Optimising the use of magnesium stearate and starch in ... · Optimisation of a Paracetamol Tablet Formulation Optimising the use of magnesium stearate and starch in direct compression

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Optimisation of a Paracetamol Tablet Formulation

Optimising the use of magnesium stearate and starch in direct compression

paracetamol tablets

Contents

Abstract 2

A) Introduction 3

B) Materials and Method 4

B) (i) Materials 4

B) (ii) Method 4

B) (ii) (1) Factorial Design 4

B) (ii) (2) Paracetamol Assay 5

B) (ii) (3) Required Excipient Masses 6

B) (ii) (4) Tablet Manufacture 7

B) (ii) (5) Uniformity of Tablet Weight 7

B) (ii) (6) Tablet Friability 7

B) (ii) (7) Tablet Tensile Strength 8

B) (ii) (8) Tablet Disintegration Time 8

C) Results 9

C) (i) Chosen Dependent Variables 9

C) (i) (1) Tablet Disintegration Time 9

C) (i) (2) Tablet Tensile Strength 13

C) (ii) Overlapped Variables 16

C) (iii) Other Dependent Variables 17

C) (iii) (1) Uniformity of Tablet Weight 17

C) (iii) (2) Tablet Friability 19

D) Discussion 20

E) Conclusion 23

F) References 24

G) Appendix 25

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Optimising the use of magnesium stearate and starch in direct compression

paracetamol tablets

Abstract

An increasing number of tablets are being produced by direct compression (DC). This, coupled with an

increasing expectation of quality from patients, emphasises how optimisation of the DC tablet formulation is not

only highly relevant to modern pharmaceutics, but also necessary. The study investigated the optimisation of

properties of directly-compressed paracetamol tablets.

The effect of low, medium, and high, magnesium stearate and starch concentrations on paracetamol tablet

uniformity of weight, friability, tensile strength and disintegration time were investigated. The formulation was

optimised using a model-dependent method. Factorial design was used to create nine combinations of different

magnesium stearate and starch concentrations, and three paracetamol tablet batches of each combination were

manufactured and tested to British Pharmacopoeia standards. Contour plots were created to predict an optimum

formulation.

The optimum tablet formulation was achieved with 9.5-10.0% starch and 0.0-0.4% magnesium stearate. This

formulation gave the lowest disintegration time of 120 -240 seconds, and the highest tensile strength of 2.3-2.5

MPa. The optimum concentrations required to achieve low friability or good uniformity of weight were not

found, but provide potential for future experiments. This formulation was proven to produce directly

compressible tablets that are able to fragment and disintegrate quickly when swallowed, as well as be durable

enough to withstand transit and storage.

Keywords: Tablet Formulation, Optimisation, Direct Compression, Magnesium Stearate, Starch

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A) Introduction

Direct compression (DC) is a straightforward method of formulating tablets that allows the tedious steps of wet

or dry granulation to be bypassed. The only requirement prior to compression is the mixing of excipients and

active pharmaceutical ingredient (API), and does not require exposure to water or heat like wet granulation1. This

is especially advantageous for drugs sensitive to moisture and/or heat. Moreover, as direct compression includes

minimal stages, further advantages include less material loss; decreased machinery, energy, and labour costs;

reduced complexity; and easier validation and control of each process2.

For these reasons direct compression is a greatly desirable formulation technique, and with estimates reporting

that some pharmaceutical companies produce up to 50% of their generic formulations via direct compression3, it

is also highly relevant to modern pharmaceutics.

In order to directly compress a tablet, a good diluent, lubricant, and disintegrant is required. Each excipient has

an important role, for example, the diluent is essential for adding bulk to the formulation as well as increasing

flowability4. A lubricant is required to ensure tablets eject easily from the machine without fracturing, binding

and/or damaging the punches5, and a disintegrant is necessary to decrease disintegration time by assisting the

fragmentation of the tablet in water, and thus aiding subsequent dissolution6.

Choice of excipients and their respective concentrations are crucial to the quality of a tablet. A direct

compression excipient should be safe, chemically and physically stable, low cost, and exhibit properties such as

high compressibility, hardness and flowability.

