Development and Validation of a Near-Infrared Method for the

Anal. Chem. 2003, 75, 754-760

Development and Validation of a Near-Infrared Method for the Quantitation of Caffeine in Intact Single Tablets Magali Laasonen,†,‡ Tuulikki Harmia-Pulkkinen,‡ Christine Simard,§ Markku Ra 1 sa 1 nen,| and ,† Heikki Vuorela*

Department of Pharmacy, Division of Pharmacognosy, P.O. Box 56 (Viikinkaari 5E), FIN-00014 University of Helsinki, Helsinki, Finland, and Pharmia Oy, P.O. Box 387, FIN-00101 Helsinki, Finland

A near-infrared spectroscopic method was developed and validated for determining the caffeine concentration of single and intact tablets in a Finnish pharmaceutical product containing 58.82% (m/m) caffeine.The spectral region of interest contained a total of 474 data points. The second derivative of Savitsky-Golay, a standard normal variate, and mean centering were used as spectral preprocessing options. The feasibility study showed nonuniformity of caffeine repartition within each tablet. Thus, spectra were recorded from both faces of the tablets, and the analysis result for a single tablet was reported as the average of both face determinations. Precision of the method was validated because the relative standard deviations from repeatability and intermediate precision tests were below 0.75% (m/m). Accuracy validation proved that the NIR results were not significantly different (P ) 0.09, n ) 12) from the results obtained with the reference HPLC method. The limit of quantification for caffeine was 13.7% (m/m) in the tablets. The method was found to be unaffected by NIR source replacement, but the repeatability of the results was affected if the sample holder was not placed in the correct position in the light beam. Routine NIR analysis of caffeine in tablet form was found to be more flexible and much faster than that performed with the HPLC method. Caffeine or 1,3,7-trimethylxanthine is a widely used drug throughout the world. This alkaloid occurs naturally in tea leaves, coffee beans, cocoa beans, and mate´ leaves and is traditionally used for its stimulatory effects.1 The caffeine found in medicines and food supplements can be of natural origin (e.g., as a byproduct from caffeine-free product manufacture) or produced by chemical synthesis. * Corresponding author. E-mail: [email protected]. † Department of Pharmacy, University of Helsinki. ‡ Pharmia Oy. § ABB Bomem Inc., 585 Charest Boulevard, East Suite 300, Quebec, PQ, Canada, G1K 9H4. | Department of Chemistry, University of Helsinki. (1) O’Neil, M. J.; Smith, A.; Heckelman, P. E.; Obenchain, J. R.; Gallipeau, J. A. R.; D’Arecca, M. A.; Budavari, S. Merck Index, an Encyclopedia of Chemicals, Drugs and Biological; 13th ed.; Merck & Co., Inc.: Rahway, NJ, 2001; p 275.

