27-28 May 2026 | Congress Center Basel
27-28. Mai 2026 | Kongresszentrum Basel
Conference
Konferenz
Basel, 27 - 28 May 2026
Schedule
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5km Fun Run
Meet Congress Center Basel Entrance
More info & registration:https://www.terrapinn.com/conference/future-labs-live/5K-Fun-Run.stm
Day 1 Opening Remarks
Accelerating Drug Discovery: From the AI factory to the Autonomous Lab
What happens when the lab becomes intelligent?
Drug discovery is moving beyond isolated AI tools toward integrated discovery systems: AI factories that train and deploy scientific models, autonomous labs that generate experimental data, and closed-loop platforms that learn with every iteration. This keynote will explore how accelerated computing, generative AI, simulation, and automation are converging to reshape how new medicines are discovered.
From molecular design to experimental validation, we will look at the strategic alliances, technologies, and ecosystem shifts required to turn AI from a promising tool into a scalable engine for therapeutic innovation.
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
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Eliminating Repetitive and Logistical Burdens in Laboratory Operations
What if your scientists and lab operators could finally dedicate all their time and energy to their core responsibilities?Laboratory operations are weighed down by extensive logistical and handling tasks that go far beyond traditional sample management. With mission‑adaptive, complementary mobile manipulators combined with the JAG RES Integration Middleware, this vision becomes reality:
- By servicing multiple instruments and workstations through on‑the‑spot and on‑demand execution via a tool changer, logistics and manipulation are seamlessly integrated – far more efficiently and flexibly than equipping each workstation with a static, underutilized robotic manipulator.
- By empowering pipetting systems to autonomously request labware, tips, reactants, and more, they become fully self‑sustaining, 24/7 workhorses.
- By extending workflows across multiple laboratories, specialized instrumentation can be shared efficiently between labs.
- By transforming cold storage into a shared resource, it becomes accessible to multiple labs throughout the entire building.
Does all this sound interesting? Then join Alain’s session!
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.
Rethinking the Lab: From Infrastructure to Intelligent Operations
Smart efficiency is often decided long before the first experiment starts. Based on insights from real lab assessments, this talk explores why many labs struggle to turn infrastructure, equipment, workstations and building systems into efficient daily operations. We will look at why new-build and renovation projects are a huge opportunity to think beyond rooms and furniture: towards better workflows, smarter use of resources, more transparent decision-making and lower operational effort later on — turning the lab into a system built for future performance.
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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
Embedded, Iterating, Accountable: The Operating Model Behind Real Scientific Data & AI Outcomes
Most life sciences organizations have the data. They have the models. They're still waiting for Scientific AI to deliver. The bottleneck isn'ttechnology —it's the operating model. Spin Wang, Co-founder and Field CTO of TetraScience, will share the unconventional ways of working that actually move the needle: 90-day iteration cycles, forward-deployed Sciborgs embedded inside customer teams, and a disciplined methodology that pairs data infrastructure with scientific use case delivery. Attendees will leave with a practical framework for organizing their programs—and a clear-eyed view of what separates the organizations achieving tangible Scientific Data and Scientific AI outcomes from those still waiting.
From Digital Challenges to a Scalable Pharma Operating Model
Digital transformation in laboratories and CMC has progressed through distinct phases from the digital capture of experiments to the optimization of experimentation in support of better scientific and regulatory decisions. Early initiatives often focused on ambitious technology delivery without consistently changing outcomes. This talk explores the shift toward a business led approach centered on trusted evidence reduced manual effort and measurable value. Drawing on experience across laboratory science digital models and data driven workflows it shows that sustained impact depends as much on people change decision ownership and ways of working as on AI capabilities themselves.
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.
SCIANCE EU Project-Building the AI ecosystem for research
Connecting Robotics, Data, and AI-powered experimentation for Scalable High‑Throughput Experimentation
High‑throughput experimentation increasingly relies on laboratory robotics, yet many organizations struggle to move from isolated automated steps to true end‑to‑end workflows. This talk presents how the integration of SciY’s vendor-agnostic solutions with Chemspeed robotic systems enables scalable high‑throughput experimentation across discovery, development and manufacturing.Real‑world use cases demonstrate improved productivity, reproducibility, and faster decision‑making, supporting a transition toward digitally continuous R&D‑to‑manufacturing ecosystems.
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.
