Jérôme Mantanus

Moisture content determination of pharmaceutical pellets by near infrared spectroscopy: Method development and validation

The aim of the present study was to develop and validate a near infrared method able to accurately determine a moisture content of pharmaceutical pellets ranging from 1% to 8% in order to check their moisture content conformity. A calibration and validation set were designed for the conception and evaluation of the method adequacy. An experimental protocol was then followed, involving two operators, independent production campaign batches and different temperatures for data acquisition. On the basis of this protocol, prediction models based on partial least squares (PLS) regression were then carried out. Conventional criteria such as the R(2), the root mean square errors of calibration and prediction (RMSEC and RMSEP) as well as the number of PLS factors enabled the selection of three preliminary models. However, such criteria did not clearly demonstrate the models ability to give accurate predictions over the whole analyzed water content range. Consequently, a novel approach based on accuracy profiles which allow the selection of the most fitted model for purpose was used. According to this novel approach, the model using multiplicative scatter correction (MSC) pre-treatment was obviously the most suitable. Indeed, the resulting accuracy profile clearly showed that this model was able to determine moisture content over the range of 1-8% with a very acceptable accuracy. The present study confirmed that NIR spectroscopy could be used in the PAT concept as a non-invasive, non-destructive and fast technique for moisture content determination in pharmaceutical pellets. In addition, facing the limit of the classical and commonly used criteria, the use of accuracy profiles proved to be useful as a powerful decision tool to demonstrate the suitability of the proposed analytical method.

Critical review of near-infrared spectroscopic methods validations in pharmaceutical applications

Based on the large number of publications reported over the past five years, near-infrared spectroscopy (NIRS) is more and more considered an attractive and promising analytical tool regarding Process Analytical Technology and Green Chemistry. From the reviewed literature, few of these publications present a thoroughly validated NIRS method even if some guidelines have been published by different groups and regulatory authorities. However, as any analytical method, the validation of NIRS method is a mandatory step at the end of the development in order to give enough guarantees that each of the future results during routine use will be close enough to the true value. Besides the introduction of PAT concepts in the revised document of the European Pharmacopoeia (2.2.40) dealing with near-infrared spectroscopy recently published in Pharmeuropa, it agrees very well with this mandatory step. Indeed, the latter suggests to use similar analytical performance characteristics than those required for any analytical procedure based on acceptance criteria consistent with the intended use of the method. In this context, this review gives a comprehensive and critical overview of the methodologies applied to assess the validity of quantitative NIRS methods used in pharmaceutical applications.

Acetaminophen determination in low-dose pharmaceutical syrup by NIR spectroscopy

The aim of the present study was first to develop a robust near infrared (NIR) calibration model able to determine the acetaminophen content of a low-dose syrup formulation (2%, w/v). Therefore, variability sources such as production campaigns, batches, API concentration, syrup basis, operators and sample temperatures were introduced in the calibration set. A prediction model was then built using partial least square (PLS) regression. First derivative followed by standard normal variate (SNV) were chosen as signal pre-processing. Based on the random subsets cross-validation, 4 PLS factors were selected for the prediction model. The method was then validated for an API concentration ranging from 16 to 24 mg/mL (1.6-2.4%, w/v) using an external validation set. The 0.26 mg/mL RMSEP suggested the global accuracy of the model. The accuracy profile obtained from the validation results, based on tolerance intervals, confirmed the adequate accuracy of the results generated by the method all over the investigated API concentration range. Finally, the NIR model was used to monitor in real time the API concentration while mixing syrups containing various amounts of API, a good agreement was found between the NIR method and the theoretical concentrations.

Active content determination of non-coated pharmaceutical pellets by near infrared spectroscopy: method development, validation and reliability evaluation.

A robust near infrared (NIR) method able to quantify the active content of pilot non-coated pharmaceutical pellets was developed. A protocol of calibration was followed, involving 2 operators, independent pilot batches of non-coated pharmaceutical pellets and two different NIR acquisition temperatures. Prediction models based on Partial Least Squares (PLS) regression were then carried out. Afterwards, the NIR method was fully validated for an active content ranging from 80 to 120% of the usual active content using new independent pilot batches to evaluate the adequacy of the method to its final purpose. Conventional criteria such as the R(2), the Root Mean Square Error of Calibration (RMSEC), the Root Mean Square Error of Prediction (RMSEP) and the number of PLS factors enabled the selection of models with good predictive potential. However, such criteria sometimes fail to choose the most fitted for purpose model. Therefore, a novel approach based on accuracy profiles of the validation results was used, providing a visual representation of the actual and future performances of the models. Following this approach, the prediction model using signal pre-treatment Multiplicative Scatter Correction (MSC) was chosen as it showed the best ability to quantify accurately the active content over the 80-120% active content range. The reliability of the NIR method was tested with new pilot batches of non-coated pharmaceutical pellets containing 90 and 110% of the usual active content, with blends of validation batches and industrial batches. All those batches were also analyzed by the HPLC reference method and relative errors were calculated: the results showed low relative errors in full accordance with the results obtained during the validation of the method, indicating the reliability of the NIR method and its interchangeability with the HPLC reference method.

