Pipeline 1: target → molecules
- Start with a disease-relevant target.
- denovoX explores chemical space through an ensemble of ML approaches.
- Receive prioritized molecule candidates for follow-up work.
AI-native in silico drug design
Move from hypothesis to prioritized decisions faster with lower early-stage cost.
denovoX pairs two high-level pipelines: target to molecules and molecule to targets, helping teams de-risk discovery through computational prioritization before wet-lab investment.
Platform access is currently gated through sales/demo onboarding.
Conceptual flow overview
Pipelines
Two complementary workflows for modern drug design teams
Pipeline 2: molecule → targets
- Start with a molecule of interest.
- denovoX predicts likely human targets and off-target signals.
- Get ranked outputs to support risk-aware decisions.
Benefits
Built for speed, resource efficiency, and higher-confidence prioritization
Lower early-stage cost pressure
Reduce broad experimental search space by prioritizing candidates before intensive wet-lab allocation.
Faster iteration cycles
Move from hypotheses to ranked options quickly, supporting tighter decision loops across discovery teams.
Off-target and adverse-effect awareness
Use predicted target/off-target patterns to spot potential risk signals earlier in exploratory stages.
Who we serve
Designed for teams with different scales but similar discovery pressure
Pharma and biotech
Support portfolio triage and early-stage prioritization with computationally ranked candidate insights.
Contact salesStartups
Focus limited resources on the most promising hypotheses and reduce exploratory dead ends.
Contact salesAcademic labs
Accelerate translational exploration with a practical in silico layer for candidate and target assessment.
Contact salesTrust and validation
Current MVP validation
MVP currently tested by 3 labs at Nazarbayev University.
Built on high-performance infrastructure (GCP, AWS, Azure, Oracle, and similar).
Infrastructure and security
Cloud-native by design
- Deployment flexibility across major cloud environments.
- Attention to practical data-protection controls for collaborative R&D workflows.
- MVP positioning remains deliberately non-committal on formal certifications.
Contact sales
Request a demo discussion
Tell us your use case and team context. We will follow up to scope fit and next steps.