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The most common methods used for analyzing caffeine are probably HPLC, recommended by the American Pharmacopoeia USP 25, and the UV method, even though these techniques are slow and solvent consuming. Researchers have recently shown interest in near-infrared spectroscopy (NIR) for the analysis of caffeine in its “natural matrix”, i.e., in green tea leaves2 or in coffee.3,4 So far, only one study has been reported on the NIR quantification of caffeine isolated from a pharmaceutical preparation, and it was published almost thirty years ago.5 This study, however, did not make use of the main advantage of NIR spectroscopy, i.e., determining a compound without having to isolate it from its matrix. The advantages6 of NIR spectroscopy over traditional methods for quantitation in solid form are very attractive due to the physical properties of the NIR region. The low molar absorptivity of NIR bands permits the measurement of solid samples with little or no sample preparation, thus avoiding manipulation errors. NIR spectroscopy is therefore environment-friendly because there is usually no need to dilute samples. The speed of this technique is due to both the minimum amount of sample preparation and the short time needed to record spectra. Moreover, the NIR signal contains both physical and chemical information about the samples. Thus it can be used for qualitative analysis7,8 and for measuring different physical parameters on the sample (e.g., particle size, tablet hardness,9 or thickness of the tablet coating). NIR can also be used for monitoring on-line processes.10 Despite all these advantages, only a small number of papers have been published on the NIR quantitation of intact tablets9,11-13 compared to the large number of qualitative NIR applications (2) Schulz, H.; Engelhardt, U. H.; Wegent, A.; Drews, H. H.; Lapczynski, S. J. Agric. Food Chem. 1999, 47, 5064-5067. (3) Downey, G.; Boussion, J. J. Sci. Food Agric. 1996, 71, 41-47. (4) Fabian, Z.; Izvekov, V.; Salgo, A.; Orsi, F. Anal. Proc. 1994, 31, 261-263. (5) Allen, L. J. Pharm. Sci. 1974, 63, 912-916. (6) Blanco, M.; Coello, J.; Iturriaga, H.; Maspoch, S.; De La Pezuela, C. Analyst 1998, 123, 135R-150R. (7) Laasonen, M.; Rantanen, J.; Harmia-Pulkkinen, T.; Michiels, E.; Hiltunen, R.; Ra¨sa¨nen, M.; Vuorela, H. Analyst 2001, 126, 1122-1128. (8) Laasonen, M.; Harmia-Pulkkinen, T.; Simard, C. L.; Michiels, E.; Ra¨sa¨nen, M.; Vuorela, H. Anal. Chem. 2002, 74, 2493-2499. (9) Chen, Y.; Thosar, S. S.; Forbess, R. A.; Kemper, M. S.; Rubinovitz, R. L.; Shukla, A. J. Drug Dev. Ind. Pharm. 2001, 27, 623-631. (10) Rantanen, J.; Ra¨sa¨nen, E.; Tenhunen, J.; Ka¨nsa¨koski, M.; Mannermaa, J. P.; Yliruusi, J. Eur. J. Pharm. Biopharm. 2000, 50, 271-276. (11) Blanco, M.; Coello, J.; Iturriaga, H.; Maspoch, S.; Pou, N. Analyst 2001, 126, 1129-1134. 10.1021/ac026262w CCC: $25.00

© 2003 American Chemical Society Published on Web 01/17/2003

reported. The main reason for this is probably because Pharmacopoeias do not give guidelines for the application of NIR in quantitative analysis, even though there are recommendations14 on how to perform a qualitative NIR analysis. Moreover, the ICH guideline15 was not aimed at the validation of nonseparative procedures, which makes the validation of NIR methods more difficult to perform. In this work, we have developed and validated a NIR diffuse reflectance method for the determination of the caffeine content in intact single tablets. This method can be used to determine the caffeine content of a batch, as well as the content uniformity of caffeine tablets, and to validate the manufacturing process, e.g., by controlling content deviations or comparing the caffeine content of tablets pressed by each punch of the press. Validation of the method was performed according to the ICH guideline15 where applicable and using recommendations from Moffat et al.16 The main points of this study are the following: (i) Caffeine is quantified for the first time in intact tablets by a validated NIR method. (ii) Spectral features of synthetic and natural caffeine were compared. (iii) Spectral differences between the tablet faces were demonstrated and explained. (iv) Statistical analysis of the model residuals was found to be an interesting new parameter to include in the method validation. (v) The method was found to be as reliable and much faster than the reference HPLC method. EXPERIMENTAL SECTION Material. The pharmaceutical product studied was in the form of commercially available 170-mg caffeine tablets produced by Pharmia Oy (Helsinki, Finland). The active principle content (anhydrous caffeine) was 58.82% (m/m), and the excipient mass consisted of cellulose, lactose, and other minor excipients. Twentytwo production batches were supplied by Pharmia Oy, and 11 laboratory-made batches were prepared in order to broaden the caffeine concentration range covered by production samples. These batches were obtained by overdosing or underdosing the samples by adding caffeine or excipient mass during the mixing process prior to tableting. The laboratory-made tablets had a weight similar to those from the production batches. The caffeine concentration covered a very wide range: 0 (excipient tablets)100% (m/m) (pure caffeine tablets). Two other laboratory batches were prepared using the same formula as for the production batches, except that caffeine was replaced by theobromine (3,7trimethylxanthine) or theophylline (1,3-trimethylxanthine). HPLC Analysis. The active principle concentration in each batch was obtained as the average of two HPLC determinations. The isocratic reversed-phase HPLC method used a methanol/ 0.05 M NaH2PO4 (30:70) mobile phase, a Lichrocart 125-4 precolumn, a Lichrospher 5-µm, 100 × 4.60 mm RP-18 Merck column, a flow rate of 1 mL/min, and a run time of 12 min. The UV absorbance was measured at 275 nm. The calibration curve (12) Broad, N. W.; Jee, R. D.; Moffat, A. C.; Smith, M. R. Analyst 2001, 126, 2207-2211. (13) Thosar, S. S.; Forbess, R. A.; Ebube, N. K.; Chen, Y.; Rubinovitz, R. L.; Kemper, M. S.; Reier, G. E.; Wheatley, T. A.; Shukla, A. J. Pharm. Dev. Technol. 2001, 6, 19-29. (14) European Pharmacopoeia, 4th ed.; Council of Europe: Strasbourg, 2002; pp 55-56. (15) ICH Harmonised Tripartite Guideline: Validation of Analytical Procedures Methodology, International Conference on Harmonization, 1996. (16) Moffat, A. C.; Trafford, A. D.; Jee, R. D.; Graham, P. Analyst 2000, 125, 1341-1351.