The aim of this study was to formulate a high dose tablet containing 400 mg of paracetamol via direct

compression, and to optimise this formulation using a model-dependent method. The intended use of the tablet

would be to act as an analgesic or antipyretic, administered orally to a patient in pain or with a fever, and thus the

tablets produced should demonstrate good uniformity of weight, low friability, high tensile strength and low

disintegration time in order to be successfully manufactured for this purpose.

A good tablet must have excipients with a high enough flowability to produce tablets with uniform weight as this

is important to produce consistent tablets for quality control. It must also have low tablet friability and high

tensile strength so that it is hard and durable enough to withstand transit and storage. Moreover, it should also

have a low disintegration time to ensure that after the patient swallows the tablet, it can fragment quickly and

allow for faster dissolution of the API, and thus increase bioavailability7. Therefore, tests are to include

uniformity of tablet weight, tablet friability, tablet tensile strength and tablet disintegration time, all performed as

per British Pharmacopoeia (BP) guidelines.

To achieve this aim, the chosen excipients included coarse lactose as a diluent, maize starch as a disintegrant, and

magnesium stearate as a lubricant.

Lactose is a commonly used diluent, and was chosen for its favourable properties, such as being an excipient

suitable for direct compression, having low hygroscopicity, being chemically and physically stable, low cost, and

exhibiting good flowability8.

For the disintegrant, the superdisintegrant crospovidone was initially planned, however, this was not available in

the lab and so maize starch was used. Maize starch is one of the oldest used disintegrants and is still widely used

today7. It is stated to work via capillary action, attracting water into pores, breaking physical bonds between

particles, and thus fragmenting the tablet.

Magnesium stearate was chosen as it is an effective lubricant that is suitable for direct compression, and also due

to its additional anti-adherent and glidant properties9. It works by forming an adsorbed film around particles, a

mechanism known as boundary lubrication, which lowers shear resistance and thus reduces the friction between

the powder and the die wall10.

In order to optimise the tablet, the respective concentrations of lubricant and disintegrant, as well as tablet

powder mixing time, were possible parameters to test. It is known that lubricant concentration would affect the

tablet’s ejection fraction, as well as the powder’s flowability and thus its uniformity of weight. It was also known

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that disintegrant concentration would affect the tablet’s disintegration time, but also its compressibility if used at

too high a concentration11. Lastly, it was known that mixing time would affect the tablet powder’s flowability,

and thus its uniformity of weight, as well as tablet dissolution rate if overmixed. As mixing time affected similar

and fewer properties to lubricant concentration, literature values of mixing the powder for 2-5 minutes12 was

decided to be used, and the respective concentrations of lubricant and disintegrant were the chosen parameters to

test.

Optimum lubricant concentration is stated to be between 0.3 – 2%,13 and thus magnesium stearate concentrations

to be tested were 0.25%, 0.75% and 1.50%. Optimum starch concentration is stated to be below 10%,11 and thus

starch concentrations to be tested were 5.0%, 7.5%, and 10.0%.

B) Materials and Methods

B) (i) Materials

The manufacturer and batch numbers of all paracetamol DC, coarse lactose, maize starch, magnesium stearate,

deionised water, and pH 2 buffer used in the experiment were unavailable.

Further materials included two balances (Sartorius, 18803261) and (Sartorius, 70506805), a UV

Spectrophotometer (Varian, ELO5073080), a turbula mixer (Glen Creston, 950411), a tablet maker (Manesty,

11174), a Roche Friabilator (Sotax, SF20609278), a hardness tester (Engineering Systems, C502280427), and a

disintegration bath (Copley, 53426).

B) (ii) Method

B) (ii) (1) Factorial Design

The different combinations of the parameters to be tested were made using factorial design. See Tables 1 and 2.

Table 1: The different concentration levels of disintegrant (maize starch) and lubricant (magnesium stearate)

respectively, and their assigned letter.

Level Assigned Letter Disintegrant Concentration (%) Lubricant Concentration (%)

Low L 5.00 0.25

Medium M 7.50 0.75

High H 10.00 1.50

Table 2: Factorial design combinations of different disintegrant and lubricant concentrations, with the first letter

denoting the level of disintegrant concentration, and the second letter denoting the level of lubricant

concentration.

