Microstructure, Quality, and Release Performance Characterization of long-Acting Polymer Implant Formulations with X-Ray Microscopy and Quantitative AI Analytics

Microstructure Formation and Characterization of Long-Acting Injectable Microspheres: The Gateway to Fully Controlled Drug Release Pattern

Long-acting injectable microspheres have been on the market for more than three decades, but if calculated on the brand name, only 12 products have been approved by the FDA due to numerous challenges in achieving a fully controllable drug release pattern. Recently, more and more researches on the critical factors that determine the release kinetics of microspheres shifted from evaluating the typical physicochemical properties to exploring the microstructure. The microstructure of microspheres mainly includes the spatial distribution and the dispersed state of drug, PLGA and pores, which has been considered as one of the most important characteristics of microspheres, especially when comparative characterization of the microstructure (Q3) has been recommended by the FDA for the bioequivalence assessment. This review extracted the main variables affecting the microstructure formation from microsphere formulation compositions and preparation processes and highlighted the latest advances in microstructure characterization techniques. The further understanding of the microsphere microstructure has significant reference value for the development of long-acting injectable microspheres, particularly for the development of the generic microspheres.

Characterization of Pharmaceutical Tablets by X-ray Tomography

Solid dosage forms such as tablets are extensively used in drug administration for their simplicity and large-scale manufacturing capabilities. High-resolution X-ray tomography is one of the most valuable non-destructive techniques to investigate the internal structure of the tablets for drug product development as well as for a cost effective production process. In this work, we review the recent developments in high-resolution X-ray microtomography and its application towards different tablet characterizations. The increased availability of powerful laboratory instrumentation, as well as the advent of high brilliance and coherent 3rd generation synchrotron light sources, combined with advanced data processing techniques, are driving the application of X-ray microtomography forward as an indispensable tool in the pharmaceutical industry.

Assessing microstructural critical quality attributes in PLGA microspheres by FIB-SEM analytics

The distribution of the active pharmaceutical ingredient (API) within polymer-based controlled release drug products is a critical quality attribute (CQA). It is crucial for the development of such products, to be able to accurately characterize phase distributions in these products to evaluate performance and microstructure (Q3) equivalence. In this study, polymer, API, and porosity distributions in poly(lactic-co-glycolic acid) (PLGA) microspheres were characterized using a combination of focused ion beam scanning electron microscopy (FIB-SEM) and quantitative artificial intelligence (AI) image analytics. Through in-depth investigations of nine different microsphere formulations, microstructural CQAs were identified including the abundance, domain size, and distribution of the API, the polymer, and the microporosity. 3D models, digitally transformed from the FIB-SEM images, were reconstructed to predict controlled drug release numerically. Agreement between the in vitro release experiments and the predictions validated the image-based release modelling method. Sensitivity analysis revealed the dependence of release on the distribution and size of the API particles and the porosity within the polymeric microspheres, as captured through FIB-SEM imaging. To our knowledge, this is the first report showing that microstructural CQAs in PLGA microspheres derived from imaging can be quantitatively and predictively correlated with formulation and manufacturing parameters.

Investigation of Quantitative X-ray Microscopy for Assessment of API and Excipient Microstructure Evolution in Solid Dosage Processing

Assessment and understanding of changes in particle size of active pharmaceutical ingredients (API) and excipients as a function of solid dosage form processing is an important but under-investigated area that can impact drug product quality. In this study, X-ray microscopy (XRM) was investigated as a method for determining the in situ particle size distribution of API agglomerates and an excipient at different processing stages in tablet manufacturing. An artificial intelligence (AI)-facilitated XRM image analysis tool was applied for quantitative analysis of thousands of individual particles, both of the API and the major filler component of the formulation, microcrystalline cellulose (MCC). Domain size distributions for API and MCC were generated along with the calculation of the porosity of each respective component. The API domain size distributions correlated with laser diffraction measurements and sieve analysis of the API, formulation blend, and granulation. The XRM analysis demonstrated that attrition of the API agglomerates occurred secondary to the granulation stage. These results were corroborated by particle size distribution and sieve potency data which showed generation of an API fines fraction. Additionally, changes in the XRM-calculated size distribution of MCC particles in subsequent processing steps were rationalized based on the known plastic deformation mechanism of MCC. The XRM data indicated that size distribution of the primary MCC particles, which make up the larger functional MCC agglomerates, is conserved across the stages of processing. The results indicate that XRM can be successfully applied as a direct, non-invasive method to track API and excipient particle properties and microstructure for in-process control samples and in the final solid dosage form. The XRM and AI image analysis methodology provides a data-rich way to interrogate the impact of processing stresses on API and excipients for enhanced process understanding and utilization for Quality by Design (QbD).

Semisolid Pharmaceutical Product Characterization Using Non-invasive X-ray Microscopy and AI-Based Image Analytics

This work reports the use of X-ray microscopy (XRM) imaging to characterize the microstructure of semisolid formulations containing multiple immiscible phases. For emulsion-based semisolid formulations, the disperse phase globule size and its distribution can be critical quality attributes of the product. Optical microscopy and light diffraction techniques are traditionally used to characterize globule size distribution. These techniques are subjected to sample preparation bias and present challenges from matrix interference and data processing. XRM imaging is an emergent technique that when combined with intelligent data processing has been used to characterize microstructures of pharmaceutical dosage forms including oral solid formulations, controlled release microspheres, and lyophilized products. This work described our first attempt to use XRM imaging to characterize two complex emulsion-based semisolid formulations, a petrolatum-based ointment with a dispersed phase comprising a hydrophilic liquid, and an oil-in-water cream. This initial assessment of technology showed that microstructure details such as globule size distribution, volume fraction, spatial distribution uniformity, inter-globule spacing, and globule sphericity could be obtained and parameterized. It was concluded that XRM imaging, combined with artificial intelligence-based image processing is feasible to generate advanced characterization of semisolid formulation microstructure through 3D visualization and parameterization of globule attributes. This technique holds promise to provide significantly richer microstructure details of semisolid formulations. When fully developed and validated, it is potentially useful for quantitative comparison of microstructure equivalence of semisolid formulations.

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.