(R2 ) 0.999) was established from duplicate determinations of standard samples at six different concentrations of caffeine in methanol/NaH2PO4. Ten tablets per batch were ground to a fine powder, and 50 mg of this mass was dissolved in methanol/NaH2PO4 (30:70) using sonication. The extracts were filtered and then transferred into HPLC vials. The precision of the method was approximated by the standard deviation (eq 1) from the pooled results of duplicate determinations made on validation samples.

x∑

k)n

s)

[(xk1 - jxk)2 + (xk2 - jxk)2]

k)1

n SE ) s/x2

(1)

(2)

where n is the number of duplicates, xk1 and xk2 are the individual duplicate results, and jxk is the mean of the duplicates. The standard deviation was 0.67% (m/m) leading to a standard error (SE) of 0.47% (m/m) using eq 2. NIR Analysis. The spectra were recorded on a FT-NIR MB160 spectrometer (ABB Bomem, Inc, Quebec, Canada) fitted with a Powder Samplir reflectance accessory, a quartz-halogen lamp, and a cooled InAs detector. The reflectance standard package was supplied by Labsphere Inc. The software package from ABB Bomem Inc. included Grams 32 version 4.04, PLSplus/IQ version 3.03, AIRS (Advance Infrared Software) version 1.54, and SYSTAT version 10, from SPSS Inc. A “tablet holder” was constructed in order to prevent light scattering from the beam due to the small nominal diameter (7 mm) of the tablets. The tablet holder consisted of a 3-mm-thick piece of metal, with a 6-mm-diameter aperture in its center. Tablets were scanned on both faces, on the basis of the feasibility results, using the diffuse reflectance mode. Each spectrum was an average of 64 scans coadded at 16-cm-1 resolution, over the range of 10 000-4000 cm-1. Routine analysis of the caffeine was performed using the AIRS interface. The total procedure required to obtain the average result of six tablets per batch took ∼12 min. System Suitability Testing. System suitability tests, including frequency, spectral quality, spectrophotometric noise, photometric linearity, and precision testing, are performed on a regular basis on the spectrometer. RESULTS AND DISCUSSION Feasibility Study. NIR reflectance spectra and their secondderivative spectra were examined to identify spectral features that could be correlated with the caffeine concentration. A diffuse reflectance spectrum of a laboratory-made tablet containing 100% synthetic anhydrous caffeine was examined. The main absorption peaks in this spectrum (4128, 4299, 4431, 4673, 5194, 5836, 5980, 7300, and 8587 cm-1) were found to be very similar to those reported by Downey and Boussion3 for dried coffee extracts and for the spectrum of a synthetic caffeine. Vibrational assignments17 of these bands are given in Table 1. (17) Osborne, B. G.; Fearn, T.; Hindle, P. H. Practical NIR Spectroscopy With Applications in Food and Beverage Analysis, 2nd ed.; Longman Scientific & Technical: Essex, England, 1993; pp 30-33.

