Simple assessment of homogeneity in pharmaceutical mixing processes using a near-infrared reflectance probe and control charts (original) (raw)
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International Journal of Pharmaceutics, 2014
The implementation of a blend monitoring and control method based on a process analytical technology such as near infrared spectroscopy requires the selection and optimization of numerous criteria that will affect the monitoring outputs and expected blend end-point. Using a five component formulation, the present article contrasts the modeling strategies and end-point determination of a traditional quantitative method based on the prediction of the blend parameters employing partial least-squares regression with a qualitative strategy based on principal component analysis and Hotelling's T 2 and residual distance to the model, called Prototype. The possibility to monitor and control blend homogeneity with multivariate curve resolution was also assessed. The implementation of the above methods in the presence of designed experiments (with variation of the amount of active ingredient and excipients) and with normal operating condition samples (nominal concentrations of the active ingredient and excipients) was tested. The impact of criteria used to stop the blends (related to precision and/or accuracy) was assessed. Results demonstrated that while all methods showed similarities in their outputs, some approaches were preferred for decision making. The selectivity of regression based methods was also contrasted with the capacity of qualitative methods to determine the homogeneity of the entire formulation.
Analytical control of pharmaceutical production steps by near infrared reflectance spectroscopy
Analytica Chimica Acta, 1999
A method for the analytical control of different pharmaceutical production steps involving various types of sample (blended products, cores and coated tablets) is proposed. The measurements are made by using a near infrared (NIR) diffuse re¯ectance spectrophotometer furnished with a ®bre-optic module that enables expeditious,¯exible analyses with no sample manipulation.
2007
This study investigates the use of a laboratory scale blender fitted with a near infrared probe to monitor lubricant uniformity in a granule blend. A software method was developed to monitor the change in absorbance at significant wavelengths for the granule and lubricant (magnesium stearate) as the blend proceeded in real-time. The standard deviation of the absorbance was plotted as a function of time to monitor the change in the blend. With near infrared spectra, when a process is complete, the spectra will not change, therefore the standard deviation will be small [6]. To verify this, the blend was sampled using a standard sampling method and analyzed with an atomic absorption method for magnesium stearate to ascertain the distribution in the blend. Blends sampled at the predetermined time intervals were well blended when the standard deviation of the absorbance was low and poorly blended when the standard deviation of the absorbance was high, thus verifying the near infrared pre...
International journal of pharmaceutics, 2005
This research note demonstrates the simultaneous quantitation of a pharmaceutical active ingredient and three excipients in a simulated powder blend containing acetaminophen, Prosolv and Crospovidone. An experimental design approach was used in generating a 5-level (%, w/w) calibration sample set that included 125 samples. The samples were prepared by weighing suitable amount of powders into separate 20-mL scintillation vials and were mixed manually. Partial least squares (PLS) regression was used in calibration model development. The models generated accurate results for quantitation of Crospovidone (at 5%, w/w) and magnesium stearate (at 0.5%, w/w). Further testing of the models demonstrated that the 2-level models were as effective as the 5-level ones, which reduced the calibration sample number to 50. The models had a small bias for quantitation of acetaminophen (at 30%, w/w) and Prosolv (at 64.5%, w/w) in the blend. The implication of the bias is discussed.
European Journal of Pharmaceutics and Biopharmaceutics, 2013
The aim of this study was to develop a quantitative Near-Infrared (NIR) method which monitors the homogeneity of a pharmaceutical formulation coming out of a continuous blender. For this purpose, a NIR diode array spectrometer with fast data acquisition was selected. Additionally, the dynamic aspects of a continuous blending process were studied; the results showed a well-defined cluster for the steady state, and the paths for the start-up and emptying stages were clearly identified. The end point of the start-up phase was detected by moving block of standard deviation, relative standard deviation, and principal component analysis.
Efficient Near-Infrared Spectroscopic Calibration Methods for Pharmaceutical Blend Monitoring
Journal of Pharmaceutical …
Near-infrared (NIR) spectroscopy is an important analytical tool for online process monitoring of pharmaceutical unit operations. Traditionally, the development and maintenance of robust, precise, and accurate quantitative NIR calibrations requires a substantial investment for the creation of sample sets. This study demonstrates the ability to develop efficient NIR calibrations using reduced sample sets. Prediction performance of several multivariate algorithms was compared on two different NIR spectrometers for pharmaceutical blend monitoring. Classical least-squares (CLS)-based algorithms took advantage of pure component scans to produce the most sensitive quantitative calibrations using reduced sample sets when compared to partial least squares (PLS) regression and two nonlinear methods. The PLS algorithm and the nonlinear methods produced models with low error but lacked the sensitivity needed to model subtle blending trends. The CLS-based methods produced models with adequate sensitivity for blend monitoring. The robustness of the CLS-based methods was further demonstrated in the ease of transfer between instruments using only a bias correction of the predictions.
Pharmaceutical Blend uniformity Near-infrared Partial least-squares Off-line calibration
A multivariate calibration approach using near-infrared (NIR) spectroscopy for determining blend uniformity end-point of a pharmaceutical solid dosage form containing 29.4% (w/w) drug load with three major excipients (crospovidone, lactose, and microcrystalline cellulose) is presented. A set of 21 off-line, static calibration samples were used to develop a multivariate partial least-squares (PLS) calibration model for on-line predictions 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 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 Savitsky-Golay using 21 points. The performance of the off-line PLS calibration model were evaluated in real-time on 67 production scale (750 L bin size) blend experiments conducted over 3 years. The real-time API-NIR (%) predictions of all batches ranged from 93.7% to 104.8% with standard deviation ranging from 0.5% to 1.8%. These results showed the attainment of blend homogeneity and were confirmed with content uniformity by HPLC of respective manufactured tablets values ranging from 95.4% to 101.3% with standard deviation ranging from 0.5% to 2.1%. Furthermore, the performance of the PLS calibration model was evaluated against off-target batches manufactured with high and low amounts of water during the granulation phase of production. This approach affects the particle size and hence blending. All the off-target batches exhibited API-NIR (%) predictions of 94.6% to 103.5% with standard deviation ranging from 0.7% to 1.9%. Using off-target data, a systematic approach was developed to determine blend uniformity endpoint. This was confirmed with 3 production scale batches whereby the blend uniformity end-point was determined using the PLS calibration model. Subsequently, the uniformity was also ascertained with conventional thief sampling followed by HPLC analysis and content uniformity by HPLC of the manufactured tablets.