World’s first AI-driven anti-metastatic drug discovery platform
Purpose-built to design and de-risk drugs that suppress metastasis by targeting the molecular drivers of invasion, EMT, and metastatic spread.
The Limitations of Modern Drug Discovery
The pharmaceutical industry faces sky-high R&D costs, decade-long timelines, and failure rates that would bankrupt any other sector.
The Translation Gap
~90% of investigational drugs fail between Phase I and approval.
Cost Explosion
US $2.23 billion—the average cost to bring one drug to market in 2024.
Timeline Crisis
10–12 years from target discovery to first patient dose.
AI Opportunity
AI drug-discovery market hit US $6.9 billion in 2025.
The Opportunity
AI-powered platforms like Vecentra compress pre-clinical timelines, cut screening costs, and surface safer, more potent candidates by predicting potency, selectivity, and toxicity before synthesising a single molecule.
Why Vecentra Wins
A unified platform where biology, chemistry, and AI converge to de-risk discovery.
Prioritize Stronger Leads
AI highlights compounds with the best balance of activity, selectivity, mechanism, and metastasis-modifying effects.
Design Optimized Molecules
All biological and safety signals converge to generate drug candidates engineered for maximum efficacy and minimal risk.
Predict Safety Early
Assess toxicity risks for both the drug and its predicted metabolites across key organ systems.
Understand Drug Impact
Downstream omics and mechanistic predictions reveal how each molecule influences EMT and metastatic potential.
IC50, EC50 & Ki Prediction
AI-powered binding affinity predictions for drug-target interactions. Perfect for medicinal chemistry research and academic studies.
Generative AI Drug Design
Generate novel drug candidates with optimized potency, selectivity, and safety profiles using advanced molecular generation algorithms.
Lab-Ready AI for Universities
Scalable AI tools for academic research labs, pharmaceutical R&D teams, and students learning computational drug discovery.
Data Input
SMILES, Sequences, Assays
AI Prediction
Binding, Activity, Toxicity
Generation
Novel Compounds
How It Works in Practice
Vecentra is an AI platform that helps you decide which molecules to advance and why. We unify multi omics signals with predictive models that estimate ligand-to-protein binding, activity in relevant assays, and cytotoxicity.
Load & Harmonize Data
Load structures, assay summaries, and omics context. Our feature store harmonizes SMILES, protein sequences or pockets, and study metadata.
Run Predictors
Models inspired by ChemBERTa and Chemprop-style GNNs estimate potency, cytotoxicity, selectivity, and pathway impact.
See Expected Biology
A downstream-omics head predicts direction and magnitude of key signatures so you can anticipate in-vitro trends before spend.
Design to Spec
The generative module proposes candidates that meet your constraints for potency, logP, TPSA, alerts, SA score, and predicted liabilities.
Close the Loop
Wet-lab results stream back in for continuous learning. Everything is logged in the Reproducibility Hub with datasets, parameters, model versions, and QC.