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.

Drug design is complex, with numerous bottlenecks before reaching clinical trials, and we need to innovate in this space to improve the process.

As AI-designed drugs enter clinical phases, we must rethink how we engage with regulatory bodies and streamline the clinical trial process.

By 2050, we envision a fully automated lab capable of simulating drug interactions with high accuracy, significantly speeding up drug discovery processes.

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 innovation in designing clinical studies to quickly gather initial data from human trials, allowing for faster assessments of whether a drug is likely to work.

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

In academia, there is less focus on hardcore drug manufacturing aspects like pharmacokinetics or toxicology, but there is significant interest in molecular glues, machine learning models, and new drug concepts.

Science has yet to fully understand what it means to be human, and this gap is where science will learn the most about our existence.