Breakage and drying behaviour of granules in a continuous fluid bed dryer: Influence of process parameters and wet granule transfer

Although twin screw granulation has already been widely studied in recent years, only few studies addressed the subsequent continuous drying which is required after wet granulation and still suffers from a lack of detailed understanding. The latter is important for optimisation and control and, hence, a cost-effective practical implementation. Therefore, the aim of the current study is to increase understanding of the drying kinetics and the breakage and attrition phenomena during fluid bed drying after continuous twin screw granulation. Experiments were performed on a continuous manufacturing line consisting of a twin-screw granulator, a six-segmented fluid bed dryer, a mill, a lubricant blender and a tablet press. Granulation parameters were fixed in order to only examine the effect of drying parameters (filling time, drying time, air flow, drying air temperature) on the size distribution and moisture content of granules (both of the entire granulate and of size fractions). The wet granules were transferred either gravimetrically or pneumatically from the granulator exit to the fluid bed dryer. After a certain drying time, the moisture content reached an equilibrium. This drying time was found to depend on the applied airflow, drying air temperature and filling time. The moisture content of the granules decreased with an increasing drying time, airflow and drying temperature. Although smaller granules dried faster, the multimodal particle size distribution of the granules did not compromise uniform drying of the granules when the target moisture content was achieved. Extensive breakage of granules was observed during drying. Especially wet granules were prone to breakage and attrition during pneumatic transport, either in the wet transfer line or in the dry transfer line. Breakage and attrition of granules during transport and drying should be anticipated early on during process and formulation development by performing integrated experiments on the granulator, dryer and mill.

Multivariate statistical process control in product quality review assessment - A case study

According to the Food and Drug Administration and the European Good Manufacturing Practices (GMP) guidelines, Annual Product Review (APR) is a mandatory requirement in GMP. It consists of evaluating a large collection of qualitative or quantitative data in order to verify the consistency of an existing process. According to the Code of Federal Regulation Part 11 (21 CFR 211.180), all finished products should be reviewed annually for the quality standards to determine the need of any change in specification or manufacturing of drug products. Conventional Statistical Process Control (SPC) evaluates the pharmaceutical production process by examining only the effect of a single factor at the time using a Shewhart's chart. It neglects to take into account the interaction between the variables. In order to overcome this issue, Multivariate Statistical Process Control (MSPC) can be used. Our case study concerns an APR assessment, where 164 historical batches containing six active ingredients, manufactured in Morocco, were collected during one year. Each batch has been checked by assaying the six active ingredients by High Performance Liquid Chromatography according to European Pharmacopoeia monographs. The data matrix was evaluated both by SPC and MSPC. The SPC indicated that all batches are under control, while the MSPC, based on Principal Component Analysis (PCA), for the data being either autoscaled or robust scaled, showed four and seven batches, respectively, out of the Hotelling T² 95% ellipse. Also, an improvement of the capability of the process is observed without the most extreme batches. The MSPC can be used for monitoring subtle changes in the manufacturing process during an APR assessment.

Accuracy profiles assessing the validity for routine use of high-performance thin-layer chromatographic assays for drug formulations

The accuracy profile, based on total error, integrates several validation parameters, such as trueness, precision and linearity, providing one statistic which enables decision on the suitability of a method for its intended purpose. Two assay methods for formulations are validated using accuracy profiles as an alternative approach to classic method validation. It concerns high-performance thin-layer chromatography (HPTLC) methods, which initially were validated using the classic approach. The first method assayed sulfamethoxazole and trimethoprim, and the second lamivudine, stavudine and nevirapine. Both formulations are fixed-dose combination tablets. The resulting accuracy profiles showed that the 95% β-expectation tolerance limits for all compounds fell well within the bias acceptance limits set at ±5%. This means that the two analytical thin-layer chromatographic methods are capable of making accurate results at the studied concentration ranges of each compound. Measurement uncertainties of every compound at each concentration level could also be determined from the accuracy profile data.