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
Insights to Impact: Leveraging AI to Enable Green Lab Certification
Achieving Green Lab Certification is often hindered by fragmented data and resource constraints. This session explores how AI transforms these challenges into opportunities by converting raw operational data into actionable insights for energy savings. We will examine how AI-developed tools—including intelligent resources designed for every stage of the certification journey—enable teams to streamline the rigorous process. By leveraging these specialized technologies to automate compliance and tracking, critical time is returned to the scientists. Join us to discover how the synergy of artificial intelligence and sustainable science provides the practical framework necessary to drive measurable, scalable environmental impact across laboratories and manufacturing.
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.
The Code-First Lab: Impact of Agentic Programming on Integrated Liquid Handling Workflows
Traditionally lab automation systems have been driven by proprietary, click-and-drag interfaces that create data silos and stifle collaboration. By shifting to unified Python environments and GitOps workflows, we can finally treat lab protocols like software, using LLMs and Agentic Programming to turn complex documents into executable code. This talk explores how breaking away from vendor lock-in and upskilling scientists into code-augmented contributors isn’t just a technical upgrade, it’s the essential leap toward a future of hardware-agnostic, closed-loop experimentation.
From Scientific Data to Food Security. A Digital Scientific Infrastructure for the AI Era
This presentation explores how FAIR digital scientific infrastructure enables collaboration, knowledge integration, and AI-ready research. Dr. Mariana Vaschetto (CDD) will discuss how CDD Vault transforms fragmented experimental data into connected, searchable scientific knowledge. Dr. Ben Allen (MoA Technology) will present MoA’s high-throughput discovery platform combining biology, chemistry, imaging, automation, and AI-assisted workflows to address herbicide resistance and crop loss. Central to this effort is CDD Vault, supporting experimental data management, ELNs, analytics, AI integrations, and collaboration across distributed teams. Together, the presentation highlights how connected scientific ecosystems accelerate innovation and support future global food resilience.
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.
Scaling Operations: Building an Organization Ready for Growth
Turning plastic scrap into pyrolysis oil to produce new plastic polymers
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.
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: From Islands of Automation to One Digital Lab
This workshop reimagines lab automationin a way that defragments islands of automation into a cohesive, interconnected experience, configured and executed from within the Scientist's own planning context. Led by Shaun Latham, Jos De Keijzer and Aleksandra Szczesniak, it will show how workflows which span previously fragmented planning, processing and automation platforms can be configured and orchestrated from within your existing planning tool of choice: you plan the day, press go and wait for your results to return. Behind the scenes, ZONTAL acts as a global orchestrator, integrating devices and software, executing workflows across multiple regional and local islands of automation; all the while automatically capturing, standardising and contextualizing data with centrally governed access, archival, retention and GxP data management. Chemspeed prepares samples, Bruker instruments run, samples are analysed using SciY solutions, then results are documented automatically for review. The outcome: a holistic integrated solution removing fragmented islands of automation in favour of simplicity, intrinsic FAIR and GxP practices, and a truly automated digital lab.
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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
From Data Management to Data-Driven Materials Innovation — Building a System of R&D Transformation
AI is reshaping R&D across industries — and the organizations that will benefit most are those that have built the right data foundation. Yet for many chemistry and materials science teams, fragmented tools and unstructured data remain the norm. This session presents a practical framework for closing that gap: from establishing a structured system of record, through enabling AI-driven discovery, to transforming how scientists work day to day. Drawing on real-world examples from leading chemical and materials companies including Henkel, Marabu, and Applied Molecules, attendees will leave with a clear maturity model and concrete first steps toward making their R&D data — and their AI investments — pay off
From Raw2Ready - Laying the Foundation for Practical AI
In today’s labs, data is everywhere- but turning fragmented, unstructured inputs intoactionable AI ready insightsremains one of the biggest challenges.
Our talk will explore how organizations can:
- Transform source experimental data into trusted, usable assets
- Lay the foundation for AI-ready, future-proof labs
- Enable faster, data-driven decisions at scale
As the industry moves toward connected, intelligent lab ecosystems, the ability to operationalize data effectively into Practical AI application becomes a mandate for all of us that are involved.
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
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.
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.
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.
