Following extensive research with the Lab of the Future Community, the European multi-track congress program includes case studies from exciting biopharma experts, insightful sessions on collaborative research partnerships, and discussions on how to address the challenges of onboarding novel technologies in research, development, and manufacturing.
AI to Innovate
AI/ML are rapidly being integrated into drug discovery and development processes. This track will discuss how large language models, generative AI and AI-driven platforms are aiding target identification, optimization, patient stratification and beyond.
The Connected Lab
In an increasingly collaborative scientific environment, interoperability of systems and connectivity within and between organizations is more important than ever. This track discusses the data platforms and technologies which can allow data sharing, methods to ensure safe and secure data transfer and storage, standardization of data to allow sharing and reuse, and case studies of successful collaborations.
AI to Optimize
AI/ML are rapidly being integrated across the biopharma value chain to optimize processes and increase efficiency from discovery through to manufacturing. This track will discuss how natural language processing, text-mining, large language models and other computational techniques are being applied to free up scientists’ time and allow more time for innovation.
Lab Operational Excellence
Creation of a physical and virtual infrastructure that allows scientists to innovate across the value chain. The track will feature discussions on new developments in lab build and design, lab asset management, application of sustainable working practices in the lab, cross stakeholder research partnerships and use of digital technologies within the lab environment.
Digital Transformation
Digital transformation is revolutionising BioPharma R&D. This is session will focus on the key operational aspects of the transformation. This track will feature innovative platforms and technologies that will facilitate digital transformation, scientific use cases, developing agile methodologies, and taking a data first approach.
Data Strategy
Data strategy comprises of creating a data architecture and infrastructure that supports innovation. Discussions will also examine how to manage and gain insights from the growing volumes of data generated in a modern research lab
Automated Lab
Automation of instruments and workflows to improve efficiency and accuracy, is becoming widespread throughout the industry. This track will discuss automating laboratory workflows through discovery and development, the application of robots, cobots and mobile technologies and the impact of automation on QA and QC processes. The power of digital twins and AR/VR in both R&D and manufacturing for process optimization will also be highlighted.
