Target intake
You give us the analyte — a protein, peptide, small molecule or even a cell.
AI powered molecular wisdom
AI driven biosensor development — months of discovery, done in days.
MOLwise designs the recognition element at the heart of every biosensor. Generative models propose the binders, physics-based screening ranks them, and the lab confirms them — one continuous loop instead of a year of trial and error.
Days
From target to candidate binder
10⁹+
Sequences screened in silico
pM–nM
Target binding affinities
1 platform
Design, rank, validate
The pipeline
Four stages, one feedback loop
Generative design
Sequence models propose aptamer and peptide libraries tuned to the target's binding pocket, not to a random pool.
In-silico screening
Docking, molecular dynamics and learned affinity predictors rank billions of candidates down to a shortlist of tens.
Wet-lab validation
The shortlist goes straight to binding assays and electrochemical sensor integration. Results feed back into the model.
Why MOLwise
Discovery that compounds
Design-first, not selection-first
Classical SELEX is a months-long search through randomness. We start from structure and learn what should bind before a single tube is filled.
Closed-loop learning
Every assay result retrains the ranking models, so each campaign makes the next one faster and more selective.
Sensor-aware chemistry
Candidates are scored for real device performance — surface immobilization, signal-to-noise, drift — not affinity alone.
Built for deployment
Outputs are handoff-ready: characterized binders, assay protocols and integration notes for point-of-need biosensors.
Have a target that needs a binder?
Tell us the analyte and the matrix it lives in. We'll come back with a feasibility read and a timeline measured in days.
Talk to our team