Nanoscopy on drug-encapsulating nanosystems by phasor-based fluorescence lifetime analysis

Understanding the supramolecular organization of active compounds (drugs) encapsulated within standard formulations is becoming increasingly important in nanomedicine. In fact, the synthetic identity of a drug-encapsulating nanosystem is supposed to change throughout its journey, from administration to final fate within the target tissue/cell. Here we addressed this issue by exploiting phasor-based fluorescence lifetime imaging (FLIM) of a drug intrinsic fluorescence signal. As case-study, we selected Irinotecan (CPT-11), a chemotherapy medication used to treat colon cancer, small lung cancer and pancreatic cancer, and focused on its liposomal formulation Onivyde®, launched in 2015 as an orphan drug for the treatment of metastatic ductal adenocarcinoma (mPDAC). After measuring the FLIM signature of the drug's individual physical states, we extracted the fractional intensities of each coexisting physical state of the active principle within the nanoparticle. Our analysis was boosted by means of dedicated custom algorithms based on preliminary data processing and multi-dimensional histogram inference to identify regions of interest in the phasor plot. Whereas, in the case of biological samples, we achieved autonomous cell segmentation by means of computer vision algorithms. Onivyde® in commercial vials was found to coexist in multiple physical states (i.e. gelated/precipitated, free and membrane-associated) and undergo extensive leakage in media mimicking complex biological environments. Moreover, we identified multiple mechanism of cellular uptake and were able to investigate subcellular localization and supramolecular organization of irinotecan in a model of pancreatic cells. In conclusion, we believe that Phasor-FLIM represents a useful platform to quantitatively address the synthetic identity of encapsulated fluorescent drugs, both in cuvette and cellular environments. In this context, we envision many potential applications ranging from batch-to-batch analysis, at the production level, to drug development optimization.