Empowering the Bench: How Dry Lab Can Drive Smarter, Faster Science
Modern R&D depends as much on data as it does on experiments. Yet scientists often lose valuable time wrangling fragmented information instead of focusing on discovery. In this session, we’ll explore how Benchling’s Dry Lab capabilities are transforming this balance—connecting clean, structured, AI-ready data with agentic automations that accelerate every stage of science. You’ll see how researchers are now using AI agents to process and contextualize lab data in seconds, validate notebook entries automatically, and uncover insights across assays, molecules, and studies that used to take days. We’ll also share how leading research organizations are leveraging Benchling’s unified platform and AI foundation—built in collaboration with partners like Anthropic, Nvidia, and GXL—to empower scientists at the bench and beyond to drive smarter, faster science.
Building partnerships between industry and academia, to advance innovation in robotic in Switzerland
From data to value: Rewiring the Lab of the Future
Why do Digital Lab Initiatives Struggle? How Astrix’s Lab of the Future Blueprint turns Vision into Impact
Across life sciences, organizations are investing heavily in lab digitalization—yet many initiatives stall, underdeliver, or fail to scale. The issue is rarely a lack of tools. More often, it’s the absence of a coherent execution model that connects strategy, architecture, and day‑to‑day laboratory work. In this session, Astrix shares why digital lab initiatives struggle and how a pragmatic, blueprint‑driven approach turns ambitious Lab of the Future visions into measurable impact.
Key takeaways:
- Why digital lab programs falter: common pitfalls such as tool‑centric roadmaps, fragmented architectures, and misalignment between science, IT, and operations
- How Astrix’sLab of the Future Blueprintbridges the gap between vision and execution through an architecture‑led, workflow‑driven approach
- Practical guidance on how to organize solution roadmaps, aligning data and systems, and avoiding pilot‑to‑production traps
- How to translate digital ambition into sustained scientific, operational, and business outcomes
Pioneering the Green Lab Revolution: Novartis’ Integrated Approach to Sustainable Science
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?
The Role of Central Labs in the Future of Blood Testing from Home
Agentic AI in the Lab: How to Unlock the Data-Driven Lab
Break
Exhibition Hall
Workflow Integration Demonstration: From Islands of Automation to One Digital Lab
This workshop reimagines lab automationin a way that defragments islands of automation into a cohesive, interconnected experience, configured and executed from within the Scientist's own planning context. Led by Shaun Latham, Jos De Keijzer, and Aleksandra Szczesniak, it will show how workflows which span previously fragmented planning, processing and automation platforms can be configured and orchestrated from within your existing planning tool of choice: you plan the day, press go and wait for your results to return. Behind the scenes, ZONTAL acts as a global orchestrator, integrating devices and software, executing workflows across multiple regional and local islands of automation; all the while automatically capturing, standardising and contextualizing data with centrally governed access, archival, retention and GxP data management. Chemspeed prepares samples, Bruker instruments run, samples are analysed using SciY solutions, then results are documented automatically for review. The outcome: a holistic integrated solution removing fragmented islands of automation in favour of simplicity, intrinsic FAIR and GxP practices, and a truly automated digital lab.
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Making AI Stick: What Drives 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.
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?
Change that fits: Tailoring transformation to real lab workflows
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.
The Future of the Cloud Lab: Biology, through a browser
The cloud lab is one of the oldest promises in life-science automation: write a protocol, run biology, get structured data back. For fifteen years it has stayed mostly a promise. Two problems held it back. The substrate could not handle real high-mix R&D, and the interfaces made scientists program instruments instead of biology.In this talk, we lay out what changed. The substrate side required reconfigurable hardware, agentic software, and an AI-native data layer. The interface side required something less obvious: exposing the right abstraction layer. A scientist orders a workflow (“express my minibinder in a cell-free system, purify, and return binding data, with QC at each step”). Ginkgo scientists have pre-programmed the biology underneath each modular step, so nobody has to learn a sepcific instrument. We will ground the case in Nebula, Ginkgo’s autonomous lab in Boston, and look forward to where this goes: what biotech R&D becomes when biology is something you call, not something you have to build.
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.
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
AI-Enabled Orchestration for the Intelligent Lab
Lab automation today reaches only a fraction of the scientists who could benefit from it. The complexity is simply too high. HighRes is out to change that. Join us to see how intelligent automation, perception, and physical AI are making autonomous labs radically more reliable and how natural-language interfaces are finally putting advanced automation directly into the hands of the scientists who need it most. Accelerating Science, Advancing Humanity.
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
Importance of automating data alongside physical automation in the lab
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?
