Christophe Chabbert

Team leader of the global Data and AI engineering team Leader of the establishment of a Data and AI strategy for the Octapharma group • Introduction of global strategy & governance for AI use and Data management • Implementation group-wide AI and data management platforms • Vendor management and negotiation (cloud, service providers, consultancies) • Educational and ideation sessions with senior leaders on genAI Impact ‣ Significant financial gains through data-driven improvements of critical processes ‣ Acceleration of the R&D development cycles ‣ Reduction of IT operational footprint

Productive deployment of 13 Machine Learning (ML) products (cloud & on-premise). Built a ML platform for scalable and automated deployments (incl. generative AI). • Design of a ML operations strategy with leaders in Pharmaceutical Research • Leadership of a cross functional team of 12 contributors • Introduction of agile methodologies (Scrum) • Creation of data scientists and IT professionals communities Impact ‣ Generation of >2 million monthly predictions from >150 predictors ‣ Distribution of ML predictions to >500 scientists in multiple software solutions ‣ Acceleration of drug discovery and development

Product ownership focusing on hybrid data and systems integration Digitalisation of key experiments in oncology. • Deployment of the first ML Operations platform in pre-clinical research. • Design of a strategy for digitalisation of key experimental datasets Impact ‣ Productive release of new ML compound property predictions in drug discovery

Introduction of a FAIR data framework in Large Molecule Research. Matrix leadership in digitalisation projects • Automation of data visualisation workflows • Establishment of workflows to systematically collect and annotate key datasets • 3rd best performance in an internal ML competition to identify biomarkers • Release of data visualisation dashboards to select drug candidates Impact ‣ Standardised, reproducible and documented selection of compounds and cell lines ‣ Improvements of the data-driven strategy to design new compounds

Automation of Next Generation Sequencing data processing. Research project support in oncology (cancer genomics) • Technical leadership for bioinformatics and biostatistics • Coordination of capability development with ETH IT services Impact ‣ Publication of 3 peer-reviewed articles

Identification of predictive biomarkers Support of drug projects transitions to clinical trials thanks to data analysis • Bioinformatics leadership of an academic collaboration in pharmacogenomics • Establishment of data visualisation and data management solutions Impact ‣ Successful transition of drug project to Lead Optimization and Phase I ‣ Publication of findings in peer-reviewed articles

Development of high-throughput next generation sequencing protocols Statistical analysis and integration of large datasets • Design of collaborative research projects Impact ‣ Publication of key findings in peer reviewed journals ‣ Public release of key datasets for malaria research

R&D Biotechnologies, technology watch • Scientific, technical and economical analysis of current technologies of biofuels synthesis

Reducing the intrinsic evolvability potential of protein coding genes • Design of a systematic method to redesign protein coding gene sequences

Development of an image processing platform to monitor large scale cell cultures in the Manufacturing Technologies Department • Development of mathematical algorithms to segment mammalian cell culture images and monitor cell culture expansion • Experimental validation of the mathematical tool via small-scale experiments • Development of a user-friendly interface

Towards the development of a robust inter-cellular communication system based on outer membrane vesicles • Synthetic biology research project development • Team management, sponsor prospection, budget and resource management • Mathematical modeling of genetic network interactions