A stronger path through chemical space.
End-to-end AI-powered in silico drug discovery services for pharma, biotech and academia, covering the key stages of early discovery.
Hit identification
Affinity. Novelty. Diversity.
Explore diverse chemical space to identify high-potential compounds for your target.
Our approach brings binding affinity, chemical novelty and scaffold diversity into the screening process, creating a foundation for further optimization.
Two complementary routes
- Virtual screening of large-scale chemical databases.
- Generation of chemical libraries with predefined properties.
What the process brings together
- Small-molecule library preparation and drug-likeness assessment.
- Physicochemical property calculation and prediction.
- Protein modeling, structural quality assessment and binding-site identification.
- Selection of 3D protein structures using benchmark tests.
- AI methods that combine 3D information with physicochemical properties to explore target–ligand interactions.
Hit to lead
Affinity. Selectivity. Safety.
Shape initial hits into more promising leads.
We examine favorable and unfavorable regions of a ligand, using that insight to refine binding affinity, target selectivity and early safety properties.
How we refine a hit
- Expand promising hits into derivative series using generative models.
- Navigate chemical space through similarity-based searches.
- Assess target-specific selectivity and potential off-target interactions in silico.
- Apply structure-based optimization with AI and structure–activity relationship data.
- Evaluate early ADME-Tox properties: absorption, distribution, metabolism, excretion and toxicity.
Lead optimization
Efficacy. Selectivity. Safety.
Refine a lead around the properties that matter for its next research stage.
Our platform supports evaluation of efficacy, selectivity, pharmacokinetic properties and secondary polypharmacology profiles. The aim is to develop a more favorable candidate profile for subsequent experimental investigation.
- Secondary polypharmacology and off-target assessment.
- A broad range of ADME-Tox predictions.
- Molecular dynamics simulation using GROMACS and AMBER.
Computational predictions guide research decisions. Experimental validation is required to establish biological activity and safety.
Start where your research needs us.
Bring a target, an existing hit series or a screening challenge. We can discuss the appropriate methods, inputs and validation needs for your project.
Discuss discovery servicesA better next step for your research.
Bring your target, your challenge, or your next idea. Let’s explore it together.