CubaseBio offers a cloud‑native platform that imports volumetric microscopy and spatial‑omics data, registers multi‑modal signals, and applies deep‑learning segmentation to produce quantitative 3D tissue maps. The system provides an interactive web dashboard, statistical spatial analysis tools, and RESTful/Python APIs for integration with pharmaceutical and academic drug‑discovery pipelines.
Funding
Funding not disclosed
Founders
Product
Problem
Researchers lack scalable tools that can capture and analyze biological structures in true three dimensions, limiting their ability to understand complex cellular organization and slowing drug discovery pipelines.
Solution
CubaseBio provides a software platform that integrates high‑resolution 3D imaging data with computational pipelines for spatial biology analysis. The system ingests volumetric microscopy or spatial‑omics datasets, aligns and registers multi‑modal signals, and applies AI‑driven segmentation and feature extraction to generate quantitative 3D maps of tissue architecture. Results are visualized through an interactive web‑based interface and can be exported via standard APIs for downstream modeling or integration with existing drug‑discovery workflows. By automating data preprocessing, scaling analysis to millions of cells, and delivering reproducible metrics, the platform accelerates hypothesis generation and target validation in pharmaceutical research.
Target Audience
Primary customers are pharmaceutical and biotech R&D teams, as well as academic laboratories conducting spatial‑omics or high‑throughput 3D imaging studies for drug target discovery and tissue‑level biology research.
Features
- Automated volumetric data import from light‑sheet, confocal, and multiplexed imaging instruments
- Multi‑modal registration engine that aligns protein, RNA, and morphological channels in 3D space
- Deep‑learning segmentation models for cell, nucleus, and sub‑cellular structure identification at scale
- Cloud‑native analytics pipeline capable of processing >10 TB of imaging data per run
- Interactive 3D visualization dashboard with real‑time slicing, annotation, and quantitative heat‑maps
- RESTful API and Python SDK for seamless integration with bioinformatics pipelines and LIMS
- Built‑in statistical modules for spatial pattern detection, neighborhood analysis, and differential expression in 3D
- HIPAA‑compliant data storage with role‑based access controls and end‑to‑end encryption