ZebraMed operates an automated zebrafish screening platform that generates high‑throughput, multi‑organ phenotypic data from in vivo experiments. Its ZebrAI engine annotates and structures these data to align with human clinical endpoints, providing searchable, machine‑learnable datasets for AI‑driven drug discovery. The company licenses the curated data and offers custom data‑generation services to pharmaceutical R&D, biotech firms, and contract research organizations.
Funding
Funding not disclosed
Founders
Product
Problem
AI-driven drug discovery suffers from a systemic data gap: existing in vitro assays and fragmented pre‑clinical models provide limited, reductionist information, resulting in low translatability of predictive models to human outcomes. The lack of large‑scale, high‑content in vivo datasets hampers the ability of pharmaceutical and biotech companies to train reliable AI algorithms for efficacy and safety prediction.
Solution
ZebraMed operates a data engine that industrializes in vivo biology using automated zebrafish screening at scale. Proprietary hardware combined with off‑the‑shelf robotics delivers standardized, high‑throughput experiments that capture multi‑organ, systemic responses. An AI enrichment layer (ZebrAI™) processes raw phenotypic readouts, aligns them with human clinical annotations, and structures the data into a searchable, machine‑learnable format. The resulting curated datasets enable partners to train predictive models with markedly higher translational fidelity. ZebraMed offers both licensed access to these datasets and bespoke data‑generation services tailored to specific target pathways or disease models, closing the loop between computational design and biological reality.
Target Audience
Primary customers are pharmaceutical R&D divisions, AI‑focused biotech firms, and contract research organizations that require high‑quality in vivo datasets to train and validate predictive drug discovery models.
Features
- Fully automated zebrafish screening pipeline with robotic liquid handling, imaging, and environmental control, supporting thousands of experiments per week.
- Standardized experimental protocols that capture multi‑organ phenotypes, enabling systemic biology insights beyond single‑cell assays.
- ZebrAI™ intelligence engine that annotates phenotypic data, performs feature extraction, and maps profiles to human clinical endpoints using deep‑learning models.
- High‑content data output (morphology, behavior, molecular readouts) stored in a cloud‑native repository with RESTful API and bulk download options.
- Ontology‑driven metadata tagging and versioned data lineage to ensure reproducibility and regulatory compliance.
- 84% gene homology zebrafish model, providing a biologically relevant bridge between rodent studies and human physiology while maintaining ethical scalability.
- Secure, HIPAA‑compatible data hosting with role‑based access controls and audit logging for enterprise customers.