Astride Genomics provides a cloud‑based SaaS platform that transforms raw microbial NGS data into actionable pathogen identification and antimicrobial resistance reports. The service automates bioinformatics analysis, quality control, and integrates results via API or HL7/FHIR into hospital LIS/EHR systems, enabling faster, evidence‑based treatment decisions for clinical labs.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare providers often lack rapid, accurate analysis of microbial whole-genome sequencing data, leading to delayed or imprecise identification of pathogens and their resistance profiles. This hampers timely diagnosis and appropriate antimicrobial treatment, contributing to poorer patient outcomes and suboptimal antimicrobial stewardship.
Solution
ASTRID Genomics offers a cloud‑based SaaS platform that ingests raw next‑generation sequencing (NGS) data from microbial samples and automatically generates clinically actionable reports. The platform applies validated bioinformatics pipelines to identify species, detect resistance genes, and predict susceptibility, delivering results in a format ready for integration into electronic health records and laboratory information systems. By standardizing and accelerating genomic interpretation, ASTRID enables clinicians to make evidence‑based treatment decisions faster, supporting both patient care and institutional antimicrobial stewardship programs.
Target Audience
Primary customers are hospital microbiology laboratories, clinical diagnostic labs, and infectious disease departments that require rapid genomic analysis of bacterial and fungal pathogens.
Features
- End‑to‑end cloud workflow that accepts raw NGS reads and returns a complete pathogen identification and resistance report
- Curated reference databases for species taxonomy and antimicrobial resistance genes with regular updates
- Automated quality control and contamination detection to ensure reliable results
- Clinically focused output that includes susceptibility predictions, confidence scores, and treatment recommendations
- API and HL7/FHIR compatible interfaces for seamless integration with hospital LIS/EHR systems
- Scalable multi‑tenant architecture that supports high‑throughput laboratory environments