HPTLC methods to assay active ingredients in pharmaceutical formulations: a review of the method development and validation steps

High-performance thin-layer chromatography (HPTLC) is still increasingly finding its way in pharmaceutical analysis in some parts of the world. With the advancements in the stationary phases and the introduction of densitometers as detection equipment, the technique achieves for given applications a precision and trueness comparable to high-performance liquid chromatography (HPLC). In this review, the literature is surveyed for developed and validated HPTLC methods to assay active ingredients in pharmaceutical formulations published in the period 2005-2011. Procedures and approaches for method development, validation and quantitative assays are compared with the standard ways of conducting them. Applications of HPTLC in some other areas are also briefly highlighted.

HPLC analysis of polyphenols in the fruits of Rubus idaeus L. (Rosaceae)

The separation of anthocyanins present in the fruits of 11 varieties of red raspberries (Rubus idaeus L.) was performed by high performance liquid chromatography (HPLC) with a diode-array detector and evaporative light scattering detection (ELSD). The ELSD parameters--drift tube temperature, nebulising gas flow rate and gain value--were optimised to get the best detection and identification of the anthocyanins. The varieties Heritage and Willamette had the simplest anthocyanin sets consisting of only two predominant anthocyanins--cyanidin-3-O-sophoroside (1) and cyanidin-3-O-glucoside (3), while in the other varieties two other predominant compounds were also present, cyanidin-3-O-rutinoside (4) and cyanidin-3-O-(2(G)-O-glucosylrutinoside) (2). Moreover, using ELSD, simultaneous analysis of anthocyanins and sanguiin H-6 (5), an ellagitannin, was performed. The contents of anthocyanins and sanguiin H-6 (5) were estimated by HPLC with ultraviolet-visible (UV-vis) light detection. The determined concentrations of anthocyanins varied from 76.22 to 277.06 mg per 100 g of dry weight (d.w.). The content of sanguiin H-6 (5) was in the range from 135.04 to 547.48 mg per 100 g of d.w.

Prediction and interpretation of the antioxidant capacity of green tea from dissimilar chromatographic fingerprints

Previously, multivariate calibration techniques have been successfully applied to model and predict the antioxidant activity of green tea from its chromatographic fingerprint. Since the selectivity differences between dissimilar chromatographic systems have already been valuably used in several applications, in this paper it is studied whether combining the complementary information contained in two dissimilar fingerprints can improve the predictive capacity of the multivariate calibration model. The simplest way of combining the data is concatenating both fingerprints for each sample. The resulting matrix can then be subjected to Orthogonal Projections to Latent Structures (O-PLS). Unfortunately, this approach resulted in a more complex model with a prediction error of about the average of the errors obtained with the individual fingerprints. Secondly, only the peaks with high loading and low orthogonal loading from both chromatograms were included in the O-PLS model. This resulted in a reduced complexity, but not in better predictions, probably due to a lack of complementarity of the information concerning the antioxidant capacity. Finally, the concatenated fingerprints were subjected to stepwise multiple linear regression (MLR) in order to build a model based on the variables most correlated with the antioxidant capacity. The obtained prediction error was lower than those of both previous approaches, but still higher than the error of the model based on a single analysis. This is probably again caused by a lack of complementarity in the variables. Nevertheless, it was advantageous to develop fingerprints on dissimilar system, because it enables to choose the most suited chromatographic profile to build a multivariate calibration model for the considered purpose. In contrast to what was expected, the study showed that the most simple (so the worst separated) fingerprints resulted in the best predictions. On the other hand, a more complex fingerprint in which more compounds are separated is still important to improve the interpretability of the model.

Drug impurity profiling: Method optimization on dissimilar chromatographic systems: Part I: pH optimization of the aqueous phase

The use of dissimilar chromatographic systems in drug impurity profiling can be very advantageous. Screening a new-drug impurity mixture on those systems not only enhances the chance that all impurities are revealed, but also allows choosing a suited system for further method development. In this paper several strategies were evaluated to predict the optimal pH (of the buffer used in the mobile phase) from the screening results. Four or five dissimilar stationary phases were screened at four pH values (between 2.5 and 9.4), in order to obtain maximal information about the composition of the sample and to select one column for the subsequent optimization. Different linear models (straight lines, 2nd and 3rd degree polynomials) based on these experiments were tested for their ability to predict the retention times (t(R)) of the impurities at intermediate pH values. The predicted t(R) values were then used to calculate minimal resolutions and eventually to select an optimal pH at which the highest minimal resolution is predicted. None of the applied models is accurate enough to predict correctly which peaks are worst separated at the indicated optimal pH. However, the best strategy (applying a second degree polynomial describing the t(R) measured at 3 consecutive screening pH values) did succeed in indicating an optimal pH at which a good separation of the impurities is obtained. Unfortunately, the resulting separation quality is not or only slightly better than the best separation obtained during screening. Therefore, it can be concluded that the most (time-) efficient approach to develop an impurity profile of a new drug is to screen it on four or five dissimilar columns at four different pH values and to retain the best screening conditions (without making predictions for intermediate conditions) for further optimization of the organic modifier composition of the mobile phase, and occasionally the temperature and the gradient. This is at least the case when the profiles have a complexity similar to those studied.