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Table 1. Vibrational Assignments of Absorption Bands for Caffeine Tablets in the Range of 10 000-4000 cm-1 wavenumbers (cm-1)

assignments

8587 7300 5836 and 5980 5194 4673 4431 4299 4128

C-H stretching second overtone combination band: 2C-H stretching and C-H deformation C-H stretching, first overtone CdO stretching, second overtone combination band: dCsH stretching and CdC stretching combination band: OsH stretching and OsH deformation combination band: CsH stretching and CsH deformation combination band: CsH stretching and CsC stretching

The second-derivative spectra of laboratory-made tablets containing 100 and 0% caffeine (i.e., excipient tablets) and of production tablets containing 58.82% caffeine were compared (Figure 1). This plot confirmed that the above absorption peaks were correlated with the caffeine concentration and did not interfere with the excipient peaks. To choose the acquisition mode for our study, we analyzed both faces of a single production tablet and compared the two spectra. Six spectra per face were recorded and the tablet was rotated between each recording. The Savitsky-Golay second derivative was applied to the spectra. Hierarchical clustering was used to classify the spectral differences between the two tablet faces. Similarity between pairs of second-derivative spectra was evaluated by the Pearson distance, which measures the strength of the linear relationship between two spectra. The Pearson distance is calculated by 1 - r, where r is the product-moment coefficient of correlation as shown in eq 3.

r)

x(∑

x2

∑xy (∑x) -

∑x∑y N

)(∑

2

N

y2 -

(

∑y)

)

(3)

2

N

where x and y are the second-derivative absorbance values from the two spectra to be compared and N is number of paired observations, i.e., number of data points in the spectra. The linkage distances between clusters were measured by the average linkageclustering algorithm. This algorithm measures the distance between two clusters as the average of the distances between all the points in the clusters. The process is repeated until all the spectra are linked in one hierarchical classification system, represented by the dendrogram (Figure 2). As the two clusters corresponded respectively to the spectra for the front and the back face of the tablet, the two faces of caffeine tablets have different spectral features. This result can be explained by considering the transmission of force in the die cavity of a press during compression. In a rotary tablet press, the compressional force of the upper punch is greater than the force derived from the lower punch because the initial pressure caused by the upper punch decreases progressively through the powder bed, leading to variations in density.18 The lower density zones are located at the periphery, near the upper punch, and also at the bottom corners.19 As a consequence, (18) Train, D. Trans. Inst. Chem. Eng. 1957, 35, 258-266.

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Figure 1. Comparison of the spectral features between PLS factor 1 loading (A) and second-derivative spectra tablets containing 100 (B), 58.82 (C), and 0% caffeine (D), over the (a) 9000-8200- and (b) 6400-5600-cm-1 regions. PLS factor 1 y-values were multiplied by a suitable constant to bring the absorbances within approximately the same range as the other spectra, thus facilitating visual comparison.

the spectral differences are most probably due to density differences between the two faces of the tablet. Spectra were therefore

Table 2. Calibration Model Description and Performance Results composition 6 batches

NIR Calibration Model for Quantitation of Caffeine in Tablets range of HPLC values no. of PLS factors 48.2-65.2% (m/m) caffeine

PRESS

SEC

39.94

1.08% (m/m)

1

second derivative, mean centering, standard normal variate and region selection

Calibration Model Performance SEP bias 1.05% (m/m)

Figure 2. Dendrogram for the hierarchical analysis of secondderivative spectra of the front (case with odd numbers) and back face (case with even numbers) of a 58.82% caffeine tablet.