Disintegrant Concentration Level

Low (5.00%) Medium (7.50%) High (10.00%)

Lubricant

Concentration

Level

Low

(0.25%)

LL

(5.00%, 0.25%)

ML

(7.50%, 0.25%)

HL

(10.00%, 0.25%)

Medium (0.75%) LM

(5.00%, 0.75%)

MM

(7.50%, 0.75%)

HM

(10.00%, 0.75%)

High

(1.50%)

LH

(5.00%, 1.50%)

MH

(7.50%, 1.50%)

HH

(10.00%, 1.50%)

Three batches of each combination were to be made, with 100 tablets per a batch.

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B) (ii) (2) Paracetamol Assay

In order to determine the percentage of paracetamol in paracetamol DC, an assay was performed. The specific

absorbance of paracetamol was 715,14 and thus a suitable range of concentrations of paracetamol DC was needed.

See Calculation 1.

Calculation 1: The maximum paracetamol concentration that can be used in UV Spectroscopy.

Suitable paracetamol BP concentrations below 1.39x10-3 % selected to be used were: 2x10-4 %, 4x10-4 %, 6x10-

4 %, 8x10-4 %, and 1x10-3 %.

First, a paracetamol BP stock solution was to be made. 0.1g of paracetamol BP was weighed using a balance

(Sartorius, 18803261) and dissolved in 100mL of pH 2 buffer to give a 100mg/100mL solution. 10mL of this was

transferred into a 100mL volumetric flask, and pH 2 buffer added to make 100mL, giving a 10mg/100mL

solution. 10mL of this solution was then transferred into another 100mL volumetric flask, and pH 2 buffer added

to make 100mL, giving a 1mg/100mL solution. The final solution of 1mg/100mL (10mg/L) was the stock

solution. Further dilutions were made according to Table 3 in mg/L.

Table 3: Volumes of paracetamol BP stock solution (10mg/L) and pH 2 buffer required for certain paracetamol

concentrations.

Concentration (mg/L) Stock Solution (mL) Buffer (mL)

2 2 8

4 4 6

6 6 4

8 8 2

The absorbance values of each concentration were measured using a ultraviolet-visible spectrophotometer

(Varian, ELO5073080) at 257nm14, and a calibration curve created (See ‘Section G) Appendix’).

The above method under ‘B) (ii) (1) Paracetamol Assay’ was also repeated using paracetamol DC instead of

paracetamol BP, and the absorbance values recorded separately.

Using the line equation of each calibration curve, the percentage of paracetamol in paracetamol DC was

calculated. See Calculation 2.

1) Paracetamol Specific Absorbance, A(1%, 1 cm) = 715

2) The maximum absorbance value the UV spectrophotometer could read was 1. Therefore, the

maximum concentration of paracetamol that could be used would give an absorbance value of 1, and

was calculated by dividing 1% by 715.

3) Absorbance value of 715 = 1% paracetamol BP (Divide both by 715)

Therefore, Absorbance value of 1 = 1.39x10-3 % paracetamol BP

4) 1.39x10-3 % was the maximum concentration of paracetamol that could be used to perform an assay

via UV spectroscopy.

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Calculation 2: The percentage of paracetamol in paracetamol DC.

1) Paracetamol BP Calibration Curve Equation: y = 0.048x –0.018

Where y is absorbance value, and x is paracetamol BP concentration (mg/L)

R2 = 0.9998

2) Absorbance value of 8mg/L paracetamol DC substituted (0.340)

y = 0.048x –0.018

0.340 = 0.048x –0.018

x = 7.46 mg/L

2) Absorbance value of 8mg/L paracetamol BP substituted (0.371)

y = 0.048x –0.018

0.371 = 0.048x –0.018

x = 8.11 mg/L

3) 7.46 mg/L x 100 = 92.0% (1 d.p.)

8.11 mg/L

4) Therefore, paracetamol DC contained 92.0% paracetamol.

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B) (ii) (3) Required Excipient Masses

In order to manufacture the tablets, the mass of API required for each tablet was calculated. See Calculation 3.

Calculation 3: The mass of API required per a tablet.

The mass of each excipient required for each combination was then calculated. See Calculation 4.

Calculation 4: An example of the mass of disintegrant, lubricant, and diluent required for an LL tablet (5%

starch, 0.25% magnesium stearate).

