Peter Serno

Development and in-line validation of a Process Analytical Technology to facilitate the scale up of coating processes.

Incorporation of an active pharmaceutical ingredient (API) into the coating layer of film-coated tablets is a method mainly used to formulate fixed-dose combinations. Uniform and precise spray-coating of an API represents a substantial challenge, which could be overcome by applying Raman spectroscopy as process analytical tool. In pharmaceutical industry, Raman spectroscopy is still mainly used as a bench top laboratory analytical method and usually not implemented in the production process. Concerning the application in the production process, a lot of scientific approaches stop at the level of feasibility studies and do not manage the step to production scale and process applications. The present work puts the scale up of an active coating process into focus, which is a step of highest importance during the pharmaceutical development. Active coating experiments were performed at lab and production scale. Using partial least squares (PLS), a multivariate model was constructed by correlating in-line measured Raman spectral data with the coated amount of API. By transferring this model, being implemented for a lab scale process, to a production scale process, the robustness of this analytical method and thus its applicability as a Process Analytical Technology (PAT) tool for the correct endpoint determination in pharmaceutical manufacturing could be shown. Finally, this method was validated according to the European Medicine Agency (EMA) guideline with respect to the special requirements of the applied in-line model development strategy.

Monitoring of an Active Coating Process for Two-Layer Tablets-Model Development Strategies

Incorporation of an active pharmaceutical ingredient (API) into the coating layer of film-coated tablets is a method mainly used to formulate combination tablets. Uniform and precise spray coating of an API represents, however, a substantial challenge that could be overcome by applying Raman spectroscopy as process analytical tool. In the present work, active-coating experiments for osmotic-controlled-release oral delivery system (OROS) tablets were performed in a side-vented lab-scale pan coater. During the process, Raman spectra were recorded in-line and off-line after sampling. Quantitative multivariate calibration models were built up by correlating these spectra with the coated API amount at each sampling point. Three different modeling approaches were tested on a second batch with regard to their predictive ability and robustness. By applying the in-line model development approach on OROS tablets, it was possible to overcome the difficulties of this dosage form with each layer contributing differently to the resulting spectroscopic signal and to determine accurately the applied API amount on two-layer tablets. Thereby, the present study demonstrated that Raman spectroscopy can be successfully implemented as a process analytical technology tool to control and monitor an active-coating process of OROS tablets.