FT-NIR models for predicting film quality parameters in titanium dioxide-free tablet coatings

•TiO2-free film coating optimization is challenging in the pharmaceutical industry.•NIR offers a precise and exact method for film coating thickness determination.•MVA methods allow a knowledge-based approach to determine film chemical signals.•Both film thickness and a* can be used as calibration techniques with high accuracy. This study leverages Fourier Transform Near-Infrared (FT-NIR) spectroscopy to monitor the coating process of pharmaceutical tablets using PVA-based TiO2-free films, with talc and iron oxides as opacifiers. By employing a combination of multivariate analytical techniques, the correlation between film coating progression and film thickness was evaluated. Assessment of coating thickness for different coating levels was performed by optical microscopy. Additionally, using colorimetric analysis by scanner method, the color progression for different coating levels was evaluated and expressed as the a* value from CIELAB color space. The coordinate value a* showed predictable changes with the progression of the coating process and film thickness values, indicating its utility as a robust reference method for quality control and process optimization. The predictive capability of the OPLS models, validated against measured film thickness and the a* value, demonstrated low prediction errors and confirmed the models' effectiveness in distinguishing coating levels and accurately predicting film coating progression. The OPLS model used knowledge-based peaks of interest, which were further confirmed by loading and coefficient plots. The study demonstrated that film thickness, as a destructive, and a* value from CIELAB color space, as a non-destructive reference method for coating progression could be used during a controlled pharmaceutical coating process for product quality assessment and pharmaceutical process endpoint determination. [Display omitted]