My name is Pinky Damani, I'm with Bayer for 14yrs, originally from Mumbai, India, but settled in NJ, USA. I love to play cricket and badminton. Married, 2 children. Currently, working on Spectrum DMW platform with CDSA, Accenture and Oracle, part of Data Transformation and Ingestion Team, I'm very excited and happy to be part of DSA&I. Looking forward to our connect!

Our vision at Data Science Services & Solutions, DS3, is to Enable, Scale, and Operationalize R&D Data Science & AI capabilities to achieve Clinical Research and Development Speed, Efficiency, and Optimization. Learn more about our areas of responsibility, capabilities, strategic priorities, and collaborations. For more information, contact DS3 Head: Abi Velurethu. Artwork created using Stable Diffusion.

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.

Machine learning is a powerful tool that is increasingly being applied to a wide range of sectors and applications, from healthcare and medicine, to finance and marketing, to manufacturing and logistics. It is expected to drive productivity gains, enable innovation, and improve quality and efficiencies in many industries. We as a pharmaceutical company are constantly looking for new ways to improve our research and development pipeline so we can deliver innovative products and therapies that will provide patients with better treatment options. Machine learning offers many opportunities to improve processes and accelerate the discovery of new therapies, and we will continue to invest in this powerful tool to drive future advances in drug development. Our group, Machine Learning Research (MLR), has a proven track record in the field covering the areas of cell painting, large language modelling of proteins, and small molecule research. In this poster we give a broad overview over our projects and collaborations both internally and externally as well as showcasing our direct impact on the R&D pipeline. Artwork created using Stable Diffusion.