Digital Twins

3 posts

Stack diagram showing the four layers AI drug discovery depends on: a data base layer of genomic, clinical, and experimental data; a pathway layer with cell-type-specific and time-resolved edges; a digital twins and simulation layer with virtual cells and organ-scale models; and AI drug discovery outcomes including target discovery, lead optimization, and in-silico Day Zero success. On the right, a multi-omic foundation model functions as an AlphaFold of pathway state.

AI Drug Discovery·April 18, 2026·4 min read

The Pathway Layer: What AI Drug Discovery Needs to Build Next

AI drug discovery's biggest gap isn't models — it's pathway infrastructure. Six investments biology needs before AI can deliver on its promise.

Animated visualization of a Scientific Visual Operating System for drug discovery — molecular structures, protein interactions, and AI-rendered scientific worlds running in real time

AI Drug Discovery·April 14, 2026·2 min read

The Scientific Visual OS: When NVIDIA Renders Drug Discovery

Graphics cards turned game worlds into clarity. The same engine could turn drug discovery into a fluid, real-time visual workflow. The Scientific Visual OS thesis.

Diverse group of tech and science professionals collaborating — illustrating the bridge between computational expertise and scientific domain knowledge in AI-driven drug discovery

AI Drug Discovery·April 18, 2025·1 min read

Uniting Tech and Science Geeks in AI Drug Discovery

Three strategies to bridge AI/ML expertise and scientific domain knowledge in drug discovery — collaboration hubs, shared data platforms, and AI-first experimentation.