AI-driven therapeutic design
Design for the drug,
not just the target.
Silicoz builds AI systems for the full therapeutic pipeline, from molecule design to clinical proof.
The Company
Drug development fails late because design tools speak only to structure.
Silicoz encodes what drug development has taught us about manufacturability, safety and regulatory fit directly into the design process. A fundamentally different starting point, not a faster version of what already exists.
Built-in developability
Development requirements are encoded from the first design decision, not assessed after the molecule already exists.
Validated before it matters
Benchmarked against approved therapeutics before your program begins, so the approach is tested against clinical reality before it matters for yours.
Your program, our system
Your target, indication and development priorities define the constraints Camelin designs within, from the very start.
Why VHH
A format that goes where conventional antibodies cannot.
Standard antibodies are large molecules, often excluded from solid tumours, the CNS and inflamed joints where many important targets reside. VHH antibodies, a fraction of the size, penetrate these compartments and access enzyme active sites and buried receptor pockets that IgG formats cannot reach.
VHH domains are also inherently modular. They can be linked in series like building blocks to create bispecific or multispecific therapeutics, targeting multiple pathways within a single molecule. Camelin is designed to harness all of these properties in every candidate it generates.
Our Platforms
From candidate design to clinical proof.
Two AI platforms covering the full therapeutic pipeline. Developability encoded at design. Efficacy and safety validated before dosing.
Camelin
VHH design with developability as a first-class constraint. Structure, stability and manufacturability are encoded from sequence generation, not assessed post hoc.
Developability-aware generation
Biophysical and CMC constraints are part of the generative model. Candidates are shaped for expression, stability and formulation from the first sequence.
Target-specific design space
Epitope accessibility, binding mode and CDR length distribution are tuned to your target. The platform adapts to the structural context, not the other way around.
Benchmarked against approved VHHs
Performance is calibrated against approved VHH antibody therapeutics before each program begins, confirming the approach against known clinical benchmarks.
Clinical AI
Agentic AI that separates drug effect from natural disease progression. Baseline prognostic models are built from real-world data before any patient is dosed.
Real-world prognostic modelling
Patient-level trajectory models trained on RWD/RWE cohorts. Counterfactual baselines isolate treatment effect without requiring a concurrent control arm.
Pre-infusion safety stratification
CRS and ICANS risk scores for TCE and CAR-T programs, derived from pre-treatment biomarker profiles. Stratification informs dosing decisions before the first infusion.
Powered Go/No-Go analysis
Regulator-qualified external control arm methodology. Reduces required sample size and supports earlier, better-evidenced portfolio decisions.
Partnership
Work with us on your program.
Silicoz works with pharma and biotech teams with a validated target exploring VHH therapeutics. We engage early, when design decisions still carry the most weight.
- Candidates built to progress, not just to bind
- Platform benchmarked against approved VHH drugs
- Full documentation for regulatory submissions
We review every inquiry personally and respond within 2–3 business days.
For qualified partnerships only.
Message received.
We review every inquiry personally and will be in touch within 2–3 business days.