The Data Assets and Insights Solutions subfunction, DAIS, consists of a team of dedicated computer and data scientists which combine deep R&D process and domain expertise (biology, chemistry, pharmacy, etc) with advanced computational expertise (software engineering, natural language processing, scalable architectures, bio- & chem-informatics, data integration & visualization, etc). We integrate, enrich and harmonize large scientific datasets to build foundational data assets which are used by the R&D organization and our team to build insights solutions. They address key R&D challenges to improve speed, quality and probability of success of our R&D pipeline. Selected business critical tasks within R&D we are focusing on: - Target identification including holistic assessment - Disease understanding including precision medicine - Pipeline evaluation (therapeutic potential and risks) - Modality selection including identification of tool compounds - Identification of collaboration and in-licensing opportunities For more information contact: Wolfgang Thielemann. Artwork: Licensed pictures.

The SCLM4Future project together with the PRINCE (Preclinical Information Center) project as well as the CONDAS (Connecting Data for Science) team is an excellent example for a successful cross-functional collaboration between CD&O, RED preMed and DS&AI within Research & Development but also between Platform IT and external partners. Together the team achieved to overcome legacy manual processes, redundant maintenance work, and functional silos by introducing new digital solutions and concepts with a strong collaborative mindset. The newly released SCLM 2.0 (Standard Codelist Maintenance) & PTO (Preclinical Terminology and Ontology) systems will enable our organization to improve the quality of controlled terminologies with regards to standard codelists and codes while reducing maintenance time and effort. This will have a positive impact on the code/codelist consistency across clinical and preclinical, as well as the compliance to regulatory requirements (e.g. CDISC (Clinical Data Interchange Standard Consortium) Controlled Terminology). The approach to share our knowledge as well as our efforts across functions will be an important step to archive our goals to increase data quality, interoperability and reusability – or to make a long story short: to make our data even more FAIR. For more information contact: Daniela Bergann.

Recent focus has been on streamlining and optimizing the clinical operations system landscape. To support the initiative, our key business capabilities related to clinical operations are consolidated on one core platform: Gemstone. Gemstone is a Software as a Service provided by Veeva and contains modules of their Vault Clinical suite. Where possible the system remains as close to "out of the box" as possible to align with industry standards and to reduce the complexity for the 3 general releases provided by Veeva. eTMF, Startup, Monitoring, Site Connect, Feasibility components are already live. The latest Gemstone „Ruby“ went live over Eastern (April 23). IRIS is now retired, and Issue Management, Monitoring, and Study Risk Management and Study Training are available in Gemstone with more capabilities to come. Gemstone interfaces with over 50 systems and is closely integrated with RAVE, RAVEN, BRAVE and other systems. Gemstone provides a modern technology foundation with API capability, allowing connection via the Integration Hub, a bespoke PaaS solution with a unified data integration layer. As not all systems are as advanced, the Integration Hub provides a database facade that allows backward compatibility to cater to those legacy systems.

ChemogenomicsDB (CGDB) and Älixir are prime examples of creating data assets and insight solutions to help improve digital and data capabilities, enhance scientific productivity, and invigorate early pipeline. Using our products, Bayer R&D colleagues can - access to a broad range of data assets essential for solving key drug discovery questions - explore integrated biomedical and chemical data for scientific curiosity, inspiration, and knowledge discovery - generate insights with the assistance of interactive visualizations for evidence-informed decision making