The weights required for each tablet component were multiplied by 100 in order to give enough to manufacture

100 tablets of each batch.

1) In 100 mg of paracetamol DC, there was 92 mg paracetamol.

2) 400 mg of paracetamol was the paracetamol mass required, and thus 92 mg required upscaling.

400 mg = 4.3478 (4 d.p)

92 mg

3) 4.3478 was the factor by which 100 mg of paracetamol DC had to be multiplied by.

100 mg x 4.3478 = 434.78 mg

4) Therefore, 434.78 mg of paracetamol DC was required to give 400 mg of paracetamol.

5) A suitable total tablet weight was 500 mg as it was adequately above this value.

1) Starch Concentration 5%

Weight required = (0.05 x 500 mg)

= 25 mg

2) Magnesium Stearate Concentration 0.25%

Weight required = (0.0025 x 500 mg)

= 1.25 mg

3) Weight of API required = 434.78 mg paracetamol DC

4) Weight of diluent required = 500 – (API +excipients)

= 500 – (434.78 + 25 + 1.25)

= 38.97 mg of lactose

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B) (ii) (4) Tablet Manufacture

The required weights of each excipient and of paracetamol DC were weighed out. The paracetamol DC, starch,

and lactose were transferred into a plastic bottle and mixed in a turbula mixer (Glen Creston, 950411) for four

minutes. The bottle was removed and magnesium stearate added. The bottle was placed in the turbula mixer

again and mixed for two minutes. Once complete, the contents of the bottle was placed in a bag and labelled with

the appropriate batch number. This process was repeated three times for each combination, giving a total of 27

bags. A calibration batch with the MM combination was also made, this contained enough excipients and API

weighed out for 500 tablets.

The bags containing all the combinations and the calibration batch were given to a technician and the tablets

were produced using a tablet machine (Manesty, 11174).

B) (ii) (5) Uniformity of Tablet Weight

Twenty tablets from each batch were randomly selected and weighed using a balance (Sartorius, 70506805). The

average weight was calculated. If no more than two tablets deviated from the average weight by ±5%, and none

deviated by ±10%, the batch passed the BP test.

B) (ii) (6) Tablet Friability

Twenty tablets were randomly selected, de-dusted, and weighed using a dusting brush and a balance (Sartorius,

70506805). The tablets were placed in a Roche Friabilator (Sotax, SF20609278) and rotated 100 times over four

minutes. Tablets were de-dusted and reweighed. Friability was then calculated. (See Calculation 5).

If the tablet batch had <1% friability, the batch passed BP specifications. If the batch had >1% friability, the

experiment should have been repeated twice and an average used, however, due to time constraints this wasn’t

possible.

Calculation 5: Tablet Friability

B) (ii) (7) Tablet Tensile Strength

Ten tablets from each batch were randomly selected. Each tablet was placed in a hardness tester (Engineering

Systems, C502280427) and the hardness measured. Using a ruler, the tablet’s diameter and width was also

measured. Tablet tensile strength was then calculated. See Calculation 6.

1) Tablet Friability (F) = W0 –W x 100

W0

Where W0 is original tablet weight (mg), and W is tablet weight after tumbling (mg)

2) For example, LL Batch 1 had an original weight of 11.39g and a weight after tumbling of 11.25g,

substituting these values gave a friability of:

3) F = (11.39-11.25)/11.39

= 1.21%

4) Therefore, LL Batch 1 failed BP specifications due to having a friability >1%.

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Calculation 6: Tablet Tensile Strength

B) (ii) (8) Tablet Disintegration Time

A disintegration bath (Copley, 53426) had each beaker filled with 800 mL of deionised water. The disintegration

bath was then allowed to heat to 37ºC. Six tablets were taken randomly and placed individually in the basket rack

tubes. Each tablet had a disc placed over it. The tubes were vertically raised and lowered 50-60 mm, 28-32 times

a minute. The time taken for all tablets in a batch to fully disintegrate was recorded. If all six tablets in a batch

disintegrated in less than fifteen minutes, the batch passed BP specifications. If any tablet had not disintegrated in

less than fifteen minutes the batch failed.

