Rafael Méndez

Mixing order of glidant and lubricant – Influence on powder and tablet properties

The main objective of the present work was to study the effect of mixing order of Cab-O-Sil (CS) and magnesium stearate (MgSt) and microlayers during mixing on blend and tablet properties. A first set of pharmaceutical blend containing Avicel PH200, Pharmatose and micronized acetaminophen was prepared with three mixing orders (mixing order-1: CS added first; mixing order-2: MgSt added first; mixing order-3: CS and MgSt added together). All the blends were subjected to a shear rate of 80 rpm and strain of 40, 160 and 640 revolutions in a controlled shear environment resulting in nine different blends. A second set of nine blends was prepared by replacing Avicel PH200 with Avicel PH102. A total of eighteen blends thus prepared were tested for powder hydrophobicity, powder flow, tablet weight, tablet hardness and tablet dissolution. Results indicated that powder hydrophobicity increased significantly for mixing order-1. Intermediate hydrophobic behavior was found for mixing order-3. Additionally, mixing order 1 resulted in improved powder flow properties, low weight variability, higher average tablet weight and slow drug release rates. Dissolution profiles obtained were found to be strongly dependent not only on the mixing order of flowing agents, but also on the strain and the resulting hydrophobicity.

Analysis of powder phenomena inside a Fette 3090 feed frame using in-line NIR spectroscopy.

New analytical methods are needed to understand and optimize the processes by which tablets are produced. Fette 3090 tablet presses are commonly used in the pharmaceutical industry. A near-infrared (NIR) probe was installed into a Fette 3090 feed frame to understand and monitor the die filling process. The second objective was to analyze in detail the different factors that could affect the prediction of the developed NIR calibration models. Two monitoring positions for NIR spectrometers were evaluated; one at each side of the feed frame. A powder wave behavior caused by the paddle motion was observed inside the feed frame. The study also revealed that NIR spectra can help in the understanding of powder flow inside the feed frame. It was demonstrated that NIR spectra baselines can also be used to determine changes in mass inside the feed frame. The new NIR method showed that the paddle wheel speed has a significant impact in the powder dynamics inside the feed frame. The baselines of the NIR spectra depended on the mass hold-up inside the feed frame and paddle wheel speed. Studies using blends were performed to develop a NIR calibration model based on the feed frame system dynamics to determine acetaminophen drug concentration variability during the die filling process. The study found that variation in the distance from the powder to the probe due to paddle wheel speed has a significant effect on the NIR prediction. This study found that with NIR spectroscopy, blend uniformity can be assessed with high accuracy during the die filling process using the corresponding paddle wheel speed in-line calibration model. NIR was demonstrated to be a good development tool for the in-line monitoring of powder during the die filling process.

Evaluation of strain-induced hydrophobicity of pharmaceutical blends and its effect on drug release rate under multiple compression conditions

Objective: The purpose of this study was to investigate the effect of mechanical shear on hydrophobicity of pharmaceutical powder blends as a function of composition and particle size, and to determine the impact on drug release from tablets. Methods: Four powder formulations were subjected to three different shear strain conditions (40 rev, 160 rev, and 640 rev) in a controlled shear environment operating at a shear rate of 80 rpm. A total of 12 blends were tested for hydrophobicity. Subsequently, sheared blends were compressed into tablets at 8 kN and 12 kN in a rotary tablet press. During tablet compression, powder samples were collected after the feed frame and their hydrophobicity was again measured. Results: Results indicated that increase in shear strain could significantly increase hydrophobicity, predominantly as an interacting function of blend composition. Blends with both colloidal silica and magnesium stearate (MgSt) were found to show higher hydrophobicity with shear than other blends. Additional shear applied by the tablet press feed frame was found to change the powder hydrophobicity only in the absence of MgSt. Conclusions: Studies showed that the drug release rates dropped with shear more for the blends with both colloidal silica and MgSt than the other blends. Furthermore, the rate of drug release dropped with a decrease in particle size of the main excipient. Surprisingly, the relationship between the relative increase in hydrophobicity and a corresponding drop in the drug release rate was not found when either MgSt or colloidal silica was mixed alone in the blends.

Near infrared spectroscopic calibration models for real time monitoring of powder density.

Near infrared spectroscopic (NIRS) calibration models for real time prediction of powder density (tap, bulk and consolidated) were developed for a pharmaceutical formulation. Powder density is a critical property in the manufacturing of solid oral dosages, related to critical quality attributes such as tablet mass, hardness and dissolution. The establishment of calibration techniques for powder density is highly desired towards the development of control strategies. Three techniques were evaluated to obtain the required variation in powder density for calibration sets: 1) different tap density levels (for a single component), 2) generating different strain levels in powders blends (and as consequence powder density), through a modified shear Couette Cell, and 3) applying normal forces during a compressibility test with a powder rheometer to a pharmaceutical blend. For each variation in powder density, near infrared spectra were acquired to develop partial least squares (PLS) calibration models. Test samples were predicted with a relative standard error of prediction of 0.38%, 7.65% and 0.93% for tap density (single component), shear and rheometer respectively. Spectra obtained in real time in a continuous manufacturing (CM) plant were compared to the spectra from the three approaches used to vary powder density. The calibration based on the application of different strain levels showed the greatest similarity with the blends produced in the CM plant.

