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This talk will cover the life science ecosystem, Flagship’s approach to collaborative innovation, and the transformative role of generative AI.
This talk will cover enabling appropriate access to internal and external data sources throughout the pipeline, design principles to enhance collaboration, and the role of enabling technology. Case studies from Kendall Square and Vienna Labs will be highlighted.
In the journey of digital transformation, many companies find themselves hindered by the fear of confronting their current realities. Join us as we delve into the mindset shifts that have propelled our digital transformation journey, offering practical strategies to overcome these struggles and leapfrog into the future.
This presentation will explore key business value drivers that enable and accelerate the scientific data journey. It will focus on strategies for maximizing the quality and usage of data, ensuring it drives impactful decisions and innovation.
When we imagine AI transforming science, we often think of billion-dollar supercomputers designing novel molecules. However, the real revolution may lie in applying AI to fundamental laboratory tasks that have remained largely unchanged for centuries. Spin Wang’s talk explores how the innovative application of scientific AI to everyday laboratory operations – like capturing weights and measures – can unlock billions in value while enabling the foundation for next-generation scientific workflows.
• Learn where the most valuable AI applications may be found in the lab.
• Understand how to identify and execute high-impact automation opportunities.
• Discover why bridging scientific and data expertise is crucial for transforming labs across domains.
The presentation will explore the future of lab research, covering both wet work and laboratory infrastructure. Novo Nordisk’s extensive analysis is informing new lab designs aimed at changing the way research is conducted and driving innovation. While labs are currently human-centric, the focus is shifting toward integrating GenAI for data generation and fostering collaboration between humans and robots. Looking further ahead, the discussion will cover the exciting possibility of fully automated lab processes that remove humans from the loop entirely. The talk will review Novo Nordisk’s experimental and digital advancements, outlining the vision for the future and identifying current blockers to progress.
This talk is a macro view of how I think about the time cycle of the drug discovery process, where are the key latencies within that process, and how I think artificial intelligence augmenting human intelligence can address those latencies. Interwoven through that will be some examples of work we’ve done at BMS.
AI can be applied to solve one of the biggest challenges in drug discovery today: the failure of drug candidates in the clinic. We generate vast amounts of data that have key biological insights, but human analysis is overwhelmed, leading to delays and hindering progress. By applying AI to unravel disease mechanisms, we can analyze vast datasets to create an unbiased map of the underlying biology, empowering scientists to discover novel insights and accelerate R&D. This presentation will explore how AI can optimize the entire preclinical pipeline, from target identification to translational workflows that ensure clinical success, but also detail a practical implementation strategy for integrating these AI-driven approaches into existing research workflows and in the hands of scientists. We will share real examples and learning for successful adoption, demonstrating how to effectively translate AI innovation into tangible improvements in preclinical R&D, accelerating research, reducing costs, and ultimately leading to the development of more effective therapies.
This talk will explore how AI is transforming drug discovery, unlocking new possibilities in therapeutic development. I will highlight how creative risk-sharing partnerships are enabling cost-effective access to AI-driven innovations. Through a showcase of recent achievements and future potential, I will also demonstrate how these advancements are reshaping the future of medicine.
This talk will highlight how AI is transforming drug discovery, from target identification and rank ordering to AI-driven molecular design. We’ll explore how AI is advancing biomarker discovery and enabling precision medicine, paving the way for more personalized and effective therapies.
This talk will outline a Phased Transformation Automation Approach, focusing on the gradual integration of automated systems to minimize disruption and enable continuous improvement. We’ll explore the Digitize First Strategy, where digitizing processes and data lays a strong foundation for future automation. The session will also highlight the importance of Maximizing Solution Potential, ensuring that existing technologies are fully leveraged to optimize efficiency and outcomes. Finally, we’ll discuss how Scalability with Digital Twin technologies can simulate and optimize lab workflows, driving efficiency and resource savings.
