Smart Automation of Trial and Error to Beat Cancer Sooner

In this essay, I reflect on my engineering work on integrating lab automation with artificial intelligence (AI) to revolutionize cancer research. This novel technology aims to use high-throughput automation to generate reproducible data and analyze it using AI, particularly reinforcement learning. This approach automates the feedback loop between experiments and analysis, finding solutions through trial and error. The aim is to manage the complexity of cancer's genetic mutations and optimize the development of personalized therapies. This essay was submitted to the BioInnovation Institute (BII) & Science Prize for Innovation in 2023.