Berlin Agenda: Our Plans for the Bio-IT World Conference & Expo Europe

September 21, 2022

September 21, 2022 | Bio-IT World is heading to Berlin next month to explore biotech advancements happening in Europe. With five conference tracks, a plenary program, and an exhibit hall there is much to look forward to. We are marking our agendas to make the most of the packed two days of scientific content and industry best practices. Here are just a few of the presentations and themes flagged thus far. –the Editors   

Plenary Programs 

Three plenary programs over the two days will cover AI, research data, and digital twins—all timely explorations of the future of research. Richard Law, Chief Business Officer at Exscientia, will call for an evolution in our approach to AI. “To unlock the power of AI for drug development and discovery, it is time to remain patient-centric, but stop thinking like humans and allow platforms to be designed to learn and become increasingly powerful and accurate with each incremental piece of data analyzed,” he says. He plans to highlight industry players who are embracing this new “AI first” way of re-engineering drug discovery processes—the leap to full, end-to-end integration of artificial intelligence—to maximize the potential of AI and machine learning to create better medicines faster and smarter. 

Philippe Marc, Executive Director and Global Head of Integrated Data Sciences at Novartis Institutes for BioMedical Research, will share NIBR’s updated data and data management strategy based around four pillars: data culture, treat data as a corporate asset; data management, structure and link data; data science, develop products and insights based on data; and data enterprise, lead the enterprise on data.  

Finally, Peter Coveney, Professor of Physical Chemistry, Honorary Professor of Computer Science, and Director of the Centre for Computational Science, University College London, will bring together AI and our vast amounts of data to explore digital twins. Coveney views digital twins as “an organizational principle for modern predictive and personalized medicine.” He’ll probe the principles on which such digital twins may be constructed and used for clinical and healthcare purposes, the roles of multiscale modeling and simulation, and how artificial intelligence and uncertainty quantification help make actionable predictions from digital twin simulations. 

From there, individual programs cover R&D in Pharma, AI for Pharma, Storage Infrastructure and Cloud Computing, Data Management, and Bioinformatics. While coverage is broad, a few themes have caught our attention.  

FAIR Insights 

FAIR data—data that are findable, accessible, interoperable, and reusable—is a common theme, with several pharma speakers sharing how data are made and kept FAIR in their own organization. Carole Goble, The University of Manchester, will report the results of a study with pharmaceutical professionals who participate in various stages of drug R&D in seven pharmaceutical businesses, and the FAIR-Decide decision making tool based on the study outcomes and Cost Benefit Analysis and Multi-Criteria Analysis. The study’s goal was to gather scientific evidence about how FAIR is currently implemented in practice, what its associated costs and benefits are, and how decisions are made about the retrospective FAIRification of data sets in pharmaceutical R&D.  

Alexander Jung, Boehringer Ingelheim Pharma, will share how the data integration and fairification program in Boehringer Ingelheim R+D supports many of the accelerations needed for the pipeline, enabling troubleshooting, decision making, risk assessment and developability of biologicals development. At Boehringer Ingelheim, data integration serves as an enabler for acceleration to the patient and market.  

Colin Blackmore will present AstraZeneca’s Augmented Drug Design program, a program that won a 2022 Bio-IT World Best Practices Award in May. ADD is driving AstraZeneca’s efforts in the drug design space with the aim of significantly reducing the time to develop candidate drugs. The Augmented Drug Design platform uses centralized data access guided by FAIR data principles, high-performance computational modelling coupled with AI/ML insights, scaled physics-based methods, underpinned by cloud architecture and services to provide our scientists with novel drug design capabilities. Since program inception, these technologies have been deployed against 70% of small molecule projects. 

Other FAIR talks from Alexandra Grebe de Barron of Bayer Business Services, Magdalena Wienken of AstraZeneca, and Felipe Albrecht of Roche promise to give even more insight into how pharma and drug discovery organizations are maximizing FAIR principles for advancing health.  

Clinical Data & Precision Medicine  

The massive preparation of clinical trial data for broad secondary use represents a significant challenge and opportunity for the biopharma industry, and several speakers are sharing best practices to turn clinical data into precision medicine. Gabriel Eichler at Novartis will introduce data42, the pharma’s program to build out its R&D-wide data & analytics platform to enable scientists, clinicians, data scientists, and engineers to bring forth innovations to advance science and medicine.   

A panel of speakers from the Barcelona Supercomputing Center, Genomics England, Argonne National Laboratory, and Frederick National Laboratory for Cancer Research will share diverse viewpoints on patient digital twins, personalized treatment predictions, application of artificial intelligence in medicine, use of clinical information, and translating computing advances for clinical application. The panel plans to provide insights into areas of early success, emerging and potentially disruptive technologies, as well as thoughts on critical elements for sustained application of AI and HPC in precision medicine 

Data Ops & Data Management  

Two years ago at Roche, a diverse team of scientists set out to explore the business and technical challenges and opportunities of bringing operational machine learning (aka MLOps) to pre-clinical research workflows. Now Christophe Chabbert and Elina Koletou will share how they are implementing and operating a state-of-the-art MLOps service tailored to the needs of the pRED (Pharma Research and Early Development) organization in Roche.  

Also, two years ago Kjiersten Fagnan, Lawrence Berkeley National Laboratory, spoke with BioTeam’s Stan Gloss for the Trends from the Trenches column about data management’s role in advancing biology. “We need to have enough information and enough data to be able to interrogate things and to be able to look for patterns. If you don't have some sort of well-organized structure around the data themselves, the pattern matching and finding becomes harder,” she said then. In Berlin, she’ll update those thoughts and explore how distributed data management can support a hybrid bioinformatics workflow.