Detection of pathogens from a gaseous mixture associated with secretions

Abstract

This disclosure relates generally to detection of pathogens from a gaseous mixture associated with secretions. Conventional methods typically involve invasive or biohazardous techniques, the requirement of quantity limits utility of several natural secretions, there is a dependency on immunological reactions to develop in a subject being monitored resulting in long time taken for detecting pathogens, which increases risk to health and environment. There is also reduced specificity and sensitivity considering the dependency on signature identification or training of machine learning models. Again, prior art focusses on designing antibodies for a particular type of sensor which is challenging when dealing with natural immunoglobulin. The present disclosure addresses these challenges by enabling identification of a most viable sensor for the natural immunoglobin, the viability being based on mathematical representations of the relationship between a sensor and the immunoglobulin using an ontology of domain knowledge associated with pathogens, technology, processing and detection.