This presentation will showcase a “no click” solution developed for scientists in upstream process development, automating the flow of data from sample analysis to dashboard visualization. This approach eliminates manual data collection and management, enabling significant time savings. We will also explore how we are building connections from in-house data models to advanced analytical platforms, including hybrid modelling tools, to enhance data integration and support more sophisticated analysis.
This talk will cover the effects of a decentralized laboratory testing ecosystem, the implications for laboratory accreditation, and the measurable gains across the laboratory ecosystem.
Next-generation high throughput (HT) ELISA system will increase business productivity and flexibility by increasing efficiency, quality, and throughput via automation of traditional ELISA workflows. The HT ELISA platform is a customized automation solution designed to integrate digital information with enhanced liquid handling technology to perform complex, repetitive, and labour-intensive ELISA workflows. This dynamic approach for ELISA workflows will streamline the acquisition of product impurity data and enable HT experiments for early-to-late phase pipeline programs
In this talk, Dr. Sharma will present how healthcare-specific Large Language Models (LLMs) significantly enhance drug discovery efforts. These models are revolutionizing drug discovery and development by streamlining critical processes and optimizing operational timelines. Trained on vast biomedical literature, clinical data, and multi-omics databases, LLMs accelerate early discovery by improving target identification, drug repurposing, and lead optimization. For example, LLMs can rapidly identify novel therapeutic targets or suggest repurposed drugs by analysing molecular pathways and historical trial outcomes—reducing months of manual research to days. Dr. Sharma will also explore how LLMs help design optimized chemical compounds and predict drug-protein interactions with greater precision, expediting lead optimization and candidate selection.
Unleash the potential of AI and synthetic biology with a modern lab framework designed for agility and innovation. This presentation examines the integration of advanced data processing, automation, and emerging technologies to redefine scientific discovery and clinical applications. It will also present a framework and reference architecture that will help you understand how composable architecture and future innovations will fit into the evolving and adaptive lab.
Data is the backbone of biotech innovation, but without the right strategy, its potential remains untapped. To stay competitive, organizations must capture, structure, and standardize data in a future-proof, AI-ready format. This session explores how to capture unstructured information and turn it into a powerful asset by leveraging tools like Electronic Lab Notebooks (ELNs) to organize data and prepare it for AI to extract actionable insights. By building well-structured, reusable, interoperable datasets, companies can accelerate discovery, enhance decision-making, and create a truly data-driven R&D ecosystem. Join us to learn how to optimize your internal and external digital landscapes and unlock the full potential of AI-powered innovation.
Bioprocess Development groups face challenges with complex modalities, faster development cycles, and more experimental data from HT and PAT technologies. Historically, lab experimental data is dispersed in many different instrument software and unstructured files formats requiring substantial manual data manipulation efforts for experimental insights, decision making, process modeling and tech transfer. Here we will share our journey to build and deploy a fit-for-science digital ecosystem within our bioprocess development labs.
In this presentation, you will learn about: The key factors for success in digital transformation programs and common pitfalls to avoid. The Key characteristics of programs that enable success and Examples of iterative approaches for executing a digital transformation roadmap.
This talk will introduce an internal AI-powered chatbot designed to enhance data retrieval and laboratory analysis.
Rob will discuss the significant advancements in ELaiN, an AI-driven digital assistant designed to create experiment content and perform advanced scientific searches. He will highlight the remarkable progress that has been made and how ELaiN has evolved since Lab of the Future 2024.
This presentation will explore the challenges and strategies for managing diverse laboratory equipment and systems in modern research environments. Even small companies can quickly accumulate thousands of instruments from hundreds of vendors, with minor differences in configurations making direct method transfers difficult. The focus will be on how capital hardware is inherently challenging to standardize, and why the emphasis should be on maximizing the impact of these investments. Attention will also be given to harmonizing essential, yet often overlooked consumables—such as sample tubes—across lab groups. Additionally, strategies for reducing the number of digital systems in the lab while enabling seamless data flow between these systems to improve efficiency and collaboration will be discussed.