1) Tablet Tensile Strength (σ) = 2P / πDH

Where σ is tablet tensile strength (N/m2), P is tablet hardness (N), D is diameter (m), and H is tablet

thickness (m).

2) For example, a tablet from LL Batch 1 had a tablet hardness of 16.49 kg, a diameter of

0.012m, and a thickness of 0.004m.

3) 1 kg = 9.807 N

Therefore 16.49 kg = 16.49 x 9.807 N

= 161.72 N (2 d.p.)

4) Substituting these values gave a tensile strength of:

3) σ = 2P

πDH

= 2 x 161.72 __

0.004 x 0.012π

= 2144878.11 N/m2

= 2144878.11/1 000 000 MPa

= 2.14 MPa (2 d.p.)

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C) Results

C) (i) Chosen Dependent Variables

The two most relevant tests selected to discuss in detail were disintegration time and tensile strength. Please see

Figures 10-13 for friability and uniformity of weight results if of interest.

C) (i) (1) Disintegration Time

For each tablet combination, three batches were made. Therefore, the disintegration time measurement taken for

each tablet combination was triplicated and a mean taken, increasing data reliability. Moreover, the standard

deviations between the triplicated results were very low, suggesting that the disintegration time results had little

variation from the mean, and thus were reliable and precise.

Figure 1 shows the relationship between disintegration time and starch concentration. A negative correlation was

observed, with disintegration time decreasing as starch concentration increased. The disintegration time of tablets

with all tested concentrations of magnesium stearate decreased with increasing starch concentration. The lowest

disintegration time was achieved with 10% starch and 0.25% magnesium stearate. Tablets with 0.25%

magnesium stearate gave the overall lowest disintegration times.

The correlation coefficients for the 0.25%, 0.75%, and 1.50% magnesium stearate tablet formulations were -0.91,

-0.93, and -0.97 respectively. The closer to -1 a correlation coefficient the stronger the negative linear

correlation, therefore suggesting that for all three different magnesium stearate concentration formulations, there

was a very strong negative linear correlation between disintegration time and starch concentration. Furthermore,

the strength of the negative linear correlation between disintegration time and starch concentration seemed to

increase with increasing magnesium stearate concentration.

Using 10.0% starch in the 0.25%, 0.75%, and 1.50% magnesium stearate tablet formulations gave respective

44.9%, 46.9%, and 51.7% decreases in mean disintegration time from using 5.0% starch. The decrease in

disintegration time by using 10.0% starch rather than 5.0% was most profound with tablets containing 1.50%

magnesium stearate.

Figure 1: The mean disintegration times (s) of tablet formulations with 0.25%, 0.75%, and 1.50% magnesium stearate

concentrations respectively, shown as a function of starch concentration (%). Each point represents the mean of n =

3 measured values. Error bars represent one standard deviation from the mean. Note y axis begins at 200 seconds,

and x axis begins at 3% starch for graph clarity. A line of best fit, y = mx + c, was fitted to the data of each

magnesium stearate concentration, where y is the disintegration time (s), m is the gradient of the line, x is starch

concentration (%), and c is the extrapolated y intercept.

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It can be suggested that increasing starch concentration has a greater effect in decreasing disintegration time in

tablets with higher magnesium stearate concentrations. This is also seen when comparing the magnitudes of the

gradients of the lines of best fit for the 0.25%, 0.75%, and 1.50% magnesium stearate tablet formulations, which

were -38.2, -43.2, and -54.2 respectively. This shows that increasing starch concentration in the tablets with

1.50% magnesium stearate, decreased disintegration time 1.4 times more than increasing starch concentration in

tablets with 0.25% magnesium stearate.

The coefficients of determination (R2 values) for the lines of best fit for the 0.25%, 0.75%, and 1.50%

magnesium stearate tablet formulations were 0.84, 0.87, and 0.94 respectively. The R2 value shows the

percentage of variation in disintegration time data that is attributable to the linear relationship with starch

concentration. The closer an R2 value to 1, the better the line represents the data. For all magnesium stearate

concentration formulations, at least 84% of the data was explained, suggesting that the lines of best fit

represented the data well, and that the models were reliable. The most reliable model was for tablets with 1.50%

magnesium stearate, having 94% of the disintegration time data variation explained due to starch concentration.

