A material sparing test to predict punch sticking during formulation development.

CONTEXT: A qualitative and material sparing test for punch sticking was developed as a predictive development screening tool for comparison of formulation strategies and processing methods to eliminate punch adhesion. OBJECTIVE: To develop a predictive test for a formulation's potential to adhere to tablet punches during compression. MATERIALS AND METHODS: Two proprietary compounds, A and B, with histories of punch sticking during manufacturing but not in development, were formulated with microcrystalline cellulose, lactose, croscarmellose sodium, and magnesium stearate. Matching placebos were also prepared by the same methods. Flat faced bevel edge (FFBE) punches of 1/2" diameter were compared with 1/4" SRC punches and 1/4" Flat Faced (FF) punches for adhesion potential using a Kilian rotary tablet press and a Huxley Bertram compaction simulator. RESULTS AND DISCUSSION: Formulation accumulated on the punches after compression, which indicated potential for punch sticking that resulted in defective tablets with successive compactions. In all cases, only active formulations adhered to the FFBE and FF punches during tableting runs and with fewer compactions than the SRC punches. Those APIs were then reformulated and successfully manufactured using the predictive test results. Reducing the punch size to 1/4" permitted testing with 50 g of formulation, a ten-fold reduction in consumption compared to the 1/2" punches. CONCLUSION: Flat surfaced punches were shown to be more challenging to adhesive formulations than SRC punches. Adhesive formulations were reformulated and successfully manufactured without punch sticking.

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

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.