Mapping interactions took years. A custom AI pipeline analyzed 1.7M predictions in 3 months, finding 40,000 high-confidence pairs.
A research laboratory at a prominent medical school aimed to map the human proteome, consisting of 20,000 proteins and potentially one million complex interactions.
Manually determining protein structures previously took years, creating a bottleneck for understanding disease mechanisms. While AI tools like...
“We’ve had so much success with AlphaFold in our area of biology that we’ve sought to expand it beyond the interest of our lab to the problem that almost all biologists think about, which is how proteins need to interact with each other throughout the human body. We're going from a few hundred proteins interacting in a few hundred ways to the scale of the entire proteome: 20,000 proteins interacting in perhaps a million ways.”
Graduate medical school and center for biomedical research.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Harvard Medical School's Protein interaction discovery is part of this use case:
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Mapping interactions took years. A custom AI pipeline analyzed 1.7M predictions in 3 months, finding 40,000 high-confidence pairs.
A research laboratory at a prominent medical school aimed to map the human proteome, consisting of 20,000 proteins and potentially one million complex interactions.
Manually determining protein structures previously took years, creating a bottleneck for understanding disease mechanisms. While AI tools like...
“We’ve had so much success with AlphaFold in our area of biology that we’ve sought to expand it beyond the interest of our lab to the problem that almost all biologists think about, which is how proteins need to interact with each other throughout the human body. We're going from a few hundred proteins interacting in a few hundred ways to the scale of the entire proteome: 20,000 proteins interacting in perhaps a million ways.”
Graduate medical school and center for biomedical research.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Harvard Medical School's Protein interaction discovery is part of this use case:
Related implementations across industries and use cases
Physics simulations took weeks to screen libraries. Boltz-2 runs 1,000x faster, cutting this to hours with 2x precision.
Medicinal chemists had no way into binding simulations—that was computational chemistry's territory. AI gave them a browser and a button.
Navigating 10^1000 variants was impossible. A model designed novel proteins, boosting stem cell marker expression >50x over controls.
Physics simulations took weeks to screen libraries. Boltz-2 runs 1,000x faster, cutting this to hours with 2x precision.
Medicinal chemists had no way into binding simulations—that was computational chemistry's territory. AI gave them a browser and a button.
Generic AI mangled chemistry terms; manual translation took months. Glossary-tuned AI now earns enough trust to publish before human review.
A maze of disconnected systems obscured global trial visibility. Now, a digital twin guides AI to automate heavily regulated workflows.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.