Sampling directly from biology
The solutions provided by Metrichor have the capability to provide global meta-analysis to understand biological events impacting everyday life. By performing repeated analyses of DNA, RNA or proteins in an organism or environment, it is possible to globally track, trend and mine these events using these natural information-rich biological barcodes.
The technology is designed to allow an individual or organisation with little or no laboratory infrastructure to digitise a biological sample and stream data to the cloud for analysis in real time. The analyses aim to answer their questions of interest and may be shared with others such as other scientists, monitoring organisations or healthcare professionals.
For example, this question may concern:
- A food sample (Are there bacteria present? What kind? What species is this? Has our supplier followed quality control regulations?)
- Human tissue (Is disease present, what is it? Are pre-disease markers present? What changes in my blood when I exercise? Has anything changed since last time I checked? How is my blood different from other people?)
- Environmental samples (Is this sample polluted? What is this species? Are infectious pathogens present here? How has this changed? How has this environment changed over time?)
- Agricultural or livestock (Is this crop what we planted? How has it changed? Is this animal the correct breed? Should I breed these individuals? How are these animals breeding? Is this a GM crop? Does my farmyard contain pathogens?)
- Infectious disease (Is this wound infected? What is it infected with and what should I prescribe? Where did it come from and how can we stop it spreading? Who is a super spreader? Have people passing through this doorway got any viruses?)
For many of these questions, ongoing monitoring is needed to understand changes in a pathogen, environment or biological status. Combining this monitoring data with other associated data (e.g. geolocation, timing, and environmental statistics) may support predictive patterns for pre-emptive actions.