About AgnoSci

Pioneering In Vitro Diagnostics for Pathogen Detection and Cause of Death Investigation

AgnoSci is dedicated to developing innovative in vitro diagnostic (IVD) solutions for death investigation and pathogen detection. By leveraging multiomics technologies and artificial intelligence, we identify and validate novel biomarkers to create rapid, accurate diagnostic tools that transform forensic science and infectious disease detection.

What We Do

    • Multi-omics analysis (genomics, transcriptomics, proteomics, metabolomics)

    • AI-powered pattern recognition for biomarker identification

    • Comprehensive validation of death-associated molecular patterns

    • Novel pathogen signature detection

    • Integration of multiple data streams for enhanced accuracy

    • Translation of validated biomarkers into diagnostic assays

    • Development of rapid, point-of-need testing solutions

    • Creation of multiplexed detection panels

    • Optimization for field deployment

    • Regulatory-compliant development process

    • Molecular diagnostic tools for cause of death determination

    • Rapid pathogen detection and identification

    • Systematic biomarker screening

    • Comprehensive molecular profiling

    • Integration with traditional forensic methods

Strategy

  • Discover

    Multi-omics data collection and analysis

    AI-driven biomarker identification

    Pattern recognition across large datasets

    Statistical validation of findings

  • Develop

    Translation of biomarkers into IVD formats

    Assay optimization and validation

    Protocol standardization

    Performance verification

  • Implement

    Field testing and validation

    Quality control implementation

    User training and support

    Continuous performance monitoring

Technology Platform

    • Next-generation sequencing

    • Proteomics profiling

    • Metabolomics analysis

    • Transcriptomics assessment

    • Machine learning algorithms for pattern recognition

    • Deep learning for biomarker identification

    • Predictive modeling

    • Automated data analysis

    • Continuous learning systems

    • Rapid assay prototyping

    • Multiplexed detection systems

    • Point-of-need format optimization

    • Stability testing

    • Performance validation