Label-free autofluorescence-detected photothermal mid-IR (AF-PTIR) microscopy is demonstrated experimentally and applied to test the distribution of active pharmaceutical ingredients (APIs) in a mixture containing representative pharmaceutical excipients. Two-photon excited UV-fluorescence (TPE-UVF) supports autofluorescence of native aromatic moieties using visible-light optics. Thermal modulation of the fluorescence quantum yield serves to report on infrared absorption, enabling infrared spectroscopy in the fingerprint region with a spatial resolution dictated by fluorescence. AF-PTIR provides high selectivity and sensitivity in image contrast for aromatic APIs, complementing broadly applicable optical photothermal IR (O-PTIR) microscopy based on photothermal modulation of refractive index/scattering. Mapping the API distribution is critical in designing processes for powdered dosage form manufacturing, with high spatial variance potentially producing variability in both delivered dosage and product efficacy. The ubiquity of aromatic moieties within API candidates suggests the viability of AF-PTIR in combination with O-PTIR to improve the confidence of chemical classification in spatially heterogeneous dosage forms.

Surface plasmon resonance microscope (SPRM) sample stage inevitably suffers from lateral drifts as a result of many environmental factors including thermal fluctuation, mechanical vibration, and relaxation. It places great obstacles to time-lapsed imaging and measurements that need high spatial resolution or long recording time. Existing solutions often require experimental efforts such as the addition of optical markers together with piezoelectric stage-based active feedback configurations. Herein, we propose an all-digital, postrecording image-processing method to remove the lateral drift in a series of time-lapsed SPRM images. The method first calculates the value of lateral drift at subpixel accuracy by combining image cross-correlation analysis and superlocalization strategy. It subsequently reconstructed the drift-free image sequences in a pixel-by-pixel and frame-by-frame manner, according to the linear decomposition and reconstruction principle. This method purely relies on image processing, and it does not require any experimental efforts or hardware. In addition to SPRM, we further demonstrated the applicability of the present method in other types of optical imaging techniques including bright-field transmission microscope and dark-field scattering microscope.