Tablets hardness

Figure 4.11 (left). Tablet hardness found for the sequence of 120 tablets. On the suspicion that there is a dependency by stamp, the data are grouped by stamp (Fig. 4.12 left), (right). Correlation between tablet hardness and weight. For the residual.s that are obtained after correction for the tablet weight, see Fig. 4.12 right. 

Fig. 8 Effect of starch concentration and location on tablet hardness. (From Ref. 54.)...

This optimization method, which represents the mathematical techniques, is an extension of the classic method and was the first, to our knowledge, to be applied to a pharmaceutical formulation and processing problem. Fonner et al. [15] chose to apply this method to a tablet formulation and to consider two independent variables. The active ingredient, phenylpropanolamine HC1, was kept at a constant level, and the levels of disintegrant (corn starch) and lubricant (stearic acid) were selected as the independent variables, X and Xj. The dependent variables include tablet hardness, friability, volume, in vitro release rate, and urinary excretion rate in human subjects. 

A graphic technique may be obtained from the polynomial equations, as represented in Fig. 6. Figure 6a shows the contours for tablet hardness as the levels of the independent variables are changed. Figure 6b shows similar contours for the dissolution response, t50%. If the requirements on the final tablet are that hardness be 8-10 kg and t o% be 20-33 min, the feasible solution space is indicated in Fig. 6c. This has been obtained by superimposing Fig. 6a and b, and several different combinations of X and X2 will suffice. 

Fig. 6 Contour plots for the Lagrangian method (a) tablet hardness (b) dissolution (t50%) (c) feasible solution space indicated by crosshatched area. (From Ref. 15.)... 

Fig. 13 Contour plots for (a) disintegration time (b) tablet hardness (c) dissolution response (%) (d) tablet friability as a function of disintegrant level and compressional force. Dashed lines on ordinate denote limits of experimental range (—1.547 to + 1.547 eu see text for details).

B. Tablets, Hard Gelatin Capsules, Soft Gelatin Capsules, and Granules... 

Fig. 16 Effect of paracetamol granule size on tablet hardness. Curve 1 paracetamol granules with no added surfactant curve 2 paracetamol granules with 0.2% w/v sodium lauryl sulfate. (From Ref. 81.)...

J.D. Kirsch and J.K. Drennen, Nondestructive tablet hardness testing by near-infrared spectroscopy a new and robust spectral best-fit algorithm, J. Pharm. Biomed. Anal., 19(3-4), 351-362 (1999). 

K.M. Morisseau and C.T. Rhodes, Near-infrared spectroscopy as a nondestructive alternative to conventional tablet hardness testing, Pharm. Res., 14(1), 108-111 (1997). 

M. Blanco, M. Alcala, J.M. Gonzalez and E. Torras, A process analytical technology approach based on near infrared spectroscopy tablet hardness, content uniformity, and dissolution test measurements of intact tablets, J. Pharm. Sci, 95, 2137-2144 (2006). 

Determining tablet hardness usually involves the destructive diametral crushing of each individnal tablet. However, Kirsch and Drennen developed a nondestructive method based on the slope of NIR spectra for intact tablets. Tablet hardness ranged from 1 to 7kp and was predicted with errors of 0.2-0.7kp by then-calibration models. Their approach, the robustness of which was confirmed by the resnlts, was claimed to surpass PCR calibration models in many respects as a result of its being unaffected by the absorption of individual bands. 

M. Blanco, M. Alcala, Content uniformity and tablet hardness testing of intact pharmaceutical tablets by near infrared spectroscopy. A contribution to process analytical technologies. Anal. Chim. Acta, 557, 353-359 (2006). 

The influence of sorbitol in specific formulations has also been reported [41-44]. In a paracetamol formulation consisting of sorbitol, sodium lauryl sulfate, and Aerosil, it was found that an increase in sorbitol and sodium lauryl sulfate content caused a decease in tablet hardness. This... 

Once the analytical method is validated for accuracy at the laboratory scale, it can be used to obtain extensive information on process performance (blend homogeneity, granulation particle size distribution, and moisture content) under various conditions (blender speed, mixing time, drying air temperature, humidity, volume, etc.). Statistical models can then be used to relate the observable variables to other performance attributes (e.g., tablet hardness, content uniformity, and dissolution) in order to determine ranges of measured values that are predictive of acceptable performance. 

Force measurements made without displacement values are still useful in identifying the dependency of tablet hardness (and other associated characteristics) on compaction force, and also the effect of the tablet press compaction speed on tablet strength (influence of dwell time/effective... 

In Figure 4, data from a low dose wet granulation formulation produced in production on a Courtoy R100/36 is compared to the Presster tablet hardness data. The force-hardness data from the two machines was comparable. 

After scale-up into production, it was determined that an increase in moisture content would improve the formulation stability for a high dose wet granulated product. It was decided to use the Presster to predict the results that would be obtained in production when the moisture content of the final blend was increased. Blends with three moisture levels were compressed at two forces. As shown in Figure 5, as moisture content increases, tablet hardness increased. The dissolution profiles for the tablets with different moisture levels were compared and found to be within specification, indicating that raising the moisture content in the final blend should result in acceptable tablets in production. 

Tablet hardness, friability, disintegration time and dissolution at 30minutes were the response variables that were measured. Tablets manufactured at 10 and 12kN were compared, as well as their compaction profiles. Table 4 shows the results from the fractional factorial DOE and Figure 19 shows the compaction profiles from the 20 batches.

Figure 22 shows the tablet hardness profiles of the 25 mg strength. Tablet hardness slightly increased as the compression force increased and... 

Similar observations were seen for the 50 and 100 mg strengths, where the press speed had no impact on tablet hardness. The data showed that the tablet hardness profiles were similar at compression speeds ranging from... 

Bilayer compression force (kN) First-layer compression force (kN) Tablet cylindrical height (mm) Tablet hardness (N) Tablet friability (% 500 Drops)... 

Fig. 1—Potassium chloride release profiles from sustained release matrix tablets (hardness, 7.5-8 kp) 10% ( ), 15% ( ), 20% ( ) carbomer 10% ( ), 15% (o), 20% (V) methylcellulose.

This study indicates that drug release from these formulations is by a matrix-diffusion-controlled process. The release rate constant shows an inverse relationship with the concentration of carbomer only. For all the formulations, release rate constants were independent of tablet hardness. 

Fig. 3—A plot of the percentage released against the square root of time showing the effect of tablet hardness (matrix material concentration, 15%) carbomer, , 3.5-4kp , 7.5-8kp methylcellulose, A, 3.5-4kp , 7.5-8kp.

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