Figure 2 shows the relationship between disintegration time and magnesium stearate concentration. A positive

correlation was observed, with disintegration time increasing as magnesium stearate concentration increased. The

disintegration time of tablets with all tested starch concentrations increased with increasing magnesium stearate

concentration. The lowest disintegration time was achieved with 0.25% magnesium stearate and 10.0% starch.

Tablets with 10.0% starch gave the overall lowest disintegration times. Tablets with 5% starch gave significantly

higher disintegration times than with 7.5% or 10.0% starch. These findings are in concordance with the findings

from Figure 1.

The correlation coefficients for the 5.0%, 7.5%, and 10.0% starch tablet formulations were 0.99, 1.00, and 0.91

respectively. Therefore, it is suggested that for all different starch concentration formulations, there was a very

strong positive linear correlation between disintegration time and starch concentration.

Figure 2: The mean disintegration times (s) of tablet formulations with 5.0%, 7.5%, and 10.0% starch concentrations

respectively, shown as a function of magnesium stearate concentration (%). Each point represents the mean of n = 3

measured values. Error bars represent one standard deviation from the mean. Note y axis begins at 200 seconds for

graph clarity. A line of best fit, y = mx + c, was fitted to the data of each starch concentration, where y is the

disintegration time (s), m is the gradient of the line, x is magnesium stearate concentration (%), and c is the

extrapolated y intercept.

Using 1.50% magnesium stearate in the 5.0%, 7.5%, and 10.0% starch tablet formulations gave respective

27.8%, 25.9%, and 12.0% increases in mean disintegration time from using 0.25% magnesium stearate. The

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increase in disintegration time by using 1.50% magnesium stearate rather than 0.25% was most profound with

tablets containing 5.0% starch, and was lowest with tablets containing 10.0% starch. This suggests that when

higher concentrations of starch are used, the effect magnesium stearate has on increasing disintegration time is

lowered. This can also be seen by the magnitudes of the gradients of the lines of best fit for each starch

concentration, which were 96.42, 55.90, and 22.00 respectively. This shows that increasing magnesium stearate

concentration in the tablets with 10.0% starch, increased disintegration time 4.4 times less than increasing

magnesium stearate concentration in tablets with 5.0% starch.

The coefficients of determination for the lines of best fit for the 5.0%, 7.5%, and 10.0% starch tablet

formulations were 0.99, 1.00, and 0.82 respectively. For all starch concentration formulations, at least 82% of the

data was attributable to the linear relationship with magnesium stearate concentration, suggesting that the lines of

best fit represented the data well, and that the models were reliable. The most reliable model was for tablets with

7.5% starch, having 100% of the disintegration time data variation explained due to magnesium stearate

concentration.

Regression analysis was performed on the disintegration time results and a predicted vs measured graph was

plotted, -see Figure 3. The regression equation was y= 573.0 (±117.9) – 35.7x[1] (±15.2) + 169.7x[2] (±120.4) –

14.9x[1]x[2] (±15.5), where y is the disintegration time value, x[1] is the starch concentration with 42.6% error,

and x[2] is the magnesium stearate concentration with 70.9% error.

The coefficient of determination was 0.89, suggesting that the line of best fit represented the data well, and that

the model was reliable with 89% of the data attributable to the linear relationship between disintegration time and

both magnesium stearate and starch concentration. However, there was a large amount of error with starch and

magnesium stearate concentration, reducing the reliability of this model.

Examining the coefficient magnitudes, it was observed that magnesium stearate concentration had a higher

coefficient than starch concentration, suggesting it has a larger effect on disintegration time than starch. It can be

concluded from the equation that increasing magnesium stearate concentration in a tablet increases disintegration

time to a greater extent than increasing starch concentration decreases disintegration time.

Figure 3: The predicted vs measured values of mean disintegration times (s) of all tablet combinations.

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A contour plot was also created (see Figure 4), and the optimum concentrations to be used were shown to be

approximately 9.5-10.0% starch, with approximately 0.0-1.1% magnesium stearate, in order to achieve the

lowest possible disintegration time of 120 -240 seconds (without predicting outside the tested data range).

