Modern drug delivery systems, including microspheres and implants, rely heavily on microstructures such as API dispersion and microporosity to control and optimize performance. Characterizing these microstructures is thus essential to drug development. Various imaging techniques are employed to provide high resolution visualization of microstructures in drug products. While the images can provide qualitative insight, differentiating and quantifying nanometer scale features from images can be challenging. In this talk, novel methods of artificial intelligence (AI) image analytics will be presented. Using a cloud-based software platform, DigiM I2S, high-resolution microstructures of drug products can be accurately analyzed and quantified. This talk will highlight the application of I2S analytics to quantify API particle and microporosity size distributions, drug distribution uniformity, and dimensional analysis of final products and coatings. The application of the AI engine developed for drug microstructure evaluation and release modeling will be discussed.
Upon completion, participants will be able to understand the principles of quantitative image analysis.
Upon completion, participants will be able to understand how various AI approaches are different from conventional image analysis methods.
Upon completion, participants will be able to consider the implications and applications of image analysis to their own projects and process development.