From target identification to lead optimization — accessible computational science for every researcher, not just those with million-dollar budgets.
Traditional computational platforms cost $500K–$2.6M annually, putting them out of reach for individual researchers and small labs.
Free tools like AutoDock and RDKit require extensive technical expertise to set up, integrate, and maintain effectively — a barrier for most scientists.
Over 100,000 researchers globally fall into the gap — needing more than basic tools but unable to afford enterprise solutions.
Three stages of drug discovery, powered by AI.
AI-powered analysis of disease pathways to identify and validate promising therapeutic targets.
Virtual screening of compound libraries with molecular docking and binding affinity predictions.
ADMET property analysis and molecular modifications to optimize lead candidates.
Accelerate your thesis research with professional-grade computational tools without the enterprise price tag.
Validate hypotheses faster and generate preliminary data for grant applications.
Enterprise-quality workflows scaled for academic budgets and smaller team sizes.
Breaking barriers to give researchers worldwide access to cutting-edge discovery tools.
We integrate established computational tools with AI-driven analysis to deliver reliable, actionable results.
Accurate protein structure predictions for target analysis
Industry-standard molecular property and docking calculations
Intelligent interpretation and decision-making support
Connected to PubChem, ChEMBL, DrugBank & more
We’re currently focused on launching LongeviTwin. The Drug Discovery platform for individual researchers is planned for release 18–24 months after LongeviTwin launches.
Join LongeviTwin Waitlist →