What do we need for AI to help us get reliable research findings in short, predictable timelines?
While innovations that require seismic shifts in ways of working require years to reach their full transformative potential, we’ve seen some promising progress. Together with massive multi-omic datasets and new modalities, AI is helping identify a huge number of diverse targets.
Yet with one problem solved, comes a new challenge. This potential wealth of potential therapeutic programs has brought new pressures to target validation and hit identification—stages that both rely on critical-path functions that require running experiments in the wet lab.
Removing inefficiencies in this area requires a combination of multivariate experiments, automation, and AI. Done right, it could expedite many more high-quality programs to the clinic, and then AI will be a substantial step closer to delivering on its potential.
iCMC Digital Transformation program is a global top program aiming at digitizing all R&D labs within Sanofi, covering 10+ countries and 2500+ users overall. The value it is bringing to our company is huge and goes from data integrity to faster time to clinics and time-to-market. It is based on a data-centered end to end approach, covering data capture from lab equipment and workflows automation, data governance, data integration, and data consumer.
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.
Interdisciplinary research collaborations carry big potential for delivering breakthrough innovations urgently needed to tackle the world’s complex challenges impacting humanity: from overcoming a global health crisis to combating climate change.
To unlock the vast potential of innovation, it is essential to embrace scientific exchange and provide collaborative engagement projects, platforms, and communities.
Join this session to explore how Bayer leverages science collaborations and the collective innovation potential of its 16 000 R&D employees through various formats, e.g., via its Life Science Collaboration Program (LSC) and discuss how we can collectively enhance the efficacy of partnerships to shape a better future.
We will discuss approaches and learnings on these topics through the lenses of business leaders, scientific users, IT delivery and data management stewards across different scientifically driven market verticals such as Pharma, C>, Food and fast-moving consumer goods (FMCG
Doing more with what you have requires a new level of “coopetition” to unlock the full capabilities of your lab operations. Get a fresh perspective on optimizing your operational digital ecosystem – encompassing people, assets, consumables and samples. Gain valuable insights into running a lab that meets the needs of both scientists and lab managers alike.
AstraZeneca’s High Throughput Screening facility recently made a significant move from Alderley Park, Cheshire to The Discovery Centre in Cambridge. This relocation involved the installation of four new automation platforms directly into The Discovery Centre, as well as the transfer of five automation platforms from Cheshire to Cambridge.
Here we will delve into the challenges encountered during the initial installation phase and explore how the insights gained were leveraged for the subsequent relocation and installation. These efforts were crucial in ensuring the seamless continuation of scientific activities, minimizing any impact on project delivery and ensuring the platforms were ready for planned scientific activities.
AI-based real-time analysis of cell fates – CellVoyant has developed AI-technology using live cell imaging to accurately monitor and analyse cell behavior in real time, improving insights into stem cell development to aid cell therapy development.
Enhancing differentiation protocols with AI – We are combining AI with advanced experimental design to fine-tune the experimental protocols for differentiation stem cells, aiming for better quality and reproducibility.
Toward an automated, AI-driven stem cell lab – Our roadmap includes developing a fully automated lab that uses AI to continuously improve and optimise differentation protocols, aiming to streamline operations and enhance research outcomes.
The novel AI toolkit presented in this work is a pioneering endeavor to connect the dots from drug development to treatment selection within the realm of cancer care.
At the foundation of our approach lies the utilization of causal models in the target discovery phase, which are validated using CRISPR screening on various cancer models to confirm the relevance of identified targets for therapeutic intervention.
Everyone’s heard the buzz about Connected Labs – streamlining systems and data flow – but there is much more beneath the surface. Join us as we explore the untapped potential of Connected Labs, revealing what they really are and why they’re crucial for scientists and technologists. Discover the unique scientific drivers and unexpected outcomes that go far beyond simple connectivity.
Historically data generated during pharmaceutical development has been stored in data siloes separated by business processes, batches and disconnected systems. In order to accelerate pharmaceutical development and to meet future regulatory requirements, there is a need to structure and connect relevant data on drug substance and product. The presentation will outline our future vision and first steps to connect lab data in knowledge graphs.