we democratize laboratory automation to achieve the dark lab
The vision of the “dark lab” is to create a laboratory with minimal human intervention. Until now, this goal has required significant resources, making it largely inaccessible to smaller laboratories and universities. However, recent advances in digitalization and automation make laboratory automation more accessible. Key enablers include cost-effective collaborative robots, drag-and-drop low-code software, and the growing adoption of open standards for direct device integration. This presentation compares laboratory automation approaches that require no deep programming or engineering knowledge, using practical examples to show how democratized automation can enhance efficiency, accessibility, and innovation in research, bringing light to the “dark lab.
Cross-pollination of intelligence: Leveraging fragrance industry innovations to reduce the carbon footprint in traditional spirits
Break
Exhibition Hall
Workflow Integration Demonstration
Sponsored by Bruker, SciY, ZONTAL, Chemspeed
Making AI Stick: Champions, Feedback & Scalable Adoption
Engineering the Future of Automation with Soft and Biohybrid Robotics
Panel: Data Harmonization & Orchestration in the Lab of the Future
- What are your real-world challenges in achieving lab-wide data harmonization across instruments, legacy systems, and global sites?
- What framework do you use for the 'build vs. buy' decision regarding data orchestration layers?
- What are the best practices for designing a flexible and scalable data architecture that truly facilitates data flow and analysis?
- What are the most significant successes and failures learnedfrom your digital transformation initiatives?
From Materials Design to Market: Unifying R&D, Integrating Materials and Recipes, and Accelerating Scale‑Up in Specialty Chemicals
Advances in digital technologies and scientific innovation are critical for developing next generation chemical materials with properties optimized for commercial use.
This session will cover the transformation of R&D operations, the integration of recipes, formulations, and full material lifecycle data, as well as how to accelerate process design and scale up to industrial production.
Together, these capabilities establish a fully connected and digital R&D environment that accelerates material discovery, strengthens compliance and data integrity, and reduces the time required to scale new performance materials and formulations to market.
Change First: The Non-Negotiable Step to Team Readiness
Leveraging AI to generate impact: From Code Generation to Lab Implementation
How do you move from LLM experiments to business impact in a lab. I will share our roadmap from first internal chatbots to knowledge bases and agent style workflows that support scientists in daily HTE operations. The focus is on what changed in practice and what moved the numbers: faster cycle times, improved data quality and traceability, and quicker troubleshooting. The talk will explore how emerging AI tools are reshaping the way we think about automation, collaboration, and decision making in the lab—highlighting opportunities, lessons learned, and what’s next on the horizon for data‑driven experimentations. Our journey is still at an early stage, and I will reflect on how the latest extended capabilities of our HTE laboratory in Frankfurt—ranging from new automation modules to integrated data pipelines.
*Title TBC
Senior Representative, Gingko Bioworks
The Orchestrated Lab: Harmonizing Digital Workflows and Integrated Interfaces
How Change Managers can help leadership on their (ESG) sustainability transformation goals
Are you AI ready? How to be a proactive lab
Validating New Approach Methods Through Standardization and Automation
New Approach Methodologies (NAMs) like iPSC-derived heart tissues promise to replace animal models in cardiovascular drug screening, but require standardization for regulatory acceptance. autoOrgan.3R is an automated test platform for high-throughput 2D (384-well monolayers) and 3D (EHM in myrPlates) tissue cultures.
We integrate robotics, SiLA2 standardization, and AI analysis (SarcAsM, pole-tracking) for pilot screens, efficacy (contractility), and safety (arrhythmia) validation. This ensures batch-to-batch consistency, low contamination, and precise functional readouts, aligning with 3R goals by reducing Germany's 130,000 annual CV animal tests
A framework for compliant preclinical discovery data sharing cross-functionally
*Title TBC
Senior Representative, HighRes
Panel: Beyond the Green Hype: Strategies for Sustaining a High-Impact Sustainability Lab
- Have you ever had to “defend” your lab's work internally? How did you do it?
- How do you handle burnout or mission drift in a sustainability lab?
- What have you done to build trust with the wider organisation?
- Which external partnerships helped elevate your lab's work, and what was the key to its success?
Panel: The Future of Workforce of the Lab: Sourcing talent, skills and awareness?
- Recruitment Channels: Where are we finding talent for highly digitized labs? (e.g., universities, industry, non-traditional paths).
- Computational Skills: Defining the difference skills needed for computational roles and how to integrate data science, AI, and programming.
- Awareness Gap: How to combat the lack of awareness about lab careers and redefine what a 21st-century lab is.
- Mitigating Shortages: Identifying the most critical skill gaps and the immediate, actionable solutions employers can implement.
- STEAM to Lab: What specific, actionable changes can STEAM programs implement to meet the high-tech demands of the future lab?
