How can emerging technology and disease immunotherapy possibly have anything in common? While both are among the most transformational areas of modern science, 30 years ago, these fields were all but ridiculed by the scientific community. This interesting information came to us from TechCrunch in their article, “The convergence of deep neural networks and immunotherapy.”
Machine learning and immunotherapy have more in common than you would think. Immunotherapy leverages the versatility and flexibility of the immune system to fight different types of cancers. While the first immunotherapies showed results in a few cancers, they were later shown to work in many other cancer types. Artificial intelligence (AI) utilizes flexible tools to solve a wide range of problems across applications via transfer and multitask learning. These processes are made possible through access to large-scale data.
Life sciences companies and labs are building large-scale datasets with tens of millions of immune cells labeled consistently to ensure the validity of the underlying data, similar to the ImageNET dataset that has been integral to how far neural networks have brought computer vision today. Using that technology for various applications bridges the gap.
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