SeqsLab Genomics and Health Data Service#
From laboratory information management and translational research analysis to diagnostic interpretation and healthcare reporting, biomedical industry including biobanks, clinical laboratories and healthcare providers requires to systematically manage data across a comprehensive landscape of workflow applications. It all starts with a data management system purpose-built for the workflows of precision medicine.
SeqsLab Genomics and Health Data Service is a suite of standard-based technologies for streamlining sophisticated data management and computational analysis of biomedical and multi-omics information. It provides the HL7® Fast Healthcare Interoperability Resources (FHIR®) compatible and the Global Alliance for Genomics and Health (GA4GH) Phenopackets standard for facilitating workload information management, actionable analytics, and exchange of data with compliant API.
Build on a trusted and secure cloud#
Atgenomix SeqsLab Genomics and Health Data Service is ISO/IEC 27001 and 27018 certified, and is built on Microsoft Cloud for Healthcare in accordance with HIPAA and GDPR requirements. It also follows FDA and MDCG cybersecurity guidance to control access of clinical data and biomedical records with role-based access controls and audits within a compliance boundary.
HL7 Fast Healthcare Interoperability Resources#
HL7® FHIR® is an open standard for health care data exchange and data model that enables data interoperability for systems using FHIR.
For details, see HL7 FHIR().
GA4GH Phenopackets#
GA4GH Phenopackets standard is an open-standard data model that offers a human and machine-readable way to store phenotypic data about a patient or individual. The information can then be shared across clinical and research environments or used for computational analyses.
For details, see GA4GH Phenopackets().
Compliant REST API#
SeqsLab Healthcare API and compliant data store provides a robust and extensible data service, backed by a fully managed Platform-as-a Service (PaaS), that makes it easier for all users and systems working together to consume, manage, and analyze biomedical and multi-omics information. It simplifies workload management and accelerates development with analytics and machine learning tools.