recorded on both faces of each tablet and averaged to give a representative spectrum for the tablet. Calibration and Design of the Validation Sets. The production and laboratory batches were split into a calibration set, used to develop the regression equation, and into a validation set, used to evaluate the model performance. The calibration set (Table 2) consisted of four laboratory batches and two production batches. Six tablets per batch were scanned, and the average spectra for both faces were used in the regression model. HPLC results from duplicate determinations were assigned to each spectrum of the calibration set. The validation set consisted of 11 laboratory-made batches and 20 production batches, spanning the range from 0 to 100% caffeine in the tablets, and 2 laboratory batches containing theobromine or theophylline instead of caffeine. Data Preprocessing. The absorbance spectra were treated mathematically by applying a Savitsky-Golay second derivative to enhance the resolution by removing the overlapping peaks and correcting the baseline. Mean centering was then performed to remove any offset from the data, and standard normal variate (SNV) correction was applied to remove the major effects of light scattering. Wavenumber selection was performed in order to include characteristic spectral features of caffeine identified in the feasibility study and to exclude regions exhibiting a high noise level (e.g. 10 000-9000 cm-1). The water absorption band around 5155 cm-1, corresponding to O-H stretching + O-H deformation, was also excluded. The selected region contained a total of 474 data points. (19) Aulton, M. E. In Pharmaceutics: The Science of Dosage Form Design; Aulton, M. E., Ed.; Churchill Livingstone: Edinburgh, 1988; pp 660-661.

preprocessing options

0.0033% (m/m)

outliers

R2

0

0.972

Model Development and Performance. The calibration model was developed using a PLS algorithm and constructed by cross-validation. The number of significant PLS factors was chosen as defined by Haaland and Thomas.20 The resulting number of factors was one (Table 2), which could indicate an underfit model. The quality of this model was checked by calculating the prediction bias (average value of residuals), standard error of calibration (SEC), and standard error of prediction (SEP) (Table 2). The F-test (R ) 0.01) was applied to determine the statistical significance of outliers. No outliers were found in our calibration set. The relevancy of PLS factor 1 information was confirmed by plotting the first PLS loading factor together with a 100% caffeine spectrum, a production tablet spectrum, and an excipient tablet spectrum. (Figure 1) This plot showed that the first factor was well correlated with the caffeine concentration in the tablet spectrum and did not interfere with the spectral features of the excipients. The calibration equation in the form of NIR value (% m/m) ) y-intercept ((std error) + slope ((std error) × HPLC value (% m/m) was found to be Y ) 1.47((1.60) + 0.97((0.03)X. The 95% confidence interval for the slope (0.92-1.03) included one, suggesting that there was no evidence for a relative systematic error in the calibration equation. As the confidence interval for the intercept (from -1.79 to 4.73) included zero, there was therefore no evidence to suggest a nonzero intercept. Graphical analysis of the model residuals was performed in order to check whether the assumptions about the model were correct. The assumptions made about the model21 were that the residuals are normally distributed random variables with a mean of 0 and variance σ2, that they are independent, that they have constant variance over the concentration range of interest, and that the variance is independent of the concentration. The first investigated figure (Figure 3a) was a probability plot of the expected value for a normal distribution versus the residuals. The points fell on a straight line, suggesting that the data followed a normal distribution. Studentized residuals were then plotted against the NIR values (Figure 3b) and showed that the residuals were randomly scattered above and below the zero horizontal of the Studentized values. Therefore, the residuals had a constant variance and were independent of the caffeine concentration. Precision Validation. Repeatability. The repeatability was demonstrated by performing 6 times the determination of a single (20) Haaland, D. M.; Thomas, E. V. Anal. Chem. 1988, 60, 1193-1202. (21) Massart, D. L.; Vandeginste, B. G. M.; Deming, S. N.; Michotte, Y.; Kaufman, L. In Chemometrics: a Textbook; Vandeginste, B. G. M., Kaufman, L., Eds.; Elservier Science Publishing Co. Inc.: New York, 1988; pp 76-80.

