With the aim of protecting more and more Greek patients, a new product in Cardiovascular Medicine is launched. KERENDIA is now available for patients with CKD & Type 2 Diabetes. Welcome to Bayer Hellas internal Kerendia launch event, focusing on educating & preparing the Sales Team for a successful product promotion in the Greek market. In this event, you familiarized yourselves with the promotional materials & the role plays. This is the first POAP related to a pharmaceutical product. If you received this POAP, you are a True Pioneer in the Web3 space. Bayer is proudly promoting innovative practices. https://www.bayer.com/en/poap-tc

I am a pharmacist from Rio de Janeiro-Brazil and I work as a computational chemist at Bayer since 2021 in the Computational Molecular Design department in Wuppertal. I work side by side with chemists on different projects using our digital tools to design small molecules that maybe one day will help patients! I am passionate about my work and I have the opportunity to also be part of the Steering Group for Transformation and Leadership in the Drug Discovery Science to help transforming the way we work and communicate.

Understanding how compounds affect the disease biology of patients, and which potential side effects could be expected, is one of the core challenges in drug discovery. Transcriptomics (RNA-seq) allows us to measure these compound effects via an unbiased readout of gene expression changes. While „conventional“ analysis of RNA-seq data yields insights into individual compound effects and similarities, deeper connections between principles of compound structure and transcriptome effect elude us. Insights into this connection would help us support project teams with data-driven decision making on compounds. In this pilot, we are bringing together a cross-functional team of colleagues from LST, CMD, SyMOL and DS&AI to tackle this challenge and build a toolkit to enable understanding of ​how compound structure relates to complex gene expression patterns​ and to explore common themes amongst structures or shared off-target/general perturbation effects. This toolbox will become the starting point for other efforts aimed at leveraging multi-omics data in understanding compound mechanism of actions. Artwork created using Stable Diffusion.

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.

Hubble is a pioneering data hub that continuously integrates and enriches terabytes of external scientific textual data to support insight generation along the R&D value chain. It opens opportunities for statistical analyses, large-scale text-mining and other data science methodologies to tease out important details and detect trends within e.g., patents, scientific literature, and grants. The Hubble platform is available Bayer-wide, and offers API access for data scientists. This allows large scale, programmatic analysis as well as integration into processes and platforms. Hubble is a cornerstone of our digital transformation journey within R&D. It serves many users, systems and processes with key data & analyses by answering ~2 million queries per week. We continue to extend the platform to best support insight generation and scientific decision making with a precision medicine focus. For more information contact: Astrid Rheinländer.

Scientific work in Pharma R&D requires a reliable high-quality body of data and knowledge. Bayer Pharma R&D has an extremely large amount of scientific data. The use of a Data Catalog significantly improves the findability of data and serves as a key pillar in the implementation of a comprehensive data strategy.