Issue link: https://www.e-digitaleditions.com/i/1287521
Tablets & Capsules September 2020 47 These equations were used to predict a pilot-plant sample set. To evaluate the models' robustness and pre- diction power, their selectivity, linearity, accuracy, preci- sion, and repeatability were tested. Figure 3 shows the ibuprofen model, which had an R 2 of 0.9993 for calibration, an R 2 of 0.9991 for internal validation, and a prediction error of 0.004. The caffeine model resulted in an R 2 of 0.9986 for calibration, an R 2 of 0.9981 for internal validation, and a prediction error of 0.002, as shown in Figure 4. Figure 3 Ibuprofen calibration model Calibration Validation Calibration Validation Pearson's r 0.99967 0.99959 R-square 0.99934 0.99918 Adj. R-square 0.99934 0.99917 Slope 0.9993 0.9993 RMSE 0.33 0.037 NIR predictions 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Reference 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Figure 4 Caffeine calibration model NIR predictions 0.20 0.15 0.10 0.05 0.00 Reference 0.00 0.05 0.10 0.15 0.20 Calibration Validation Calibration Validation Pearson's r 0.99931 0.99907 R-square 0.99861 0.99814 Adj. R-square 0.99861 0.99813 Slope 0.9986 0.9986 RMSE 0.18 0.21