Investigating structural attributes of drug encapsulated microspheres with quantitative X-ray imaging.

The intra-sphere and inter-sphere structural attributes of controlled release microsphere drug products can greatly impact their release profile and clinical performance. In developing a robust and efficient method to characterize the structure of microsphere drug products, this paper proposes X-ray microscopy (XRM) combined with artificial intelligence (AI)-based image analytics. Eight minocycline loaded poly(lactic-co-glycolic acid) (PLGA) microsphere batches were produced with controlled variations in manufacturing parameters, leading to differences in their underlying microstructures and their final release performances. A representative number of microspheres samples from each batch were imaged using high resolution, non-invasive XRM. Reconstructed images and AI-assisted segmentation were used to determine the size distribution, XRM signal intensity, and intensity variation of thousands of microspheres per sample. The signal intensity within the eight batches was nearly constant over the range of microsphere diameters, indicating high structural similarity of spheres within the same batch. Observed differences in the variation of signal intensity between different batches suggests inter-batch non-uniformity arising from differences in the underlying microstructures associated with different manufacturing parameters. These intensity variations were correlated with the structures observed from higher resolution focused ion beam scanning electron microscopy (FIB-SEM) and the in vitro release performance for the batches. The potential for this method for rapid at-line and offline product quality assessment, quality control, and quality assurance is discussed.

Release Mechanisms and Practical Percolation Threshold for Long-acting Biodegradable Implants: An Image to Simulation Study.

The development of long-acting drug formulations requires efficient characterization technique as the designed 6-12 months release duration renders real-time in vitro and in vivo experiments cost and time prohibitive. Using a novel image-based release modeling method, release profiles were predicted from X-Ray Microscopy (XRM) of T0 samples. A validation study with the in vitro release test shows good prediction accuracy of the initial burst release. Through fast T0 image-based release prediction, the impact of formulation and process parameters on burst release rate was investigated. Recognizing the limitations of XRM, correlative imaging with Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) was introduced. A water stress test was designed to directly elucidate the formation of pores through polymer-drug-water interplay. Through an iterative correction method that considers poly(lactic-co-glycolic acid) (PLGA) polymer degradation, good agreement was achieved between release predictions  using FIB-SEM images acquired from T0 samples and in vitro testing data. Furthermore, using image-based release simulations, a practical percolation threshold was identified that has profound influence on the implant performance.  It is proposed as an important critical quality attribute for biodegradable long-acting delivery system, that needs to be investigated and quantified.