Formulation and Quality – Chemical
2019 PharmSci 360
This presentation will review emerging 3D imaging techniques as they are applied to drug formulation development. Using various case studies in the characterization of solid and semi-solid dosage form, nova image-based analytics and image-based release modeling methods will be demonstrated to advance mechanistic understanding and accelerate characterization cycle in bioequivalence, bioavailability, and stability studies.
Modern drug delivery increasingly relies on microstructures to achieve specific release rate and therapeutic target. The delivery systems modulate drug release via precise engineering control of the API domain and pore size. Other approaches involve the use of functional coating or performance-enabling excipients. The small-scale nature of pores, drug domains, and delivery vehicles demands higher resolution technique. Image-based characterization has been broadly utilized in drug product development for fundamental understanding of the process-property-performance interplay and optimizing formulation process and design. In addition, the image-based analytical tools can help tailor rate-limiting film coat thickness where the pore formation is critical to controlling drug release. The technique also find applications in amorphous solid dispersion to interrogate the underlying mechanism of in-situ drug nanoparticles formation in dissolution media for solubility enhancement. Three-dimensional micro-imaging, represented by X-Ray Micro-computed tomography (MicroCT) and Focused Ion Beam Scanning Electron Microscope (FIB-SEM), can qualitatively visualize these microstructures, quantify their spatial and chemical distribution, and predict release behavior. In recent years, the emerging image-based numerical simulation has received significant traction and plays an important role on predicting drug release performance. The combined workflow of micro-imaging, artificial intelligence-base image analytics, and image-based release simulation represents a potential paradigm shift in drug design and evaluation, with significantly reduced evaluation time, improved release performance, and lowered in-vitra and in-vivo experiment cost, for both chemical and biological medicine.
While micro-imaging, represented by light microscopy, Raman, and SEM, is widely used in formulation development as a direct and qualitative method, quantitative effort is much less abundant, due to the lack of automated, intelligent, and fully-validated analysis tools. Subsequently, 3D imaging is less explored, and even less analyzed. Release predictions, possible with information-rich images, are rarely attempted because of the lack of awareness and appropriate workflow.
The challenges associated with the data intensive nature of various imaging methods will be discussed. Solutions leveraging artificial intelligence and cloud computing will be presented.