Large Language Model Framework for Optimising Chemistry
Cybersecurity in the Lab: Balancing Innovation and Data Protection
I will share practical insights from enterprise cybersecurity initiatives that laboratories can adopt to strengthen data protection and operational resilience. The session will cover conducting risk assessments to identify and protect the laboratory’s crown jewels, implementing third-party and supplier security to safeguard collaborations, and embedding secure-by-design principles into projects from the outset. Attendees will learn how to turn these insights into actionable operational decisions, protect sensitive research data, and foster innovation without compromising compliance or continuity.
How do I bring my diagnostic innovation to the patient?
Exhibition Drinks
Exhibition Hall
Create your personal agenda –check the favourite icon
Molecule to Market: One Strong Thread - No Loose Ends
Today’s labs create amazing science, but the path from idea to approved product is still slowed by silos, manual handoffs, and missing context. This keynote shares a practical blueprint to build a clear digital thread from early R&D to tech transfer and manufacturing, so teams can move faster with fewer surprises.
We start in discovery, where multimodal therapeutics and complex biologics raise the bar for data quality and traceability. When sequence design, construct registration, and assay results live in one connected fabric, scientists can explore more formats with confidence. Machine learning guides choices with evidence. Integrated modeling, registration, and production context improve precision and speed when information stays harmonized end to end.
Next, the lab backbone: Automated capture of instrument files, with parsing, QC flags, and one click reports, turns messy streams into analysis ready data. Collaboration improves because everyone sees the same view. Dashboards compare candidates and move the right ones forward faster.
Simulation strengthens the thread. Digital twins let teams test factory layouts, flows, and staffing before steel is cut. Fluid dynamics in fermenters reveals mixing and oxygen transfer, so you can tune baffles, impellers, and setpoints before scale up. Process models explore control strategies and failure modes, which cuts experiments and speeds learning.
Your move. Connect instruments and data early. Keep entities and context consistent. Use simulation to de risk choices. Carry that thread into the plant. Before you leave, pick one workflow to digitize, one model to run, and one metric to improve in 90 days.
Keynote Panel: The Great Transformation: How AI, automation and cloud are unlocking intelligent scientific discovery at scale
- How to leverage AI Co-scientists and other AI-driven systems to generate novel hypotheses and accelerate discovery?
- How does the convergence of AI and automation enable scientists to focus on creativity and breakthrough discoveries?
- How can the industry overcome fragmented data silos to build a truly collaborative and efficient cloud ecosystem at scale?
- How do integrated platforms enable global, remote collaboration across different sites and geographies?
Break
Exhibition Hall
Start-up pitches (Round 1)
Working Group 1) Scaling AI in the Lab: Overcoming Data, Trust, and Adoption Barriers
- Move AI from pilots to scale in the lab
- Solve data quality and integration challenges
- Build trust in AI-driven results
- Drive real adoption by scientists and teams
Working Group 2) Using sustainability to drive return on investment
Working Group 3) What is intelligence and how can different industries get involved?
Working Group 4) Healing the human-tech fracture: Change management in global R&D
The Challenge:Large organisations often struggle with the "human" side of digital transformation, as scientists can be resistant to new automated workflows if they feel they lose creative control
Working Group 5) A 2026 Sustainable Lab: Engaging beyond the organisation
Self-driving labs
Interoperability as Catalyst for Lab Automation and AI Enabled Drug Development
Interoperability is a key enabler of laboratory digitalization, automation, and AI-driven analyses. This presentation outlines the stages of interoperability based on international definitions and examines how connectivity, data management standards, and digital transformation enable seamless system integration. Particular emphasis is placed on the interplay between syntactic and semantic interoperability in automated laboratories to ensure consistent data interpretation across workflows involving heterogeneous devices and systems. Through practical examples, we demonstrate how enhanced interoperability supports efficient data exchange and collaboration, fostering innovation in laboratory environments. Attendees will gain insights into the strategic relevance of interoperability for automation and AI-driven pharmaceutical R&D.
Implementing LIMS, MODA, and Spreadsheet validation
First Time Right Lab Design: Unleashing CFD Power Through the Digital Lab Twin
Airflow is one of the most critical safety barriers in laboratory environments, yet many design principles are still guided more by long‑standing myths than by measurable facts. By extending the use of the digital twin beyond static coordination and applying it to simulate the dynamic behavior of laboratory spaces during early design phases, previously invisible airflow phenomena become visible, understandable, and controllable.
In collaboration with HSLU Lucerne, Siemens conductedProject PEARL, a unique large‑scale measurement campaign involving stress‑testing of seven different laboratory airflow configurations. These real‑world results were then compared with an enhanced digital twin that modeled not only geometry, but also thermal and fluid dynamics, particle trajectories, and factors influencing both safety and comfort. The correlation between simulation outputs and empirical data from Project PEARL was remarkably high, demonstrating the reliability and transformative value of physics‑based digital twins in designing safer and more efficient laboratories.