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Figure 3. Residual analysis for the statistical evaluation of the calibration equation: (a) probability plot of the expected values for a normal distribution versus the residuals and (b) Studentized residuals plotted against the NIR results.

tablet from two production batches: V1 and V2. Only one tablet per batch was analyzed in order to avoid recording error due to tablet-to-tablet manufacturing deviation. The mean and relative standard deviations (RSDs) were 58.47 (m/m) ( 0.74% and 60.01 (m/m) ( 0.55% for V1 and V2, respectively. As the RSDs were well below the usual acceptable criterion of 1%, the repeatability was validated. In addition, paired Student t-tests were used to compare the caffeine concentration determined from the front and back face of the tablets. The results for the two faces were significantly different (P < 0.005, n ) 6, for V1 and V2), which confirmed the feasibility results. The concentration difference between the two faces of the tablet was 1.4 and 1.0% (m/m) caffeine for V1 and V2, respectively. Intermediate Precision. The aim of this test is to establish the effects of random events on the precision of the procedure. In our study, the variable parameters were days and operators. This test was performed on two batches (V2 and V3) using six tablets per batch. An experimental design with three factors was applied to assess the intermediate precision: factor A ) operator (3 levels ) 3 different operators), factor B ) day of analysis (3 levels ) 3 days), and factor C ) batch used (2 levels). The results obtained by three analysts on three different days (n ) 9) for the two batches were as follows: mean (95% confidence interval ) 60.63 ( 0.22% and 59.62 ( 0.28%, and RSD ) 0.61 and 0.48% (m/m), respectively. These results are well below the usual accepted RSD of 2%. The variability of these two parameters was examined jointly by means of two-way analysis of the variance (ANOVA). Neither the parameters nor the interaction produced had any effect on 758

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the precision of the result (P ) 0.64 and 0.90, respectively, for the interaction effect on the results of the two batches). Specificity Validation. The feasibility study demonstrated (Figure 1) that the absorption peaks correlating with the caffeine concentration did not interfere with the excipient peaks. This result was verified by a comparison of the spectral residuals of three production batches (V4, V5, V6) and one excipient batch (VL1) when challenged with the method. Six tablets per batch were analyzed. The acceptance criterion (mean spectral residual + 3 standard deviations) was calculated from the results of production batches from the calibration set. One-sample t-tests confirmed that the mean residual of the excipient batch was significantly different (texp ) 24.8, t ) P < 2 × 10-5, n ) 6) and 35 times higher than the acceptance criterion. The mean spectral residuals from the production batches were within the acceptance criterion. The ability of the method to discriminate caffeine from theobromine and theophylline, two alkaloids with structures closely related to caffeine, was also evaluated. Due to manufacturing problems the theophylline and theobromine tablets (VL12 and VL13) were ∼3 times thinner and lighter than the caffeine tablets. Nevertheless, their spectra and second derivatives (Figure 4) showed significant differences between caffeine and theobromine or theophylline tablets. Thus, this method is able to discriminate caffeine from excipients and closely related compounds and the specificity is therefore validated. Linearity Validation. The linearity was already established in the calibration stage, on the basis of the evaluation of the calibration equation. The linearity was also established in the validation step by predicting different batches over the range of approximately 60-130% of the nominal caffeine concentration (about 35-75% caffeine in the tablets) and by comparing the results to HPLC reference values. To increase the number of batches, and because of the problems in producing several laboratory batches, the four laboratory batches from the calibration set were added to the linearity set. Linearity was thus established at 10 different concentrations (VL2-VL10, V7), using three tablets per concentration level. The regression line was calculated by the method of least squares. The equation for the NIR value () Y) of the caffeine concentration in percent (m/m) versus the HPLC value () X in % (m/m)) was Y ) 0.15(( 1.32) + 0.99(( 0.02)X. (R2 ) 0.986, SEC ) 1.38%, SEP )1.37%, and prediction bias -0.32%). The confidence interval for the slope (0.95-1.04) and for the y-intercept (-2.55-2.85) included 1 and 0, respectively. Moreover, the t-test proved that the y-intercept did not differ significantly from 0 (texp ) 0.11, P ) 0.91, n ) 30), and analysis of the variance proved that the slope also did not differ significantly from 1 (P ) 0.91). Figure 5 shows the correlation between the NIR and HPLC values for both the calibration and validation samples. The results obtained for excipient tablets (VL1) and pure caffeine tablets (VL11) were included in the plot for comparison purposes but not taken into account when the regression line was calculated. The NIR results seem to become nonlinear at very high concentrations of caffeine (>80%) but to remain linear over the lower range (0-30%). This phenomenon could be due to variations in the physical properties of the tablets pressed without excipient compared to those pressed with excipients. We can, however, conclude that the NIR results are linear with the HPLC