Raman spectroscopy as a process analytical technology (PAT) tool for the in-line monitoring and understanding of a powder blending process

The aim of this study is to propose a strategy to implement a PAT system in the blending step of pharmaceutical production processes. It was examined whether Raman spectroscopy can be used as PAT tool for the in-line and real-time endpoint monitoring and understanding of a powder blending process. A screening design was used to identify and understand the significant effects of two process variables (blending speed and loading of the blender) and of a formulation variable (concentration of active pharmaceutical ingredient (API): diltiazem hydrochloride) upon the required blending time (response variable). Interactions between the variables were investigated as well. A Soft Independent Modelling of Class Analogy (SIMCA) model was developed to determine the homogeneity of the blends in-line and real-time using Raman spectroscopy in combination with a fiber optical immersion probe. One blending experiment was monitored using Raman and NIR spectroscopy simultaneously. This was done to verify whether two independent monitoring tools can confirm each other's endpoint conclusions. The analysis of the experimental design results showed that the measured endpoints were excessively rounded due to the large measurement intervals relative to the first blending times. This resulted in effects and critical effects which cannot be interpreted properly. To be able to study the effects properly, the ratio between the blending times and the measurement intervals should be sufficiently high. In this study, it anyway was demonstrated that Raman spectroscopy is a suitable PAT tool for the endpoint control of a powder blending process. Raman spectroscopy not only allowed in-line and real-time monitoring of the blend homogeneity, but also helped to understand the process better in combination with experimental design. Furthermore, the correctness of the Raman endpoint conclusions was demonstrated for one process by using a second independent endpoint monitoring tool (NIR spectroscopy). Hence, the use of two independent techniques for the control of one response variable not only means a mutual confirmation of both methods, but also provides a higher certainty in the determined endpoint.

Implementation of a Process Analytical Technology System in a Freeze-Drying Process Using Raman Spectroscopy for In-Line Process Monitoring

The aim of the present study was to propose a strategy for the implementation of a Process Analytical Technology system in freeze-drying processes. Mannitol solutions, some of them supplied with NaCl, were used as models to freeze-dry. Noninvasive and in-line Raman measurements were continuously performed during lyophilization of the solutions to monitor real time the mannitol solid state, the end points of the different process steps (freezing, primary drying, secondary drying), and physical phenomena occurring during the process. At-line near-infrared (NIR) and X-ray powder diffractometry (XRPD) measurements were done to confirm the Raman conclusions and to find out additional information. The collected spectra during the processes were analyzed using principal component analysis and multivariate curve resolution. A two-level full factorial design was used to study the significant influence of process (freezing rate) and formulation variables (concentration of mannitol, concentration of NaCl, volume of freeze-dried sample) upon freeze-drying. Raman spectroscopy was able to monitor (i) the mannitol solid state (amorphous, alpha, beta, delta, and hemihydrate), (ii) several process step end points (end of mannitol crystallization during freezing, primary drying), and (iii) physical phenomena occurring during freeze-drying (onset of ice nucleation, onset of mannitol crystallization during the freezing step, onset of ice sublimation). NIR proved to be a more sensitive tool to monitor sublimation than Raman spectroscopy, while XRPD helped to unravel the mannitol hemihydrate in the samples. The experimental design results showed that several process and formulation variables significantly influence different aspects of lyophilization and that both are interrelated. Raman spectroscopy (in-line) and NIR spectroscopy and XRPD (at-line) not only allowed the real-time monitoring of mannitol freeze-drying processes but also helped (in combination with experimental design) us to understand the process.

