Excelsior Sciences provides a machine‑ready chemistry platform that uses proprietary “smart bloccs”—modular, tokenized building blocks for carbon‑carbon bond formation—to enable fully automated synthesis of small molecules. The system integrates robotic synthesis, purification, and assay preparation with closed‑loop AI workflows, allowing pharmaceutical, biotech, and materials companies to accelerate discovery and scale production without manual intervention.
Funding
Funding not disclosed
Founders
Product
Problem
Small-molecule synthesis remains a slow, artisanal process that cannot keep pace with AI-driven design, limiting the speed of drug and material discovery and hindering domestic reshoring of pharmaceutical manufacturing.
Solution
Excelsior Sciences has created a machine‑ready chemistry platform built around proprietary “smart bloccs,” modular chemical building blocks optimized for automated carbon–carbon bond formation. These bloccs serve as a tokenized chemical language that enables AI models to design molecules that can be synthesized, purified, and tested by closed‑loop robotic systems without human intervention. The platform integrates discovery‑scale synthesis with scale‑up capabilities, allowing seamless transition from milligram‑level screening to clinical‑batch production. By automating the make‑test‑learn cycle, the system generates high‑quality data for AI algorithms, accelerating optimization of drug‑like properties and reducing development timelines.
Target Audience
Primary customers are pharmaceutical and biotech companies seeking faster small‑molecule discovery and manufacturing, as well as materials‑science firms and research laboratories that require automated, AI‑driven synthesis capabilities.
Features
- Smart bloccs: synthesis‑friendly building blocks that encode carbon–carbon bond formation as modular, machine‑readable tokens
- Automated robotic synthesis platform that performs iterative reactions, purification, and assay preparation with minimal human oversight
- Closed‑loop AI workflow that feeds experimental results back into generative models for rapid design‑test‑learn cycles
- Scalable chemistry that bridges discovery (milligram) and manufacturing (clinical batch) without re‑engineering processes
- High‑stability TIDA boronate building blocks offering up to 1,000× greater stability for reliable automation
- Compatibility with existing laboratory information systems via API integration for data capture and reporting