I had the honor of serving as the DSSS team's subject matter expert for Rave EDC and its integrations in the past. However, I now have the privilege of leading a diverse group of talented senior developers and user access management professionals within the DSSS team. By working together, we aim to deliver innovative solutions that optimize clinical trial performance and drive positive outcomes for our study teams.

I work in the System Managers team and currently support the reporting application CART. I am also responsible for the reporting part of Gemstone and currently working on the reports needed for MVP-2. I am located in the UK and have worked at Bayer for 15 years.

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.

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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 R&D Digital Fluency Program (DFP) is supporting you with learning offerings to build up competencies and further skillsets around digital technologies to enable a competitive and digitally literate organization. At the Digital Fluency Program, we set ourselves apart by offering learning opportunities created by your peers who understand the unique challenges you face in your job. Our tailored approach focuses on real-life use cases, taking our training far from generic and providing you relevant and impactful skill development. In 2020 we, a small team of four people, started our journey with the DFP as part of the R&D Digital Roadmap. Since technologies are ever evolving and impacting our work environment it is more important than ever to foster a culture of continuous learning and enable future opportunities. Thus the DFP learning portfolio includes something for everyone, regardless of your level of knowledge: It offers general awareness programs to enhance basic digital literacy, self-learning pathways on data analysis & visualization and the ability to access online courses like Coursera via the Digital Curriculum. The team ensured the learning objective was met by piloting newly developed learning programs, making use of cross-functional development, and incorporated R&D specific components prior to a broader roll-out in the organization.

With the new head of R&D Community Engagement, RDCE, a new set-up has also been introduced, which newly regulates the tasks and responsibilities of the business partners assigned to the functions, SPOCs, which stands for Single Point of Contact. What is now in scope and what is not? The poster provides information on this.

Professional with extensive experience in analyzing, designing, and implementing novel solutions through the use of Machine Learning for its applications in Research and Development for the Healthcare and Pharmaceutical Industry. I employ my interpersonal communication, business, and technology integration talents to set product strategy and create product roadmaps in an agile environment. • Talent Management • Team-Player • Effective Communicator • Detail Oriented • Analytical Mindset • Computer Vision • Machine Learning • Natural Language Processing • Data Analysis • Statistical Modeling