Statistical modeling allows for auto-calibration of second harmonic generation (SHG) images for quantification of trace crystallinity within amorphous solid dispersions (ASDs). An increasing number of active pharmaceutical ingredients (APIs) have poor water-solubility, which can diminish bioavailability and efficacy of the drug. A popular strategy to improve the solubility is to put the APIs in an amorphous form and to stabilize it in a polymeric carrier matrix to form an ASD. While an ASD does improve the solubility and thus the bioavailability of the API, even a few nucleation sites can negatively affect both the formulation stability and dissolution activities. Due to the impact trace crystallinity has, it is important to be able to quantify the crystallinity during manufacturing and storage processes, but detection of &lt;~1% crystallinity by volume is difficult for many standard benchtop methods. The selectivity of SHG microscopy for homochiral API crystals allows for detection down to the ppm regime and makes it an ideal tool to quantify crystallinity content in pharmaceutical formulations. The use of particle-counting algorithms and analytical expressions to correct for bias from particle overlap was demonstrated with both simulated and experimental data. Since particle-counting can recover the SHG intensity and the percent crystallinity based on image analysis, it can be used as an internal calibrant for quantifying higher levels of crystallinity, enabling auto-calibration based on the average SHG intensity per unit volume.

Image analysis for calibration-free determination of crystallinity in amorphous solid dispersions

256th National Meeting (2018)

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