Coating uniformity assessment for colored immediate release tablets using multivariate image analysis

Abstract

Multivariate image analysis (MIA) was applied to quantitatively assess film-coated tablets providing a cost-effective tool to replace visual inspection. MIA was used to determine the cosmetic end-point of the film-coating step and to calculate the coating level and distribution across tablets. The technique relies on simple digital images of the tablets and multivariate latent variable methods such as Principal Components Analysis (PCA) and Projection to Latent Structures (PLS). This application has precedence in the food industry and is a useful tool in Quality by Design by providing quantitative ranges on coating targets. The technique is illustrated using two sizes of tablets coated at two different scales. As expected, the coating distribution across tablets for the larger scale is broader, and the total amount of coating material is proportional to the surface area of the tablet. The technique is illustrated with off-line images taken with a Single-Lens Reflex digital camera, and with in-line images taken with a webcam installed inside the coater. For the latter case a novel adaptive PCA modeling approach is proposed to handle the real-time images and translate them into indexes that determine the cosmetic end-point of the film-coating step.