Robert works in TAM and helps providing tools, technologies and supports different kind of systems including GxP relevants

I studied piano performance and toxicology, and am now Master Data Manager at Bayer Pharma in the R&D Master Data Management team of Data Science & AI. I am passionate about team collaboration and rowing. Currently, I'm co-leading the IDMP Ontology, an international cross-industry project with 12 pharma companies for the unique identification of medicinal products to ensure patient safety. Talk to me about common standards and high quality data for better ML and AI outcomes, our next collaboration project, and/or our next jam session at the Bayer Berlin campus.

Thank you for the discussion during the global meeting. This token commemorates the occasion. DS3, Strategy & Venturing Major

I work in ALYCE as Tech and Data Lead. I am working towards ALCYE-Spectrum integration from Core side and also involved in Alyce-MIRA use case. I come from Spectrum [Oracle warehouse] background and also work as Spectrum Utility Programmer. I love playing Cricket, Badminton and TT [Ping Pong]. In my free time I listen to Geopolitical news and do Yoga.

Business Technology Manager in DS&AI unit at Bayer.

Great meeting you!!! I am domain SME in Clinical and Healthcare systems.

Experienced leader in development, validation, and implementation of clinical trial software and processes

Team R&D Master Data Management (MDM) is responsible for the processes and technologies used to ensure the consistency, accuracy, and completeness of critical data that is used across various departments and functions within the R&D organization. MDM plays a crucial role in ensuring the reliability of scientific and clinical data used for research, drug development, regulatory submissions, and decision-making. Key responsibilities include: define and implement data standards & policies, develop and maintain a centralized master data repository, establish data quality controls, ensure data steward- and ownership, manage data integration from different sources and systems, ensure compliance with regulatory requirements and provide training and support for end-users across R&D to ensure proper use and interpretation of data.