Figure 4: The relationship between various levels of magnesium stearate concentration (%) and starch concentration

(%), with disintegration time (s). Lighter coloured bands represent a lower disintegration time.

C) (i) (2) Tensile Strength

For each tablet combination, three batches were made. Therefore, the tensile strength measurement for each

tablet combination was triplicated and a mean taken, increasing data reliability. Moreover, the standard

deviations between the triplicated results for 0.25% and 0.75% magnesium stearate were reasonably low,

suggesting that the tensile strength results for these tablets had little variation from the mean, and thus were

reliable and precise. The tensile strength results for tablets with 1.50% magnesium stearate had the largest

standard deviations and thus the greatest data variability and spread from the mean, and were thus the least

reliable.

Figure 5 shows the relationship between tablet tensile strength and starch concentration. The correlation

coefficients for the 0.25%, 0.75%, and 1.50% magnesium stearate tablet formulations were -0.50, -0.01, and 0.01

respectively. No correlation was observed between tensile strength and starch concentration, except for tablets

containing 0.25% magnesium stearate, which showed a weak negative linear correlation. These were not

expected results, see ‘Section D’ for discussion.

The coefficients of determination for the 0.25%, 0.75%, and 1.50% magnesium stearate tablet formulations were

0.25, 0.01, and 0.01 respectively. For tablets with 0.75% and 1.50% magnesium stearate concentration, 99.0% of

the data was not attributable to a linear relationship between tensile strength and starch concentration, suggesting

that the lines of best fit represented the data very poorly, and that the models weren’t reliable. The most reliable

model was for tablets with 0.25% magnesium stearate, having 25% of the tensile strength data variation

explained due to starch concentration.

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Figure 5: The mean tensile strengths (MPa) of tablet formulations with 0.25%, 0.75%, and 1.50% magnesium stearate


3 measured values. Error bars represent one standard deviation from the mean. Note y axis begins at 1.4 MPa, and x

axis begins at 3% starch for graph clarity. A line of best fit, y = mx + c, was fitted to the data of each magnesium

stearate concentration, where y is the tensile strength (MPa), m is the gradient of the line, x is starch concentration

(%), and c is the extrapolated y intercept.

Figure 6 shows the relationship between tensile strength and magnesium stearate concentration. A negative

correlation was observed, with tensile strength decreasing as magnesium stearate concentration increased. The

correlation coefficients for the 5.0%, 7.5%, and 10.0% starch tablet formulations were 0.83, 1.0, and 0.86

respectively. Therefore, it is suggested that for all different starch concentration formulations, there was a very

strong negative linear correlation between tensile strength and starch concentration.

The standard deviations between the triplicated results for 0.25%, 0.75% and 1.50% magnesium stearate were

quite high, suggesting that the tensile strength results had a large amount of variation from the mean, and thus

were not very reliable. Furthermore, the error bars (as seen in Figure 6) had a lot of overlap, suggesting that the

difference between the means of each starch concentration was not statistically significant and was likely due to

natural variation. This is in concordance with the findings from Figure 5 where no correlation was observed

between starch concentration and tensile strength.

The coefficients of determination for the 5.0%, 7.5%, and 10.0% starch tablet formulations were 0.70, 1.00, and

0.74 respectively. For all starch concentration formulations, at least 70% of the tensile strength data variation was

attributable to the linear relationship with magnesium stearate concentration, suggesting that the lines of best fit

represented the data well, and that the models were reliable. The most reliable model was for tablets with 7.5%

starch, having 100% of the tensile strength data variation explained due to magnesium stearate concentration.

Page 15 of 25


Figure 6: The mean tensile strengths (MPa) of tablet formulations with 5.0%, 7.5%, and 10.0% starch concentrations


measured values. Error bars represent one standard deviation from the mean. Note y axis begins at 1.4 MPa for

graph clarity. A line of best fit, y = mx + c, was fitted to the data of each starch concentration, where y is the tensile

strength (MPa), m is the gradient of the line, x is magnesium stearate concentration (%), and c is the extrapolated y

intercept.

Regression analysis was performed on the tensile strength results and a predicted vs measured graph was plotted,

-see Figure 7. The regression equation was y= 2.2 (±0.3) – 0.0x[1] (±0.0) – 0.3x[2] (±0.3) – 0.0x[1]x[2] (±0.0),

where y is the tensile strength, x[1] is the starch concentration with 0.0% error, and x[2] is the magnesium

stearate concentration with 100.0% error.

