I work in DSSS and a Subject Matter Expert in Rave and Integrations

Over 15+ years of professional experience as a Product Owner/Software Business Analyst and Process Owner in Pharmaceuticals, Banking, and Health care domains. Working from India for Bayer pharmaceuticals since 2018.

I met Jesus during the Bayer Data Science & Artificial Intelligence, DS&AI, F2F event in Madrid in May 2023. Jesus works at Bayer AG currently as the Head of Business Disruption. If you are into Stranger Things, Breakthrough Innovations, AcceleRed, TeamRed, Science4Berlin, STEM4Health, Hackathons, Biotech, Digital Health, Startups, Entrepreneurship, Intrapreneurship, Web3, Web5, Networking For Health, Science, Technology, Pharma, Exobiology, Space, Science Fiction, Germany, Cuba, you can connect with Jesus in LinkedIn: https://www.linkedin.com/in/yeysus/ Twitter: https://twitter.com/yeysus Meetup: https://www.meetup.com/members/45080772/ Web3: yeysus.eth/.tez/.near Some of his POAPs collections in Welook.io: Bayer: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/1 Corporates: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/2 Animated: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/5 Ladies: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/8 Beautiful: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/9 Great connecting with you!

Morphological profiling with Cell Painting allows an unbiased characterization of cellular states by observing changes in cell morphology. Cell Painting images are information-rich and can guide the elucidation of mode of action, toxicity, and off-target effects, help drug repurposing, indicate differentiation states of iPSC lines, discover new biology and more. However, this technology is data-greedy and computationally complex and demanding. At DS&AI, we enable this technology at Bayer! To this end, we support large data generation campaigns internally and externally, develop novel machine learning algorithms, and create tools for efficient analysis and visualization of Cell Painting data. For more information please contact Paula Marin Zapata or Marc Osterland. Self-painted image modified using pictures from https://quizlet.com/420027050/animal-cell-diagram/ as starting models.

Given the considerable amount of data that is collected throughout clinical trials, it can be asked if this data can be used to improve our understanding of the trial, regardless of outcome. The radiomics pilot seeks to provide a toolkit that is capable of analyzing the different modalities of information found in clinical trials (genome, gene expression, biomarker, clinical information, and imaging information) to derive insights into why a patient may be responding, or why a clinical trial was unsuccessful. The current efforts have focused on clinical trials in oncology, while collaborating with the RED-ONC function. Overall, the project is in its pilot state, and demonstrating a proof of concept, while documenting many challenges and learnings with the development of such a toolkit. Potential directions that could expand this toolbox include deriving the factors that best predict why a patient would stay in a clinical trial, and providing assistance with patient selection of clinical trials. Other potential directions involve suggesting why a particular trial may have been unsuccessful and providing that information back to the drug development team.

The Proprietary Information Management team, PIM, takes care of processes and systems related to either Compliance or Data Governance. Please talk to us if you need help with some cross-functional or collaboration-related topic or if you are interested to learn more about compound-related processes, compliance checks, lab notebook systems and similar things. For more information contact: Friederike Stoll.

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.