Dispersive Raman Spectroscopy for Quantifying Amorphous Drug Content in Intact Tablets.

Process-induced inadvertent phase change of an active pharmaceutical ingredient in a drug product could impact chemical stability, physical stability, shelf life, and bioperformance. In this study, dispersive Raman spectroscopy is presented as an alternative method for the nondestructive, high-throughput, at-line quantification of amorphous conversion. A quantitative Raman method was developed using a multivariate partial least squares (PLS) regression calibration technique with solid-state nuclear magnetic resonance (ssNMR) spectroscopy as the reference method. Compositionally identical calibration tablets containing 20% w/w total MK-A drug in varying weight proportions (0%-50% w/w based on total MK-A) of amorphous and crystalline MK-A were compressed at 10-45 kN force. PLS predictions of amorphous content of tablets using Raman spectroscopy correlated well with ssNMR quantification. The predictive accuracy of this model led to a strong correlation (R2 = 0.987) with a root mean-squared error of prediction of 1.5% w/w amorphous MK-A in tablets up to 50% w/w amorphous conversion in compressive stress range of 60-320 MPa. Overall, these results suggest that dispersive Raman spectroscopy offers fast, sensitive, and high-throughput (<5 min/tablet) method for quantitating amorphous conversion.

Development of robust quantitative methods by near-infrared spectroscopy for rapid pharmaceutical determination of content uniformity in complex tablet matrix.

Robust NIR transmission spectroscopic methods have been developed for determination of content uniformity (CU) of pharmaceutical products with a complex tablet matrix. The tablets of interest, formulated with eight components with active drug load of approximately 30% (w/w), are non-film coated, embossed, and round with thickness values of 3.6 and 5.6 mm, for the 125 and 500 mg dosage strength, respectively. The calibration data set contained seven laboratory scale batches of tablets with concentration range of active pharmaceutical ingredients (API) varying from 85 to 115% relative to label claim (LC) as well as four full scale production batches of tablets that included the natural physical variability of tablets. The reference concentration values were established by a high performance liquid chromatographic method. Partial least-squares (PLS) regression method was used to generate the calibration models. The root mean squared error of calibration for 125 and 500 mg was 1.6 and 1.5% in LC, respectively. The calibration models were validated in terms of measurement accuracy, repeatability, precision, robustness and transferability. Robustness assessment involved challenging the model with tablets incorporating variations in hardness, excipient vendors, excipient content and excipient particle size. The methods exhibited excellent measurement accuracy based on 87 batches (ten tablets for each batch) evaluated. The transferability of the developed NIR methods was demonstrated by comparing the NIR CU results associated with the same set of tablets scanned at the development site with those scanned at the production site. The result indicates that the NIR method can be used as a suitable alternative to the HPLC method for rapid tablet CU release test in pharmaceuticals.

Evaluation of transmission and reflection modalities for measuring content uniformity of pharmaceutical tablets with near-infrared spectroscopy.

This paper examines how one may assess spectral changes with instrument configuration (or composition), in combination with the spectral changes in the measurement that are caused by experimental effects, and subsequently select an appropriate measurement modality for tablet content uniformity determination with near-infrared (NIR) spectroscopy. Two NIR spectrometers furnished with three configurations in the sample measurement interface were evaluated. One spectrometer, Bruker MPA (multiple purpose analyzer), was equipped with two measurement modalities, diffuse transmission (DT) and diffuse reflection based on integrating sphere optics (DR/IS). The other spectrometer, Bruker StepOne, was equipped only with diffuse reflection mode based on a fiber-optic probe (DR/FO). The data were collected with each of the configurations for the tablets associated with two dosage strengths differing significantly in diameter and thickness. Spectral diagnosis was performed in terms of sensitivity and selectivity. The signal-to-noise ratio computed for the data collected with the DT and DR/IS spectrometers was approximately an order of magnitude greater than that computed for the DR/FO spectrometer. The net-analyte-signal-based selectivity analysis of NIR spectra associated with the sample tablet and the placebo tablet indicated that both transmission and reflection mode provided similar selectivity when the optimal spectral range was chosen. A partial least squares (PLS) calibration model was developed for each data set. The overall standard error of calibration for each DT and DR/IS measurement was approximately 0.3% in weight for each strength, significantly better than the value of 1.0% in weight produced by the DR/FO measurement. This result was consistent with the sensitivity analysis based on spectral noise characterization. The poor analytical performance of the DR/FO spectrometer was attributed to the small illumination spot size of the reflection probe and thus the sensitivity of the measurements to the tablet engraving. The PLS analysis and spectral diagnostics both showed that transmission and reflection modes based on the Bruker MPA provided similar measurement accuracy for each strength. However, the robustness study clearly revealed that the transmission mode would be more robust than the reflection mode when there is considerable variability in the chemical composition and physical properties of tablets.

Real-time on-line blend uniformity monitoring using near-infrared reflectance spectrometry: a noninvasive off-line calibration approach.

