Our goal is to solve all diseases by leveraging AI to transform our understanding of biology and chemistry, enabling us to manipulate and craft solutions effectively.

Machine learning for biology is not limited to drug design; it encompasses a broader potential that significantly impacts human lives.

I believe biology is the most powerful manufacturing platform on the planet, and I want to use it to build innovative solutions.

We aim to create technologies and platform capabilities that are broadly useful, enabling new mechanistic insights and potentially curing diseases.

We aim to create a general drug design engine with AI that can be applied across various disease areas, not just targeting a single indication.

Programming biology goes beyond drug development; it involves understanding how hormones can influence thoughts, feelings, and behaviors in powerful ways.

To achieve transformative drug design, we need several more breakthroughs similar to AlphaFold, focusing on different core concepts of biology and chemistry.

There's significant potential for breakthroughs by merging different subject areas, and I've always aimed to be multidisciplinary in my own work, integrating neuroscience, machine learning, and computer science.

There's a significant opportunity in generating in vivo data, which is currently limited, to better understand drug interactions in real biological systems, and we're seeing breakthroughs in data-generating technology in biology and chemistry that will significantly impact how we model these fields.