Predict Off-Target Effects
Before They Reach the Clinic
Physics-aware AI delivers binding affinity predictions 1,000 to 100,000x faster than ab initio methods, with comparable accuracy.
The Technology
AI that understands molecular physics for reliable off-target prediction.
Physics-Aware AI
Our models understand the fundamental symmetries and physical laws governing molecular interactions. This ensures reliable predictions across diverse chemical space.
Dynamic Molecular Signatures
We capture how molecules actually behave—not just static snapshots. This dynamic information reveals binding characteristics that traditional methods miss.
AI Surrogate Models
Get quantum-level accuracy at a fraction of the computational cost. What takes days with ab initio methods, our AI aims to deliver orders of magnitude faster.
Proteome-Wide Screening
Screen compounds against thousands of off-targets simultaneously. Identify selectivity liabilities before committing to synthesis.
Why This Approach
Traditional methods force a choice between speed and accuracy. We provide both.
Ab Initio / DFT
- - Days per binding calculation
- - Limited to small systems (<500 atoms)
- - High computational cost limits screening
- - Static structures miss dynamics
- - Difficult to scale for off-target panels
Physics-Aware AI
- + Orders of magnitude faster
- + Handles full protein-ligand complexes
- + Screen entire proteomes affordably
- + Captures conformational dynamics
- + Built for large-scale off-target screening
How It Works
From compound to off-target profile in three steps.
Input Structure
Provide your compound structure. We screen against our proprietary database of molecular fingerprints.
AI Analysis
Our physics-aware models analyze molecular interactions and binding dynamics.
Get Predictions
Receive binding affinities, selectivity profiles, and flagged off-target risks with confidence scores.
Get Early Access
Currently in benchmarking. Join the waitlist for early access.