(686j) An Optical Near Infrared Doxorubicin Sensor Revealed By Principal Component Analysis of Nanosensor Libraries
To enable the rapid discovery of new sensor targets, we apply principal component analysis (PCA) to nanosensor discovery screening of mixed chirality nanosensor libraries. The screen consists of a library of SWNT functionalized with different polymer corona phases such as polynucleotides, phospholipids, and amphiphilic heteropolymers along with a panel of >40 biomolecular targets. Our analysis can quickly identify nanosensor responses to different analytes and organizes analytes with similar responses into groups using hierarchical clustering. We find that chemical classes, e.g. catecholamines, can be grouped together based on their multi-chiral fluorescent responses, demonstrating that PCA enables classification of molecular specifics for nanosensor-target interactions. Our approach further identifies a novel NIR nanosensor for the detection of the chemotherapeutic doxorubicin (DOX) with µM sensitivity. We find that the kinetics of binding as well as the optical response of nanosensors to DOX is strongly dependent on the polynucleotide sequence used to functionalize the SWNT. We characterize our findings in the context of DOX detection as a biological therapeutic, and extrapolate its use to image drug bio-distributions in vivo.