This presentation will address the challenges of laboratory automation and the need for scalable digital workflows. Often, workflows are viewed in isolation, leading to numerous point-to-point solutions that create complex processes and increase maintenance overhead. Taking a holistic view of the data workflow allows for the simplification of processes, reducing redundant systems and avoiding one-off workflows. This approach not only streamlines current operations but also fosters agility for future advancements in laboratory automation.
In the rapidly evolving landscape of chromatography method development, the integration of modeling approaches has transformed liquid chromatography (LC) into a more efficient and resource-conscious discipline. This talk will elucidate the pivotal advantages of utilizing in silico tools, focusing on retention time (RT) modeling to expedite method screening and optimization, thereby reducing solvent consumption and instrument time. We will discuss the application of various modeling techniques, including physiochemical-based mechanistic modeling (such as solvent strength theory) and statistical modeling, ranging from traditional Design of Experiments (DOE) methodologies to advanced machine learning techniques like graph neural networks that have shown exceptional predictive accuracy for a wide range of analytes. Through practical case studies from our research, we will illustrate the systematic application of these methodologies in pharmaceutical development, demonstrating how computational strategies can streamline workflows and improve separation efficiencies in complex analytical processes.
Live Lab sessions are interactive group discussions which tackle the bigger questions of the day in an open forum to brainstorm ideas and discuss the roadblocks to break-through innovation. They take the format of moderated standing discussions. The objective is to share views and experiences to stimulate new ways of thinking about common objectives.
Best Practice for the AI enabled Lab of the Future
What’s on the horizon?
Getting tools back to the consumers
Agentic AI and software vendor platforms
Lab in the loop / Human in the Loop / AI in the loop
Live Lab sessions are interactive group discussions which tackle the bigger questions of the day in an open forum to brainstorm ideas and discuss the roadblocks to break-through innovation. They take the format of moderated standing discussions. The objective is to share views and experiences to stimulate new ways of thinking about common objectives.
LIMS of The Future
Supporting the scientist in the Lab of the Future
The digitalisation journey – What’s the destination?
Cloud data drag and drop
New technologies and opportunities
Live Lab sessions are interactive group discussions which tackle the bigger questions of the day in an open forum to brainstorm ideas and discuss the roadblocks to break-through innovation. They take the format of moderated standing discussions. The objective is to share views and experiences to stimulate new ways of thinking about common objectives.
Building the Lab of the Future – Building the value case for investment projects
Leveraging future flowing internal investment
Attending to C-Suite initiatives
The value case and AI
This talk will explore the key inefficiencies in biopharma and how enabling technologies like AI, automation, and cloud platforms can drive process improvements. We’ll also discuss the power of a bottom-up approach to change management, ensuring sustainable and impactful transformation across the organization.
This presentation will focus on : The challenges surrounding modern lab environments and how scientific discovery is increasingly driven by data, AI and automation, but labs spend nearly 50% of their time managing data instead of focusing on innovation. A vision for the lab of the future, focused on a dynamic learning system that transforms raw data into real-time insights, integrates AI-driven predictions, and bridges the gap between R&D and clinical outcomes. How to build intelligent labs that accelerate discovery, reduce inefficiencies and empower scientists to solve critical healthcare challenges through advanced data technologies and sustainable practices.
Traditional lab environments often present challenges, from managing complex workflows to ensuring the availability of critical resources. Embark on a day in the Life of a Scientist and explore how cutting-edge technology can revolutionize laboratory operations, empowering scientists to focus on what they do best: discovery
This presentation will outline our transition from manual to automated data capture for biologics. It will highlight the deployment of AI-augmented hit selection, advanced analytics, and insights, demonstrating how these technologies are transforming biologics discovery. Additionally, I will discuss the foundation we’ve built—incorporating data governance, a collaborative network, and continuous improvement strategies—to ensure long-term success and adaptability in our AI-driven research process.
This presentation will provide an overview of the development process for a high-throughput SARS-CoV-2 assay, highlighting the use of automation technologies, including liquid handling robots and plate readers, to streamline workflow and enhance reproducibility. We will discuss how these systems are integrated into our Laboratory Information Management System (LIMS) for seamless data tracking and management, as well as the methods used for efficient data analysis and interpretation.
