Bayer Is Rapidly Expanding Its Footprint With Artificial Intelligence

Bayer is one of the world’s most prominent pharmaceutical and biotechnology companies. It is known for creating household staples such as Aspirin, to more advanced technologies and innovations that are often used behind the scenes, including dyes for radiological studies and critical crop/plant bio-products.

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

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

One key focus area of this work is improving the clinical trial and drug discovery process 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 to this via Google Cloud, and can be used to train extensive machine learning models and perform large matrix operations. Bayer hopes to leverage this technology to execute large quantum chemistry calculations and unlock new insights accordingly.

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

Guido Mathews, Head of Imaging, Data and the AI Research Center of Excellence at Bayer, discussed with me how AI can efficiently make use of the immense amount of data that R&D often entails, while also transforming the entire process to be more streamlined, swift, and scalable. Furthermore, he exclaims that one of the most useful applications of AI will be to help generate regulatory documentation, which is currently one of the most onerous processes in research. Specifically, clinical trials often require extensive paperwork and documentation to be submitted to regulatory bodies to ensure strict compliance. Preparing this documentation requires significant time and resources and frequently demands extensive collation of information and submission in a specific format. With AI, there is a notable opportunity to automate some of these processes, using the technology to summarize and synthesize text, organize references, and ultimately, neatly package the documentation so that it is ready to submit.

Mathews also describes how Bayer envisions transforming radiology by using AI: “radiology is a growing business, and there has been a significant increase in medical procedures and imaging. AI can help radiologists drive better outcomes, discover more accurate findings, and ultimately provide better care for 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 aspirations to innovate in radiology is quite timely, as the field is increasingly becoming positioned for collaboration with AI. Numerous research studies have shown the immense potential at the intersection of AI and radiology; in fact, just earlier this summer, a prominent study found that AI algorithms performed radiological predictions of breast cancer better than standardized risk models.

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

Shweta Maniar, Director of Healthcare & Life Sciences Solutions at Google Cloud, explains that using Google Cloud’s TPUs for quantum computing is an incredibly important step forward for Bayer. She also mentions 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 a variety of languages. With Vertex AI search, there are also opportunities to create custom chat bots and empower organizations with a new way to engage with data and insight generation. Overall, this technology can revolutionize the life sciences and biotechnology fields.

Congruently, she also thoughtfully explains: “We don’t want to rush this process. People are getting very excited about generative AI—but we need to take the right steps to develop this technology. As slow and as time consuming as this may be, we are focusing on keeping the human in the loop and developing this technology in a safe and sustainable manner.” She also describes how there is an immense amount of testing that happens internally before Google Cloud brings the technology to customers and partners, further highlighting the company’s commitment to responsible and safe development.

Ultimately, this is just the beginning for Bayer and for its partnership with Google Cloud. Indeed, with the right testing, development and deployment, the applications for this technology and the value that it can potentially add for patient lives is endless.