Figure 5. Correlation statistics between the caffeine content measured by NIR and HPLC. Three tablets per batch were determined from the calibration set (+) and validation set (O) samples.

Figure 4. Comparison of the spectral features between secondderivative spectra from laboratory-made tablets containing 58.82% theophylline (A), production tablets containing 58.82% caffeine (B), and laboratory-made tablets containing 58.82% theobromine (C) over the (a) 6200-5600- and (b) 4600-4000-cm-1 regions.

results within the range of 35-75% (m/m) caffeine. Accuracy Validation. The accuracy of our method can be expressed as the closeness of agreement between the HPLC and NIR values. The ICH guideline16 recommends assessing accuracy using a minimum of nine determinations over a minimum of three concentration levels. However, as the results could be affected by the physical differences of laboratory-made batches, accuracy was evaluated on both of the linearity set samples (consisting of laboratory-made and production samples) covering 10 concentration levels and on a set of 12 production batches (V7, V10-V20). The accuracy was approximated by the mean recovery between the NIR and HPLC results. Values of 99.4 and 98.9% were obtained for the two sets of samples, respectively. A further estimate was given by the SEP (1.37%) and the prediction bias (-0.32%) calculated from the linearity data set. Therefore, these estimations

confirm that the accuracy lies within the usual accepted limits of 98-102% for the recovery percentage. In addition, a paired Student t-test was applied to the results of the 12 production batches and confirmed that there was no significant difference between the NIR and the HPLC results (texp ) -1.84, P ) 0.09, n ) 12). The accuracy was also established because precision, linearity, and specificity were demonstrated. Range Validation. The range was validated because linearity, accuracy, and precision were validated. Quantification Limit Validation. Although the quantification limit (QL) is not required for the validation of assays, we found this parameter to be of interest and easy to approximate. Therefore, it was evaluated here, according to the ICH guideline,15 as QL ) 10σ/S, where σ is the standard deviation of the response, estimated by the residual standard deviation of the linearity regression line and S is the slope of the linearity regression line. The quantification limit was therefore 13.7% (m/m) caffeine in the tablets, which confirms the validity of the range. Robustness Validation. Even if the evaluation of robustness is not required for a marketing authorization application, it remains an interesting parameter for evaluating the method performance. For the current study, environmental conditions (temperature, humidity, direction of sunlight, and the presence of dust and vibrations) are always controlled to prevent them from affecting the results. Moffat et al.17 suggested study of the effects on the results when changing the sample presentation. This was very applicable in the current study because the tablet holder could be easily moved in the beam of the spectrometer. The robustness was therefore tested by performing six NIR determinations of the caffeine concentration in one tablet (V8) using the correct location of the sample holder, i.e., on the center of the beam (test 1), and six determinations of the same tablet with the sample holder located off-center (tests 2). One determination was the average of the determinations on two tablet faces. The background spectrum was acquired once before each test. The paired Student t-test showed no significant difference (texp ) 1.14, P ) 0.30, n ) 6) between the mean results of the two tests. However, the repeatability of the results was acceptable (