Influence of preparation method on itraconazole oral solutions using cyclodextrins as complexing agents

In the literature, solubility values of itraconazole complexed with 2-hydroxypropyl-beta-cyclodextrin (HP-beta-CD) were found which were still much too low to obtain the target concentration of 1 g itraconazole/100 ml, the concentration of the marketed itraconazole formulation Sporanox (Janssen Pharmaceutica). Therefore, we compared two preparation methods: the classical and the dissolving method to investigate if the method of preparation can have an influence on the solubility of itraconazole complexed with cyclodextrin (CD). With the classical method, the active compound and the CDs are jointly dissolved with a co-solvent, propylene glycol, in water. With the dissolving method, the active compound is first dissolved separately in a solvent in which it dissolves well, while the CDs are dissolved in water, before mixing. Three different CDs were used and compared for their complexing capacity with itraconazole. The complex formation of itraconazole with HP-beta-CD, sulfobutylether-7-beta-cyclodextrin (SBE-7-beta-CD) and maltosyl-beta-cyclodextrin (malt-beta-CD) was investigated at pH 2, in the presence of 10% propylene glycol for an oral solution. These three CDs were chosen as they can also serve in formulations for parenteral use. The method of preparation had an important influence on the complex formation. With the dissolving method, a much higher solubility of itraconazole was obtained using the same CD concentration than with the classical method. Inclusion capacity obtained with the dissolving method was comparable for HP-beta-CD and SBE-7-beta-CD: 1 g itraconazole/100 ml of 25% HP-beta-CD or of 30% SBE-7-beta-CD. In 100 ml of 40% malt-beta-CD only about 500 mg of itraconazole could be dissolved. With the classical method only around 160 mg itraconazole could be dissolved with 100 ml 40 % HP-beta-CD or SBE-7-beta-CD. Due to the fast preparation, once the CD amount is known by pretests, the dissolving method shows also an advantage for industrial production.

Comparison of Plackett–Burman and supersaturated designs in robustness testing

An optimized FIA assay of L-N-monomethylarginine (LNMMA) was validated. The linearity, precision, accuracy and range of the analytical method were evaluated and robustness testing was performed. Several experimental designs for robustness testing containing different numbers of experiments (N) were compared. Both Plackett-Burman (N=8 or 12) and supersaturated designs (N=6) were examined. The latter design results were analyzed with the Fixing Effects and Adding Rows (FEAR) method, based on the initial addition of zero effect rows to the model matrix, which then are iteratively replaced by fixed effects. It was evaluated whether by reducing the number of experiments from 12 to 8 or 6, similar effects are estimated and considered (non-)significant. The FIA method was found linear in a range of 70-130% of the LNMMA concentration in the samples, and precise and accurate in a range of 80-120%. The estimated factor effects and the critical effects were found comparable for all examined designs, though there also are some indications that some from the supersaturated designs tend to be overestimated. The method was considered robust, since no significant effects occurred for the response describing the quantitative aspect of the method. For other responses, such as peak height and residence time, significant effects occur. However, only the most important effects are found with all designs. The effects reported from a supersaturated design based on the FEAR method still can be subject of further research.

Influence of particle size on the quantitative determination of salicylic acid in a pharmaceutical ointment using FT-Raman spectroscopy

A second order polynomial calibration model was developed and statistically validated for the direct and non-destructive quantitative analysis - without sample preparation - of the active pharmaceutical ingredient (API) salicylic acid in a pharmaceutical ointment using FT-Raman spectroscopy. The calibration curve was modeled by plotting the peak intensity of the vector normalized spectral band between 757 and 784cm(-1) against the known salicylic acid concentrations in standards. At this band, no spectral interferences from the ointment vehiculum (white vaseline) are observed. For the validation of the polynomial model, its fit and its predictive properties were evaluated. The validated model was used for the quantification of 25 ointments, compounded by different retail pharmacists. The same standards and samples were used, both for development and validation of a regression model and for quantitative determination by HPLC - with sample preparation - as described for the related substances of salicylic acid in the Ph. Eur. IV. The quantification results obtained by the FT-Raman method corresponded with the HPLC results (p=0.22), provided that the particle size of salicylic acid in the standards is the same as in the analyzed samples. The non-destructive FT-Raman method is a reliable alternative for the destructive HPLC method, as it is faster and does not require sample pre-treatment procedures.

