The trifecta: How generative AI, automated laboratories and high performance computing are reshaping biological research?

Biological research is undergoing a technological revolution driven by the convergence of generative artificial intelligence (AI), automated laboratories, and high-performance computing (HPC). In this talk, I will highlight how this trifecta is fundamentally accelerating biological discoveries while expanding research capabilities. I will present some of our recent efforts in standardizing biological experiments using robotic systems and scalable open source tools such as the modular autonomous discovery for science (MADSci). Then, I will highlight how we have been interfacing these tools with generative AI and reasoning tools to "self-design" experimental protocols that allow us to design novel proteins and peptides to: bind, recognize and modulate the function of intrinsically disordered regions in key cancer signaling pathways; target specific microbial strains acting as effective antimicrobials; and enhance the catalytic rates of specific enzymes across bio-manufacturing pathways. Together, these applications demonstrate the promise to unlock new frontiers in personalized medicine and synthetic biology, positioning biology as a predictive, engineering-oriented discipline.

Bio

Arvind Ramanathan is a computational biologist at Argonne National Laboratory in the data science and learning division, where he leads the efforts in development of self-driving laboratories for biological research. His research focuses in understanding cellular signaling mechanisms in cancer and infectious diseases.