A robust, noninvasive, real-time, on-line near-infrared (NIR) quantitative method is described for blend uniformity monitoring of a pharmaceutical solid dosage form containing 29.4% (w/w) drug load with three major excipients (crospovidone, lactose, and microcrystalline cellulose). A set of 21 off-line, static calibration samples were used to develop a multivariate partial least-squares (PLS) calibration model for on-line prediction of the API content during the blending process. The concentrations of the API and the three major excipients were varied randomly to minimize correlations between the components. A micro electrical-mechanical system (MEMS) based portable, battery operated NIR spectrometer was used for this study. To minimize spectral differences between the static and dynamic measurement modes, the acquired NIR spectra were preprocessed using standard normal variate (SNV) followed by second derivative Savitzky-Golay using 21 points. The performance of the off-line PLS calibration model were evaluated in real-time on 16 laboratory scale (30 L bin size) blend experiments conducted over 3 months. To challenge the robustness of the off-line calibration model, several blend experiments were conducted using a different bin size, faster revolution speed and variations in the potency of the API. Employing the PLS calibration model developed using the off-line calibration approach, the real-time API NIR (%) predictions for all experiments were all within 90-110%. These results were confirmed using the conventional thief sampling of the final blend followed by high performance liquid chromatography (HPLC) analysis. Further confirmation was established through content uniformity by HPLC of manufactured tablets. Finally, the optimized off-line PLS method was successfully transferred to a production site which involved using a secondary NIR instrument with a 15-fold scale-up in bin size from development.

Robust calibration design in the pharmaceutical quantitative measurements with near-infrared (NIR) spectroscopy: Avoiding the chemometric pitfalls.

Quantification analysis with near-infrared (NIR) spectroscopy typically requires utilizing chemometric techniques, such as partial least squares (PLS) method, to achieve the desired selectivity. This article points out a major limitation of these statistical-based calibration methods. The limitation is that the techniques suffer from the potential for chance correlation. In this article, the impact of chance correlation on the robustness of PLS model was illustrated via a pharmaceutical application with NIR to the content uniformity determination of tablets. The procedure involves evaluating the PLS models generated with two sets of calibration tablets incorporated with distinct degree of concentration correlation between the active pharmaceutical ingredient (API) and excipients. The selectivity and robustness of the two models were examined by using a series of data sets associated with placebo tablets and tablets incorporated with variations from excipient content, hardness and particle size. The result clearly revealed that the strong correlation observed in the PLS model created by the correlated design was not solely based on the API information, and there was an intrinsic difference in the variances described by the two calibration models. Diagnostic tools that enable the characterization of the chemical selectivity of the calibration model were also proposed for pharmaceutical quantitative analysis.

Content uniformity determination of pharmaceutical tablets using five near-infrared reflectance spectrometers: a process analytical technology (PAT) approach using robust multivariate calibration transfer algorithms.

Near-infrared calibration models were developed for the determination of content uniformity of pharmaceutical tablets containing 29.4% drug load for two dosage strengths (X and Y). Both dosage strengths have a circular geometry and the only difference is the size and weight. Strength X samples weigh approximately 425 mg with a diameter of 12 mm while strength Y samples, weigh approximately 1700 mg with a diameter of 20mm. Data used in this study were acquired from five NIR instruments manufactured by two different vendors. One of these spectrometers is a dispersive-based NIR system while the other four were Fourier transform (FT) based. The transferability of the optimized partial least-squares (PLS) calibration models developed on the primary instrument (A) located in a research facility was evaluated using spectral data acquired from secondary instruments B, C, D and E. Instruments B and E were located in the same research facility as spectrometer A while instruments C and D were located in a production facility 35 miles away. The same set of tablet samples were used to acquire spectral data from all instruments. This scenario mimics the conventional pharmaceutical technology transfer from research and development to production. Direct cross-instrument prediction without standardization was performed between the primary and each secondary instrument to evaluate the robustness of the primary instrument calibration model. For the strength Y samples, this approach was successful for data acquired on instruments B, C, and D producing root mean square error of prediction (RMSEP) of 1.05, 1.05, and 1.22%, respectively. However for instrument E data, this approach was not successful producing an RMSEP value of 3.40%. A similar deterioration was observed for the strength X samples, with RMSEP values of 2.78, 5.54, 3.40, and 5.78% corresponding to spectral data acquired on instruments B, C, D, and E, respectively. To minimize the effect of instrument variability, calibration transfer techniques such as piecewise direct standardization (PDS) and wavelet hybrid direct standardization (WHDS) were used. The PDS approach, the RMSEP values for strength X samples were lowered to 1.22, 1.12, 1.19, and 1.08% for instruments B, C, D, and E, respectively. Similar improvements were obtained using the WHDS approach with RMSEP values of 1.36, 1.42, 1.36, and 0.98% corresponding to instruments B, C, D, and E, respectively.