The application of non-linear curve fitting routines to the analysis of mid-infrared images obtained from single polymeric microparticles

Abstract

For the first time, we report a series of time resolved images of a single PLGA microparticle undergoing hydrolysis at 70 °C that have been obtained using attenuated total reflectance-Fourier transform infrared spectroscopic (ATR-FTIR) imaging. A novel partially supervised non-linear curve fitting (NLCF) tool was developed to identify and fit peaks to the infrared spectrum obtained from each pixel within the 64 × 64 array. The output from the NLCF was evaluated by comparison with a traditional peak height (PH) data analysis approach and multivariate curve resolution alternating least squares (MCR-ALS) analysis for the same images, in order to understand the limitations and advantages of the NLCF methodology. The NLCF method was shown to facilitate consistent spatial resolution enhancement as defined using the step-edge approach on dry microparticle images when compared to images derived from both PH measurements and MCR-ALS. The NLCF method was shown to improve both the S/N and sharpness of images obtained during an evolving experiment, providing a better insight into the magnitude of hydration layers and particle dimension changes during hydrolysis. The NLCF approach facilitated the calculation of hydrolysis rate constants for both the glycolic (kG) and lactic (kL) acid segments of the PLGA copolymer. This represents a real advantage over MCR-ALS which could not distinguish between the two segments due to colinearity within the data. The NLCF approach made it possible to calculate the hydrolysis rate constants from a single pixel, unlike the peak height data analysis approach which suffered from poor S/N at each pixel. These findings show the potential value of applying NLCF to the study of real-time chemical processes at the micron scale, assisting in the understanding of the mechanisms of chemical processes that occur within microparticles and enhancing the value of the mid-IR ATR analysis.

Investigation of factors influencing the hydrolytic degradation of single PLGA microparticles

“…In order to facilitate an insight to the effect of the scCO 2 processing (which resulted in a 234 porous structure) on the hydrolytic degradation behaviour of the PLGA 50/50 polymer, FTIR 235 imaging in ATR mode was used as demonstrated in previous work [24]. For the real-time of hydrated PLGA surrounding both the processed and un-processed particles, as indicated by 247 the apparent concentration gradient from the particle centre towards the water rich zone.…”

“…The cropped data was first order baseline corrected and vector normalised. 199 'Water' and 'PLGA' images were then generated using software MCRv1.6 as described in 200 [24]. The data used to generate line profiles to investigate polymer-water interfaces and to 201 calculate the degradation rate constants were processed using the non-linear curve fitting 202 algorithm developed by authors as described elsewhere [24].…”

“…Scientific microtool straight needle T5340) using a 40X binocular microscope and raw image 191 data was collected using the Agilent Technologies' ResolutionsPro FTIR Spectroscopy 192 software version 5.2.0 (CD846) within the mid-infrared (3800-950cm −1 ) region with 4 cm -1 193 spectral resolution under the conditions described elsewhere [24] at 50 °C or 70 °C where 194 indicated. 195 M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT…”

“…As the error obtained when 203 calculating rate constants by binning a number of spectra (5x5 pixels) was found to be lower 204 than that obtained from a single pixel, three 5x5 pixel regions of interest were selected from 205 each experiment for each sample. Binned spectra of these regions were used to calculate rate 206 constants [24]. 207…”

“…199 'Water' and 'PLGA' images were then generated using software MCRv1.6 as described in 200 [24]. The data used to generate line profiles to investigate polymer-water interfaces and to 201 calculate the degradation rate constants were processed using the non-linear curve fitting 202 algorithm developed by authors as described elsewhere [24]. As the error obtained when 203 calculating rate constants by binning a number of spectra (5x5 pixels) was found to be lower 204 than that obtained from a single pixel, three 5x5 pixel regions of interest were selected from 205 each experiment for each sample.…”