A New Climatic Map of the Dominican Republic Based on the Thornthwaite Classification

In this paper, we present the results of a climatic analysis based on 30-year (1971-2000) averages of precipitation and air temperature monthly data from 115 air temperature and precipitation stations of the National Meteorological Office and National Hydraulic Resources Institute of the Dominican Republic. The performed analysis provides a synthesis of the climate of the Dominican Republic, consistent with its orography and the atmospheric dynamics typical for the Caribbean region. According to the analysis, 54% of the Dominican territory can be classified as dry or semi-dry, and hence quite vulnerable to extensive or intensive land use practices, especially if inappropriate, with important implications in terms of water supplies, both for human consumption and for crop irrigation. This highlights the need to adopt appropriate policies to reduce vulnerability to climate change which, according to predictions, will lead to an increase in aridity.

In line monitoring of the powder flow behavior and drug content in a Fette 3090 feed frame at different operating conditions using Near Infrared spectroscopy

HIGHLIGHTSA NIR calibration model is developed to predict low drug content in a feed frame.NIRs can be used to track when a process enters or leaves the mass steady state.Variographic analysis demonstrated that the feed frame is an excellent sampling unit.Differences in spectra baseline can affect the NIR calibration model predictions.The die disc speed does not affect wave powder behavior inside of feed frame. ABSTRACT Near infrared (NIR) spectroscopy was used to determine the drug concentration in 3% (w/w) acetaminophen blends within the complex flow regime of the tablet press feed frame just before tablet compaction. NIR spectra also provided valuable information on the powder flow behavior within the feed frame and were used to track when a process enters or leaves the steady state. A partial least squares regression calibration model was developed with powder mixtures that varied from 1.5 to 4.5% (w/w) by obtaining 135 spectra after steady state for each concentration while the feed frame and die disc operated at 30.5 revolutions per minute (rpm). The calibration model determined drug concentration in validation blends with a root mean square error of prediction and bias below 0.1% (w/w). The robustness of the NIR calibration model was evaluated by determining the effect of variation on the operating conditions (paddle wheel speed and die disc speed) on NIR predictions. This work found that the paddle wheel speed can be increased up to 30% and the die disc speed decrease 10% without affecting NIR predictions. The results demonstrated that paddle wheel speed has a significant effect on the wave powder behavior (frequency and amplitude) but does not have significant effect on the mass hold‐up within feed frame. The die disc speed does not affect wave powder behavior but affects significantly the mass hold‐up inside the feed frame. This information can be used to reduce the tablet weight variability and ensure that this critical attribute is met.

Study of near infrared chemometric models with low heterogeneity films: The role of optical sampling and spectral preprocessing on partial least squares errors

This study is focused on understanding absorption and scattering effects and their impact on the errors observed in near infrared calibration models developed using partial least squares regression able to predict the number of polypropylene film layers stacked together. The films provided a system with reduced heterogeneity to study the sources of error due to light scattering, selection of spectral preprocessing and spectral region on near infrared calibrations. Near infrared spectra were acquired using two experimental setups with the integrating sphere module of the FT-NIR spectrometer. The first setup consisted in stacking the polymer films to determine the penetration of the near infrared radiation. The second setup was a variation using a reflective surface on the top of the films in transflection mode, increasing the pathlength and therefore transmission and absorption of the material. The estimation of the penetration of radiation was performed using talc placed over the polymers films. The narrow bands of talc, related to first and second overtones of the O-H stretching mode, were used to estimate the near infrared sampling depth into polymer film layers, which ranged from 2.95 to 3.12 mm. Partial least square calibrations developed with up to 30 film layers were accurate with bias values that were not significantly different from zero at the 95% confidence level. Statistical errors were calculated for seven near infrared regions using different spectral preprocessing and the confidence interval of the bias showed that optical sampling is unbiased and there is an absence of systematic error by the near infrared method. A calibration model developed with 50 film layers presented high statistical errors and bias different from zero, indicating a sampling error due the depth of penetration of near infrared radiation. The impact of number of samples in the calibration and validation set was also evaluated. The results showed that bias was significant when the number of samples was less than 11. This finding highlights the lack of systematic error in the near infrared method, as long as the number of samples in the calibration set is representative of the variation to be modelled by a partial least squares regression and the sampling error is reduced.

Development of Near Infrared Spectroscopic Calibration Models for In-line Determination of Low Drug Concentration, Bulk Density, and Relative Specific Void Volume within a Feed Frame

Graphical abstract Figure. No Caption available. HighlightsDevelop a NIR calibration model to predict low drug concentration in a feed frame.Monitoring low drug concentration and powder density using NIR spectroscopy.Physical properties of the blends affect the predictions of the drug concentration.PCA and physical properties of the blends provides insights on model performance. Abstract This study describes the development of a near infrared (NIR) calibration model for real time determination of drug concentration, powder density, and porosity or relative specific void volume (RSVV) of 3.00%w/w acetaminophen blends within a feed frame. The NIR calibration model was developed from 1.50 to 4.50%w/w of acetaminophen, using a high variability of major excipients (from 12.92 to 81.95%w/w) which facilitates the prediction of powder density and RSVV based on near infrared calibration spectra. The model using second derivative as spectral preprocessing explained the changes related to acetaminophen concentration in the first latent variable. The second latent variable was related to changes in concentration of microcrystalline cellulose and lactose in the powder blends. NIR calibrations were also developed based on the bulk density and RSVV of the powder blends using the same design as the API model, due to the physical properties of the particles and their effects on the NIR spectra. The RSVV was predicted for the independent set blends with an RSEP(%) below 4% with a significantly low bias (0.04 cm3/g) from reference values of 1.33 to 1.58 cm3/g. The bulk density model also exhibited excellent predictions with RSEP(%) below 2.6% and significantly low bias (0.01 g/cm3) from reference values of 0.45 to 0.51 g/cm3. The excellent results obtained show the potential of near infrared spectroscopic measurements within the feed frame for a Process Analytical Technology method to control the critical properties such as tablet mass, hardness and dissolution in batch and continuous manufacturing processes.