Diagnostic innovation, from advanced analytical techniques to machine learning, is transforming medicine. Yet most innovations never reach patients. Why? Becausewe focus on technologies, not on clinical use. In practice, value is created when a tool improves a specific decision, at a specific moment, for a specific patient. Our work shows that successful translation requires more than innovation: it starts with aclear clinical need, uses real-world data, follows phased validation, and integrates seamlessly into clinical workflows. If we get this right, we can turn promising ideas into trusted diagnostic tools that truly improve care and outcomes.
Exhibition Drinks
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Day 2 Opening Remarks
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?
Start-up pitches (Round 1)
10:20 - Chair intro
Start-ups:
10:25 Pitch 1: Achentic
10:30 Pitch 2: Milva
10:35 Pitch 3: Initiocell
10:40 Pitch 4: Alter work
10:45 Pitch 5: NXT Spectra
10:50 Pitch 6: Proofminder
10:55 Pitch 7: FinalSpark
11:00 Pitch 8: GMP4U
11:05 Pitch 9: Alipheron
11:10 Pitch 10: Nium
Break
Exhibition Hall
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) Exploring Biointelligent Lab Solutions: What It Means for Your Industry and How You Can Get Involved
Step inside the biointelligent Lab and explore how innovation emerges at the intersection of biology, hardware, and software. This interactive workshop introduces the concept of biointelligence through practical use cases that demonstrate how biological systems, sensing technologies, computation, and digital platforms can work together to create new forms of value and capability. Participants will reflect on challenges and opportunities within their own industries and collaboratively identify where biointelligent approaches could unlock innovation. The session concludes with concrete pathways for experimentation, collaboration, and engagement within the Biointelligence Engine ecosystem.
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
Chair
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A self-driving, AI-enabled liquid handler with integrated readouts for battery formulation screening
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 Lucerne University of Applied Sciences and Arts, Siemens conducted Project PEARL, a unique large-scalemeasurement 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.
Biointelligence – Towards scalable, autonomous lab solutions
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
Lab-in-the-Loop enabled: Needs and Enablers – AI , IT architectures and interoperability
Lab-in-the-loop (LITL) places the wet-lab experimental process into an iterative loop. Supported by suitable IT infrastructure the right AI tools, and open standards such as SiLA, this promises faster and more effective R&D.
Integrating LIMS, liquid handing and AI
The Campus Advantage: How labs, community and ecosystem access accelerate life sciences innovation
Following the campus tour at Switzerland Innovation Park Basel Area, this presentation takes a closer look at how a modern innovation campus operates within one of Europe’s leading life sciences ecosystems. It highlights the labs, flexible infrastructure and shared spaces that support companies from early experimentation to growth, while showing how proximity to research, industry and entrepreneurial talent creates real value. The talk also reflects on why physical ecosystems still matter in an increasingly digital and AI-driven future of life sciences innovation.
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.
Digital standards: the foundation for scalable, software-driven laboratories
As laboratories accelerate digital transformation, many workflows are still constrained by standards designed for paper, not systems. True digital transformation requires more than digitizing documents, it requires digital standards that are structured, machine‑readable, and built for interoperability.
In this session, USP outlines how digital documentary standards and digital reference data together form the backbone of modern laboratory execution. Attendees will learn how standards designed for system‑to‑system use help enable consistent execution, improved data integrity, and scalable automation across ELN, LIMS, LES, and analytics platforms. The session will also preview how USP standards delivered digitally are evolving to help reduce ambiguity and accelerate adoption, while maintaining scientific rigor and confidence.
EGNATON - the CUBE project
Start-up pitches (Round 2)
Break
Exhibition Hall
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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?
Toolpoint Meeting
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?
ISO/TC 336: Introducing the work on the first International Norm on Laboratory Design
Laboratories play a crucial role across all sectors of the economy. Factors such as a rapidly increasing global population, rising demands for food production, and escalating environmental and climate challenges will only heighten the need for these vital facilities.
ISO/TC 336 represents the first international standard dedicated to laboratory design, with the core goal of creating functional, safe, energy-efficient, and sustainable environments. This presentation will highlight how the framework addresses the complex requirements of future laboratories—where safety, flexibility, the integration of automation and AI, talent attraction, life-cycle cost efficiency, and environmental sustainability are front and center.
Closing session: Workflow Integration Demonstration: How an AI factory fit with the AI of a Lab?
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