Building the quality into pellet manufacturing environment – Feasibility study and validation of an in-line quantitative near infrared (NIR) method

The present study focuses on the implementation of an in-line quantitative near infrared (NIR) spectroscopic method for determining the active content of pharmaceutical pellets. The first aim was to non-invasively interface a dispersive NIR spectrometer with four realistic particle streams existing in the pellets manufacturing environment. Regardless of the particle stream characteristics investigated, NIR together with Principal Component Analysis (PCA) was able to classify the samples according to their active content. Further, one of these particle stream interfaces was non-invasively investigated with a FT-NIR spectrometer. A predictive model based on Partial Least Squares (PLS) regression was able to determine the active content of pharmaceutical pellets. The NIR method was finally validated with an external validation set for an API concentration range from 80 to 120% of the targeted active content. The prediction error of 0.9% (root mean standard error of prediction, RMSEP) was low, indicating the accuracy of the NIR method. The accuracy profile on the validation results, an innovative approach based on tolerance intervals, demonstrated the actual and future performance of the in-line NIR method. Accordingly, the present approach paves the way for real-time release-based quality system.

Near infrared and Raman spectroscopy as Process Analytical Technology tools for the manufacturing of silicone-based drug reservoirs.

Using near infrared (NIR) and Raman spectroscopy as PAT tools, 3 critical quality attributes of a silicone-based drug reservoir were studied. First, the Active Pharmaceutical Ingredient (API) homogeneity in the reservoir was evaluated using Raman spectroscopy (mapping): the API distribution within the industrial drug reservoirs was found to be homogeneous while API aggregates were detected in laboratory scale samples manufactured with a non optimal mixing process. Second, the crosslinking process of the reservoirs was monitored at different temperatures with NIR spectroscopy. Conformity tests and Principal Component Analysis (PCA) were performed on the collected data to find out the relation between the temperature and the time necessary to reach the crosslinking endpoints. An agreement was found between the conformity test results and the PCA results. Compared to the conformity test method, PCA had the advantage to discriminate the heating effect from the crosslinking effect occurring together during the monitored process. Therefore the 2 approaches were found to be complementary. Third, based on the HPLC reference method, a NIR model able to quantify the API in the drug reservoir was developed and thoroughly validated. Partial Least Squares (PLS) regression on the calibration set was performed to build prediction models of which the ability to quantify accurately was tested with the external validation set. The 1.2% Root Mean Squared Error of Prediction (RMSEP) of the NIR model indicated the global accuracy of the model. The accuracy profile based on tolerance intervals was used to generate a complete validation report. The 95% tolerance interval calculated on the validation results indicated that each future result will have a relative error below ±5% with a probability of at least 95%. In conclusion, 3 critical quality attributes of silicone-based drug reservoirs were quickly and efficiently evaluated by NIR and Raman spectroscopy.

PAT tools for the control of co-extrusion implants manufacturing process

Hot melt extrusion is a novel pharmaceutical manufacturing process technique. In this study, we identified four Critical Quality Attributes (CQAs) of the implant manufacturing process by hot melt extrusion: the implant diameter, the quantity of the Active Pharmaceutical Ingredient (API), the homogeneity distribution of API and the thickness of the membrane. We controlled the implant diameter and the quantity of API in-line with a laser measurement, NIR and Raman spectroscopy, respectively. These two different spectroscopic techniques provided comparable results. In fact, the RMSEC and RMSECV were very close in each PAT technique but NIR spectroscopy was easier to use and less sensitive to external changes. For the control of the homogeneity of API distribution and the thickness of the membrane, we used successfully Raman spectroscopy imaging. These PAT tools help reducing analysis time.

Determination of binary polymorphic mixtures of fluconazole using near infrared spectroscopy and X-ray powder diffraction: A comparative study based on the pre-validation stage results

The aim of the present study was to develop near infrared (NIR) and X-ray powder diffraction methods (XRPD) able to determine pure crystalline form II of fluconazole in a binary polymorphic mixtures containing forms II and III. In order to give a first performance estimation of both methods, these latters were pre-validated using accuracy profiles, a statistical approach based on β-expectation tolerance intervals. Both methods showed a good trueness, precision and accuracy and their β-expectation tolerance intervals were fully included within the acceptance limits. The comparative study was carried out using statistical analysis based on the work of Bland and Altman. A good agreement between the two methods was demonstrated indicating the interchangeability of NIR method with XRPD method.

A Review of PAT Strategies in Secondary Solid Oral Dosage Manufacturing of Small Molecules

Pharmaceutical solid oral dosage product manufacturing is a well-established, yet revolutionizing area. To this end, process analytical technology (PAT) involves interdisciplinary and multivariate (chemical, physical, microbiological, and mathematical) methods for material (e.g., materials, intermediates, products) and process (e.g., temperature, pressure, throughput, etc.) analysis. This supports rational process modeling and enhanced control strategies for improved product quality and process efficiency. Therefore, it is often difficult to orient and find the relevant, integrated aspects of the current state-of-the-art. Especially, the link between fundamental research, in terms of sensor and control system development, to the application both in laboratory and manufacturing scale, is difficult to comprehend. This review compiles a nonexhaustive overview on current approaches from the recognized academia and industrial practices of PAT, including screening, selection, and final implementations in solid oral dosage manufacturing, through a wide diversity of use cases. Finally, the authors attempt to extract a common consensus toward developing PAT application guidance for different unit operations of drug product manufacturing.