Bayer is rapidly expanding its footprint with artificial intelligence

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Bayer is one of the world’s most prominent pharmaceutical and biotechnology companies. It is known for its more advanced technologies and innovations used behind the scenes to produce household staples like aspirin, radiological studies and dyes for critical crop/plant bio-products.

The company is nearly 150 years old, and continues to innovate and expand its global reach and influence with a strong commitment to improving patient care.

Among its latest ventures is its extensive work with AI, notably in partnership with Google Cloud to optimize its core pharmaceutical business.

The main focus area of ​​this work is improving clinical trial and drug discovery processes using Google Cloud’s Tensor Processing Units (TPUs). TPUs are Google’s custom-developed application-specific integrated circuits (ASICs) used to accelerate machine learning workloads; Cloud TPU is a web service that provides access through Google Cloud, and can be used to train extensive machine learning models and perform large matrix operations. Bayer hopes to leverage this technology to compute large-scale chemistry and unlock new insights accordingly.

Bayer will also use Google Cloud’s Vertex AI and Med-PaLM 2 to refine complex clinical trial processes. Namely, these tools will be able to better decipher large data sets, find correlations between disparate data points, and generate tangible insights that can be used to advance the research and development lifecycle.

Guido Mathews, head of the Imaging, Data and AI Research Center of Excellence at Bayer, discussed with me how AI is driving R&D in a big way, while also making the entire process more streamlined, faster. , and scalable. Moreover, he insists that one of the most useful applications of AI will be to help create regulatory documentation, which is currently one of the most difficult processes in research. In particular, clinical trials require extensive paperwork and documentation to be submitted to regulatory agencies to ensure strict compliance. Creating these documents requires significant time and resources and often demands extensive collection of information and submission in a specific format. With AI, there is a remarkable opportunity to automate some of the processes using technology to summarize and synthesize text, organize references, and finally, neatly package documents so that they are ready for submission.

Matthews also describes how Bayer envisions using AI to transform radiology: “Radiology is a growing profession, and medical procedures and imaging have grown significantly. AI can help radiologists achieve better results, find more accurate findings and ultimately provide better care to patients.” Now, through this expanded partnership with Google Cloud, Bayer has access to the technology, healthcare expertise and advanced models to make this vision a reality.

And Bayer’s ambition to innovate in radiology is timely, as the field is increasingly positioned to collaborate with AI. Numerous research studies have shown enormous potential at the intersection of AI and radiology; In fact, just earlier this summer, a major study found that AI algorithms made radiological predictions of breast cancer better than standard risk models.

Undoubtedly, the Google Cloud partnership will be a key unlock and value addition to Bayer’s growing ambitions in this space.

Google Cloud’s director of healthcare and life sciences solutions Shweta Maniyar explains that using Google Cloud’s TPUs for quantum computing is an incredibly important step for Bayer. She also notes that generative AI is a boon for life sciences; With Vertex AI, there are new ways to understand images, enable ambient documentation and understand speech in different languages. With Vertex AI Discovery, there are also opportunities to build custom chat bots and enable organizations in new ways to engage with data and generate insights. Overall, this technology can revolutionize the field of life sciences and biotechnology.

In unison, she thoughtfully explains: “We don’t want to rush the process. People are excited about generative AI—but we need to take the right steps to develop this technology. As slow and time-consuming as this may be, we are focused on keeping humans in the loop and developing this technology in a safe and sustainable manner. She also describes how Google Cloud undergoes extensive testing before rolling out the technology to customers and partners, highlighting the company’s commitment to responsible and secure development.

Ultimately, this is just the beginning for Bayer and its partnership with Google Cloud. Indeed, with proper testing, development and deployment, the applications for this technology and the value it can potentially add to patients’ lives are endless.

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