A molecular imaging application was developed to characterize the drug distribution on CYPHER® and NEVO™ Drug-eluting Stents using MALDI Qq-ToF analytical methodology. The coating matrix, laser energy, laser frequency, spatial resolution (related to rastering speed) and mass spectrometer parameters were optimized to analyze drug distribution in both durable and biodegradable polymer matrices. The developed method was extended to generate data from stents explanted from porcine coronary arteries. Due to the method's intrinsic specificity, it offers a significant advantage over other techniques in that it allows low-level detection of the target molecule without biological interferences from the blood or tissue. The method is also capable of detecting drug-related degradation products both from the finished stent product and from explanted stents.

Multivariate data analysis was applied to confocal Raman measurements on stents coated with the polymers and drug used in the CYPHER Sirolimus-eluting Coronary Stents. Partial least-squares (PLS) regression was used to establish three independent calibration curves for the coating constituents: sirolimus, poly(n-butyl methacrylate) [PBMA], and poly(ethylene-co-vinyl acetate) [PEVA]. The PLS calibrations were based on average spectra generated from each spatial location profiled. The PLS models were tested on six unknown stent samples to assess accuracy and precision. The wt % difference between PLS predictions and laboratory assay values for sirolimus was less than 1 wt % for the composite of the six unknowns, while the polymer models were estimated to be less than 0.5 wt % difference for the combined samples. The linearity and specificity of the three PLS models were also demonstrated with the three PLS models. In contrast to earlier univariate models, the PLS models achieved mass balance with better accuracy. This analysis was extended to evaluate the spatial distribution of the three constituents. Quantitative bitmap images of drug-eluting stent coatings are presented for the first time to assess the local distribution of components.

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