MolAIcule is an integrated AI–Biology–Chemistry (ABC) company advancing precision therapeutics. We engineer models that learn from multi‑omics, structural, and real‑world data to design higher‑quality candidates and de‑risk R&D decisions.
We fuse generative and predictive AI with wet‑lab workflows to: select targets, design molecules, score liabilities, and guide make–test–learn cycles. Outputs include ranked designs, risk maps, and experimentation plans.
Modern models, pragmatic science, measurable acceleration.
Cross‑link biology knowledge graphs with structural and omics data to prioritize targets and choose the right modality (biologics, peptides, conjugates, or small molecules).
Generate, dock, and refine candidates with multi‑objective scoring: potency, selectivity, stability, immunogenicity, and developability.
Closed‑loop learning from assays and in vivo data to optimize candidates and reduce cycle time from hit to preclinical candidate.