Learn how Avantor is returning time to our customers through benchtop level accuracy of real-time asset location tracking, removing the need for labor intensive, manual searches.
Identify underutilized equipment allowing for resource consolidation and/or redistribution to optimize asset utilization with asset usage data.
Maximize the lifespan of assets and curb unnecessary maintenance spend by understanding the usage of all equipment, as well as proactively identify maintenance needs to prevent interruptions in science
How increased centralization efforts can cause global efficiencies with local hidden opportunity costs
How we optimize local scientific productivity through process optimization & automation
How this drives engagement, efficiency and productivity
This presentation will outline the strategy for centralizing and digitalizing biologics development to move beyond siloed approaches and address data inconsistencies. By adopting consistent ontologies, development data can be leveraged for deeper insights, driving more informed decisions. The talk will also touch upon the change management efforts necessary to ensure smooth integration and alignment across teams.
This presentation will introduce the Specialized Research in Chaotic Systems (SPaRCS) team, outlining its mission to develop groundbreaking technologies that drive the discovery and advancement of life-changing therapies.
The evolution of lab automation has achieved a remarkable level of sophistication, precision and applicability to a wide and growing range of processes. Yet, successfully automated steps of a value stream often exist as technology and data silos that create manual junctions and bottlenecks. The last mile to reach some level of autonomy in the lab is a complete, cohesive digital representation of the physical and conceptual versions of experimental or testing cycle that includes digital manifestations of goals, “knowledge” and decision making capabilities.
The talk will highlight the role Digital Transformation plays in achieving an Automated Lab of the Future vision , with the journey at Biotherapeutics, Boehringer Ingelheim
In business transitions such as Mergers and Acquisitions (M&A), startup launches, or periods of expansion and contraction, establishing a unified vision is essential. This talk will explore the four key pillars of infrastructure—People, Space, Digital/IP, and Content—with a focus on why People are the most critical element. It will offer strategies to help individuals step back from immediate tasks, recognize their broader impact, and align their efforts with the company’s long-term goals.
Many sustainability initiatives fall flat due to lack of stakeholder engagement, conflicting priorities of scientists, and lack of organizational resources. This talk will explore the successful launch of two My Green Labs programs, it will cover the challenges faced and lessons learned for future roll-outs.
• Significant maintenance and downtime is the result of usage patterns inconsistent with equipment manufacturer recommendations
• See how flow cytometry usage data analytics led one customer to identify hundreds of thousands in extra maintenance, significant downtime, and potentially inconsistent scientific outcomes.
• Noninvasive monitoring and AI-driven insights provide a clear picture of equipment utilization, helping labs optimize performance without disrupting workflows.
In this talk, we’ll discuss how, in a traditional QC laboratory, business processes intersect a patchwork of systems. Through the connected lab, a business user is empowered to leverage digital technologies that transform data into intelligence, utilizing smart devices, connected applications, and predictive analysis
This talk will cover how Novartis managed to incorporate security best practices into their research environment while balancing user needs and minimizing disruptions to research.
Digital transformation is not just a technological shift but a fundamental change in how organizations operate and innovate. At GSK, we embarked on an ambitious journey to raise digital fluency within our CMC operations, recognizing that a successful transformation hinges on effective change management strategies and a people-centric approach.
As GenAI moves past the peak of inflated expectations, life science companies must make strategic AI investments within the DMTA cycle. This talk will explore AI architectures and key considerations for enhancing DMTA, focusing on how to enable a flexible AI environment that evolves alongside data to drive more effective and efficient R&D.
The CMC Process Development is facing multiple challenges from the increasing number of projects, need for agility, cost reductions, data integrity & accelerated development timelines. Data generated during drug development is only partially leveraged to further improve our processes or use it for predictive modelling. Building on a multi-year CMC Digital Transformation program, we embarked on digitizing End-to-End workflows across multiple modalities, platforms & lab families. We focused on three key areas: Operating Model, Value delivery & Scaling. Mohan will share the progress and challenges in each of these areas.