At Arc Institute, we are focused on applying high-throughput scalable technologies to understand multi-system interactions, particularly at the neuro-immune interface.

AI for science is a major focus, as it can significantly enhance productivity and lead to new scientific discoveries.

Multidisciplinary research will be crucial in the next decade, combining expertise in areas like AI or machine learning with fields such as biology, chemistry, or mathematics.

In a hundred years, Science Exchange will continue to enable scientific breakthroughs by providing infrastructure for collaboration among researchers.

My vision extends beyond just creating better drugs; I aim to build a comprehensive understanding of biology at all scales.

Building a diverse team of experts in AI, chemistry, and biology is essential for questioning traditional approaches and fostering innovation in drug design.

AI can bridge different scientific modalities, enhancing our understanding of diseases like cancer by integrating imaging, genomics, and other data, and can help integrate sleep data with cardiovascular health and oncology to prevent cancer, which is challenging in traditional healthcare systems.

AI is being utilized to generate peer-reviewed scientific papers and breakthroughs, significantly accelerating scientific discovery.

AI is already helping scientists become three times more productive, indicating its potential to autonomously conduct scientific research in the future.