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Digital Technologies in Pharma R&D at Bayer r&d technology

Transcript of the video shot before the COVID-19 pandemic:

“Everybody hears, reads, and speaks about artificial intelligence, the power of advanced analytics on top of big data, and how these techniques will change the world as we know it in the most dramatic way. Today, we want to tell you how we see things, how we use these techniques to make our Pharma R&D more efficient, to find innovations. not findable without, and to crack some real hard nuts not crackable without. We are the Digital Technologies Team, 80 digital natives driving and applying data science in a multidisciplinary environment. All that towards novel, innovative, fast to the market solutions for our patients. And the best thing: We have lots of fun doing so.

Talking about data – we support the transformation of unstructured into structured and harmonized data. How do we do that? We have a powerful ontology management platform and a cutting-edge natural language processing technology in place. And with that we extract key information from legacy and external data to enable you to create findable, accessible, interoperable and reusable data in the future. We developed novel representations of big data to gain new insights. For example, to find new links between targets and diseases.

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These links between targets and diseases are substantiated now by medical data science teams. We analyze large scale molecular data in humans and animal models. In this way, we enable data-driven decision making. With human disease understanding at its core. We deliver value to the Pharma pipeline by identifying the most relevant drug targets, the most valuable indication spectrum and suitable biomarker candidates that identify those patients with the highest benefit from our drugs.

Yeah, talking about drugs, we focus on discovering, designing and optimizing new drug candidates with the help of computers and in close collaboration with experimental scientists. Using computers, we can characterize molecules and their interactions before they are even made, and in that way, we focus experimental efforts onto the most promising ideas. And we decide what’s most promising based on a diverse toolbox of computational methods ranging from machine learning to physics based methods. To do that, we also closely collaborate with others like our colleagues from machine learning research.

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The primary function of the machine learning group is to develop new algorithms to accelerate our discovery processes at Bayer. For example, we have recently found a new computational representation of molecules which we used to predict their properties. We are also collaborating with our colleagues from the screening departments where we help them to extract insights from their large scale imaging data.

It is our goal to foster a passionate and collaborative digital innovation culture within Bayer Pharma R&D and beyond. Together with our friends in DT, we develop creative and lean digital solutions to solve scientific business problems. These digital solutions could be scientific apps, insightful data visualizations or optimized algorithms.

It’s exciting to co-develop our R&D digital strategy and portfolio, including a road map with prioritized activities that have a significant impact on our business. Digital fluency options help us to continuously learn and grow in our fast-changing world.

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We harness high-throughput sequencing technologies to enable data-driven decisions across our R&D portfolio. We also advance Bayer’s commitment to open innovation, right here in Boston.

Now you got a glimpse of what we do, how we do it, and what our purpose is. Want to know more or even collaborate driving Digital R&D? Looking forward talking to you! :-)”

#TeamBayer #Pharma #DigitalTechnologies #DataScienceForABetterLife #HealthForAll #HungerForNone #welivelife .

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Digital Technologies in Pharma R&D at Bayer

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