High Stakes, High Precision: AI Assistants for Validation in Biopharmaceutical Manufacturing
In biopharmaceutical manufacturing, critical decisions depend on details buried in reports, specifications, and diagrams where general-purpose AI often misses technical nuance. Standard tools struggle with the multimodality and precision these high-stakes use cases demand.
This session presents how Sartorius and Zeta Alpha have developed “Confidence AI,” a high-precision, agentic RAG assistant for validation services like sterile filtration system validations and cell cultivation. We explore practical design principles for building an AI-ready foundation, improving retrieval across complex documents, and ensuring traceability and expert trust in environments where interpretation errors impact quality and regulatory compliance.
* Title TBC
Developing a tailor-made LIMS - Challenges, pitfalls and success
Synthos collaborates with global tire manufacturers to pioneer sustainable synthetic rubber solutions. Our functionalized SSBR grades enhance energy efficiency by reducing rolling resistance and extend tire life through improved abrasion resistance, supporting compliance with upcoming Euro 7 tire abrasion limits. In the R&D labs we implemented a tailor-made LIMS and ELN system covering synthesis, polymerization, and performance evaluation, integrated with a chemical database for streamlined data access. This talk highlights the challenges faced, the improvement project undertaken, and how efficiency gains in R&D accelerate innovation for environmentally responsible mobility.
Catalyzing Breakthroughs: Bayer’s Shared Lab Ecosystem for Startups
From Quantum Mechanics to Self-Driving Labs: Accelerating Materials Discovery
Past, Present and Future of Regulated Bioanalysis at Abbvie
Integrating LIMS, liquid handing and AI
*Title TBC
Senior Representative, HOK
Start-up pitches (Round 2)
Break
Exhibition Hall
Vision Intelligence: Transforming Laboratory Workflows with AI and Computer Vision
Staige AI cameras empower laboratories to transition from manual oversight to intelligent automation. These systems continuously capture and analyze visual data, supporting applications such as equipment monitoring, sample tracking, safety compliance, and process optimization as well as others. The integration of AI‑vision accelerates decision‑making, enhances reproducibility, and enables laboratories to operate with unprecedented precision and agility.
Robots, Compounds, and Code: Integrating Automation for Next-Generation Chemistry Education
Panel: More than a paper substitute: ELNs from implementation to Interoperability
- Beyond the software, what are the critical steps for a successful ELN rollout?
- How do we ensure the resulting data is properly secured, compliant, and contributes to lab safety?
- How do we achieve ELN interoperability with exchange and migration of data between different systems and institutions?
- How can we leverage AI/LLMs to ensure our assets are high-quality and can be repurposed?
Panel: Labs in Orbit: Can we Scale Research Automation in Space?
- Why would we want to conduct space in microgravity?
- What are '1G bottlenecks' that could be solved in orbit?
- Is the move from space exploration to in-space manufacturing a viable one?
- Currently space research requires a well-trained astronaut, what possibilities could be unlocked by removing the human?
- What are other considerations (inc ‘shipping costs’ and new IP environments)?
- In ten years, will every large research company have a 'Head of Microgravity Research,' or will this remain a niche playground for the few?
Mobile robotics & AI assistance systems
Closing panel: Breaking Bias: Can we create fair and ethical AI?
- How religion, generational differences, gender identity, and disability etc shape experiences in scientific environments and how AI can support inclusion?
- How to embrace diversity to build stronger teams and bridge cultural gaps?
- Can AI/ML be designed to actively support equity and representation in research settings?
- What steps has the EU taken to regulate AI with an ethical lens?
- What are the best practices for ensuring AI in labs supports ethical decision-making and inclusive research?
Closing panel: How can we scale self-driving labs to become the norm across all scientific domains?
ELNs Don’t Make Data FAIR — but Your Implementation Can Bring the FAIRy Tale to Life
Capturing the scientific record in a FAIR fashion is often an assumption of the benefits that Electronic Lab Notebooks (ELNs) can bring. However, no tool can conjure FAIRness from data that was poorly planned or inconsistently captured, and if all your ELN does is replicate poor paper-based practice in an electronic system, then your data might be digital, but it will remain staunchly unFAIR. FAIR begins at the creation and capture stage, and the capacity to produce re-useable data is heavily influenced by the way these digital tools are implemented and used. This presentation explains why FAIR cannot be retrospectively added to your ELN, and extols the importance of good data stewardship throughout the research lifecycle, and how well‑designed ELN implementations can guide researchers toward producing richer, more reusable, and genuinely FAIRer data.
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