Predicts which sequences may bind
- Learns mainly from binding data
- Limited insight into other functional characteristics
AI aptamer design for therapeutics
PentaBind combines proprietary AI with experimental validation to create target-specific, drug-like aptamers engineered beyond binding.
The platform
Our models learn from sequence, structure and measured experimental outcomes. Every design cycle expands the proprietary dataset and improves the next.
Proprietary models design candidates against the performance profile the therapeutic needs.
Wet-lab testing measures affinity, selectivity, stability, localisation and functional response.
Results feed back into the platform to focus designs on target-specific, drug-like performance.
A closed AI and wet-lab loop built on proprietary methods and data
Our advantage
PentaBind learns from multi-characteristic experimental data, linking sequence and structure to the measured outcomes that determine whether an aptamer can become a therapeutic asset.
Aptamers: Engineered for Therapeutic Performance
Strong target engagement at therapeutically relevant concentrations.
Discrimination across closely related proteins and disease-specific forms.
Sequence and chemistry optimisation for performance in biological conditions.
Internalisation, localisation and functional modulation designed into the asset brief.

Built in the lab
Our in-house team generates the sequence–structure–function data that trains the platform. The result is a compounding advantage rooted in experimental evidence.
Meet PentaBindPartner with PentaBind
We work with therapeutics partners to design the performance their application needs.
Start from an important product need and define a target-specific performance profile.
Optimise an existing sequence to increase performance across the characteristics that matter.
Use discovery data to identify higher-value aptamer asset opportunities.