Isomorphic Labs Tech Stack
AI-first drug discovery platform built on AlphaFold, JAX, and PyTorch
Isomorphic Labs applies frontier machine learning to drug design, with a heavy-compute stack (AlphaFold, TPU, GPU, JAX, PyTorch, TensorFlow on GCP). The 28-person research group dwarfs engineering (12), indicating the company is fundamentally research-driven rather than product-driven—drug discovery is the output, not the software. Active projects span greenfield ML models, AI-powered design platforms, and predictive toxicology, while pain points cluster around manufacturing integration and managing the design-make-test-cycle, suggesting the core challenge is closing the loop between computational design and wet-lab validation.
Tech Stack 12 technologies
What Isomorphic Labs Is Building
◆Challenges
- Accelerating drug discovery
- Multi-part drug substances
- Reducing animal testing
- Managing cro network
- Tackling intractable proteins
- Optimising design-make-test-analyse cycle
- Transforming drug design and manufacturing
- Integrating ai discovery with manufacturing
- Lack of efficacy
- Managing external cro team
▲Active Projects
- Greenfield machine learning models
- Induced proximity
- Quantitative pharmacology strategy for drug discovery projects
- Cutting edge machine learning algorithms
- Groundbreaking platform for biopharmaceutical transformation
- Ai predictive toxicology platform development
- Design cmc strategy for complex biologics
- Ai-powered drug design platform
- Optimising design-make-test-analyse cycle
- Large-scale ml experiment tools
Hiring Activity
Department
Seniority
Notable leadership hires: Engineering Director, Chemistry Lead, CMC Project Lead
