This study describes the robustness test of a transmission near-infrared spectroscopic (NIRS) model for prediction of drug concentration in core tablets as part of real-time release testing (RTRt) efforts for a continuous manufacturing process. Seven calibration blend samples were prepared spanning a concentration range from 70 to 130% of the active pharmaceutical ingredient (API) target level with tablets prepared with laboratory-scale equipment, and their NIR spectra were obtained to develop a partial least squares (PLS) calibration model. The calibration model’s accuracy was assessed with an independent set of tablets obtaining a root mean standard error of prediction (RMSEP) of less than 1.5% label claim at each concentration level. However, a decrease in the prediction of API concentration of tablets exposed to the production environment was observed indicating lack of robustness as a RTRt method. The API is known to interchange solvate molecules with water molecules from the environment. Even though this exchange does not affect product quality, it affects the NIR spectra. The calibration model was then optimized by excluding O–H bands from the spectral range and shown to predict accurately the drug concentration in tablets for up to 113 h after tablet compaction. The calibration model was updated by including tablets produced in the continuous manufacturing line within the calibration model. The updated calibration model was used to predict tablets from three different continuous manufacturing runs, involving different lots of excipients and drug. The results from the updated calibration model showed excellent agreement with reference HPLC results.

• University of Puerto Rico at Mayagüez
• Janssen

• PAT
• Oral solid dose

1. Active pharmaceutical ingredient
2. Chemometrics
3. Near-infrared spectroscopy
4. Optimization / Real-time release testing
5. oral solid dose
6. Partial least squares regression
7. pat
8. Research Article
9. Tablets