Preparation and evaluation of paclitaxel-containing liposomes

Paclitaxel, an antitumoral drug, is poorly soluble in aqueous media. Therefore, in a commercialised formulation (Taxol), paclitaxel (30 mg active compound) is dissolved in polyethoxylated castor oil (Cremophor EL) and ethanol. After dilution of Taxol in aqueous media paclitaxel tends to precipitate. Several side effects, attributed to the surfactant Cremophor EL, occur, e.g. bronchospasm, hypotension, neuro- and nephrotoxicity, and anaphylactic reactions. To eliminate these side effects, the solubility of paclitaxel was enhanced using liposomes instead of Cremophor EL. The amount of entrapped paclitaxel in crystal-free liposomes was 0.5 mg/ml liposome suspension, i.e. almost 85 times the native solubility. Thus, 30 mg paclitaxel had to be dissolved in 60 ml liposome suspension, of either multi-lamellar vesicles (MLV's) or of small unilamellar vesicles (SUV's) with 5% sucrose as cryoprotector. No precipitation was observed after dilution of the MLV-formulation with (physiological) water or with 5% aqueous dextrose solution, which proves their suitability for administration with perfusions. The chemical stability of paclitaxel in the prepared MLV's stored at 4 degrees C was demonstrated during a period of 5 months. The chemical degradation to conjugated dienes and hydroperoxides, two oxidative degradation products of EPC, was negligible (less than 1%).

Direct orthogonal signal correction as data pretreatment in the classification of clinical lots of creams from near infrared spectroscopy data

Direct orthogonal signal correction (DOSC) is applied to correct for major variance sources such as temperature effects, time influences and instrumental differences in near infrared (NIR) data. The samples analysed are creams containing different concentrations of an active drug. The final aim is to classify the samples according to their concentration of active compound. Having performed DOSC on the data, it is not necessary anymore to apply sophisticated chemometric techniques to correct for temperature or time effects and to attribute the samples to their respective concentration classes. Moreover, the application of DOSC on the NIR spectra recorded on two different instruments shows that this method can be considered as a valuable alternative for the standardisation in classification applications. Since the applied algorithm tends to overfit, in a second part of this paper, a comparison is made with an algorithm designed by Westerhuis, which should overcome this problem. Although the calibration set results show that the overfitting has been partially corrected for by the latter algorithm, the test set results did not improve significantly.

Exploration of linear modelling techniques and their combination with multivariate adaptive regression splines to predict gastro-intestinal absorption of drugs

In general, linear modelling techniques such as multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS), are used to model QSAR data. This type of data can be very complex and linear modelling techniques often model only a limited part of the information captured in the data. In this study, it was tried to combine linear techniques with the flexible non-linear technique multivariate adaptive regression splines (MARS). Models were built using an MLR model, combined with either a stepwise procedure or a genetic algorithm for variable selection, a PCR model or a PLS model as starting points for the MARS algorithm. The descriptive and predictive power of the models was evaluated in a QSAR context and compared to the performances of the individual linear models and the single MARS model. In general, the combined methods resulted in significant improvements compared to the linear models and can be considered valuable techniques in modelling complex QSAR data. For the used data set the best model was obtained using a combination of PLS and MARS. This combination resulted in a model with a Pearson correlation coefficient of 0.90 and a cross-validation error, evaluated with 10-fold cross-validation of 9.9%, pointing at good descriptive and high predictive properties.

Evaluation of chromatographic descriptors for the prediction of gastro-intestinal absorption of drugs

The use of chromatographic descriptors in QSAR was evaluated. Therefore, retentions were measured on an immobilized artificial membrane system, 2 micellar liquid chromatography systems and 17 orthogonal or disimilar reversed-phase liquid chromatographic systems. It was investigated whether it was possible to model gastro-intestinal absorption as a function of chromatographic retentions applying two linear and one non-linear multivariate modeling technique. In a second step it was evaluated if models built with theoretical descriptors could be improved by adding the measured retention factors to the data set of descriptive variables. It was seen that gastro-intestinal absorption could be modelled in function of chromatographic retention using the non-linear modeling technique multivariate adaptive regression splines (MARS). The best models were obtained using a combination of theoretical and chromatographic descriptors with MARS as modeling technique.

