Wen Zhang Base: Chengdu, China Working experience in Bayer: Apr 2023: Data Science Services & Solutions Oct 2019-Mar 2023: Medical Writing Digital Innovation Apr 2019-Sep 2019: Medical Writing Operations

I am a Programmer from India with a passion for coding and a deep understanding of several key technologies. My expertise is in Oracle Apps, PLSQL, Oracle Database, Python, and Azure. I have gained experience working with large databases in Core Banking tool, to working with more than 10 million Customer records in Telecom domain, enriching my skills in Performance Tuning. As a technology enthusiast, I am always eager to learn new skills and explore emerging trends in the field with particular interest in creating chatbots. Currently I am working in Spectrum automation utilities, and I love to work in a dynamic environment and enjoy collaborating with other talented professionals to solve challenging problems and drive innovation.

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.

Collaborations with external partners may lead to joint legal rights for compounds and data, which may restrict reusage in other projects. With the increasing number of collaborations at Bayer and with advancing time, memories of the project details fade, and reconstruction of the status will be nearly impossible. Therefore, we aim for a system to document the role of compounds, which will facilitate decisions on further usage in other collaborations. For more information contact: Miriam Wollenhaupt. Images taken from Microsoft Office free for use pictograms.