Robustness testing of a chiral NACE method for R-timolol determination in S-timolol maleate and uncertainty assessment from quantitative data

A robustness test of a capillary electrophoresis method for the chiral separation of timolol in nonaqueous acidified media was performed. A two-level Plackett-Burman design was applied in which one qualitative and six quantitative factors were examined. Resolution, migration times and relative migration times to pyridoxine (selected as internal standard) were examined as qualitative responses to evaluate electrophoretic performance. A quantitative response, the content of R-timolol in S-timolol maleate sample, was also considered. Even though some significant factor effects were observed on the qualitative responses, it was still possible to quantify the R-timolol in the S-timolol maleate samples properly. The quantitative response was not significantly affected by the selected factors, demonstrating the robustness of the procedure. However, the use of different HDMS-beta-CD batches seemed to affect both types of responses necessitating to introduce a warning in the procedure. Since the experiments of the Plackett-Burman design can be assimilated to laboratories in an interlaboratory study, uncertainty can be evaluated using the robustness test data. The robustness test was set-up in such a way that the required variances could be estimated.

Increasing conclusiveness of metabonomic studies by chem-informatic preprocessing of capillary electrophoretic data on urinary nucleoside profiles

Nowadays, bioinformatics offers advanced tools and procedures of data mining aimed at finding consistent patterns or systematic relationships between variables. Numerous metabolites concentrations can readily be determined in a given biological system by high-throughput analytical methods. However, such row analytical data comprise noninformative components due to many disturbances normally occurring in analysis of biological samples. To eliminate those unwanted original analytical data components advanced chemometric data preprocessing methods might be of help. Here, such methods are applied to electrophoretic nucleoside profiles in urine samples of cancer patients and healthy volunteers. The electrophoretic nucleoside profiles were obtained under following conditions: 100 mM borate, 72.5 mM phosphate, 160 mM SDS, pH 6.7; 25 kV voltage, 30 degrees C temperature; untreated fused silica capillary 70 cm effective length, 50 microm I.D. Different most advanced preprocessing tools were applied for baseline correction, denoising and alignment of electrophoretic data. That approach was compared to standard procedure of electrophoretic peak integration. The best results of preprocessing were obtained after application of the so-called correlation optimized warping (COW) to align the data. The principal component analysis (PCA) of preprocessed data provides a clearly better consistency of the nucleoside electrophoretic profiles with health status of subjects than PCA of peak areas of original data (without preprocessing).

Improving method capability of a drug substance HPLC assay

The assay of a drug substance (DS) is one of the tests required to confirm the active pharmaceutical ingredient (API) quality at release. In the past, usually volumetric titration methods were performed, that were precise, but often non-specific. Nowadays specific chromatographic assay procedures are preferred. However, high performance liquid chromatographic (HPLC) methods, the way they are usually executed, tend to be less precise and have a larger total method variation compared to titration methods. The capabilities of fully validated titration and HPLC assay methods were determined and compared. It was studied which factors had the largest effects on the capability of chromatographic HPLC methods in order to improve their precision and precision-to-tolerance ratio. This was done using multiple Gage R&R (repeatability & reproducibility) studies and an experimental design approach. The investigations showed that it was feasible to define an HPLC method with a similar capability as the titration method. The most important factor determining the precision was demonstrated to be higher sample and reference material weights. When low weights are to be used, increasing the number of sample preparations and the number of reference solutions may enhance the method capability.

Chemometric treatment of vanillin fingerprint chromatograms

This study describes the chemometric treatment of vanillin fingerprint chromatograms to distinguish vanillin from different sources. Prior to principal component analysis, which is used to discriminate vanillin from different origins, the fingerprints are aligned. Three alignment algorithms are tested, correlation optimized warping (COW), target peak alignment (TPA) and semi-parametric time warping (STW). The performance of the three algorithms is evaluated and the effect of the different alignments on the PCA score plots is investigated. The alignment obtained with STW differs somewhat from that with COW and TPA. However, equivalent score plots were obtained regarding the different vanillin groups.