The coefficient of determination was 0.75, suggesting that the line of best fit represented the data well, and that

the model was reliable with 75% of the data variation attributable to the linear relationship between tensile

strength and magnesium stearate and starch concentration. However, there was a large amount of error with

magnesium stearate concentration, reducing the reliability of this model greatly.

Examining the coefficient magnitudes, it was observed that magnesium stearate concentration had a higher

coefficient than starch concentration, suggesting it has a larger effect on tensile strength. This supports Figure 4,

where it appeared tensile strength was not correlated with starch concentration. These were not expected results,

see ‘Section D’ for discussion.

Figure 7: The predicted vs measured values of mean disintegration times (s) of all tablet combinations.

Page 16 of 25


A contour plot was also created (see Figure 8), and the optimum concentrations to be used were shown to be

approximately 0.0-10.0% starch, with approximately 0.0-0.4% magnesium stearate, in order to achieve the

highest possible tensile strength of 2.3-2.5 MPa.


(%), with tablet tensile strength (MPa). Darker coloured bands represent a higher tensile strength.

C) (ii) Overlapped Variables

The contour plots for disintegration time and tensile strength (Figures 4 and 8), were overlapped in order to find

the optimum concentration ranges of magnesium stearate and starch. The area which overlapped to give the

shortest disintegration time and highest tensile strength was with approximately 9.5-10.0% starch, with

approximately 0.0-0.4% magnesium stearate.


(%) with tablet disintegration time (s), overlapped with the relationship between various levels of magnesium stearate

concentration (%) and starch concentration (%) with tablet tensile strength (MPa).

Page 17 of 25


C) (iii) Other Dependent Variables

The aim of the study was to investigate two variables in detail and this has been achieved using disintegration

time and tensile strength. The lines of best fit for both disintegration time and tensile strength results had high R2

values, suggesting they were good, reliable models which represented the data well. Whereas, when lines of best

fit were applied to the results for friability and uniformity of weight, low R2 values were produced. To use the

data from the friability and uniformity of weight tests would have meant observing trends from less reliable

models, and making less reliable predictions, than with the experiments that had higher R2 values.

Furthermore, many of the error bars in Figures 10, 11, 12, and 13 overlapped, suggesting that the means were not

statistically significant, reinforcing the fact that making observations from these graphs would not have been

reliable.

Moreover, both disintegration time and uniformity of weight are good indicators of tablet uniformity and thus

analysing both in detail would have been less beneficial than analysing two tests that showed different tablet

properties. This was the same for tensile strength and tablet friability, both of which are linked and are an

indicator of a tablet’s durability.

However, despite this link between tablet properties, this was not observed with the results. For instance, Figures

1 and 2 did not match Figure 10 and 11. It would have been expected that the small error bars observed in

Figures 1 and 2 would suggest that all tablets produced for each combination were uniform as they produced a

similar disintegration time, and thus the standard deviations between the calculated coefficients of variation for

each batch should have also been low. However, this was not the case. It would also have been expected for

tablet friability to be higher in tablets with low tensile strength, but there was no similarity between Figure 5 and

12, or between Figure 6 and 13. This will be discussed in Section D.

C) (iii) (1) Uniformity of Weight

Table 4: Summary of which tablet combinations passed or failed BP specifications for uniformity of weight

Combination Batch Status

Batch 1 Batch 2 Batch 3

LL PASS PASS PASS

LM PASS FAIL FAIL

LH PASS PASS PASS

ML PASS FAIL FAIL

MM PASS FAIL PASS

MH FAIL PASS PASS

HL PASS PASS PASS

HM PASS PASS PASS

HH FAIL PASS PASS

Page 18 of 25


Figure 10: The mean coefficient of variation (%) of the weight measurements for tablet formulations with 0.25%,

0.75%, and 1.50% magnesium stearate concentrations respectively, shown as a function of starch concentration (%).

Each point represents the mean of n = 3 calculated values. Error bars represent one standard deviation from the

mean. Note x axis begins at 3% starch for graph clarity. A line of best fit, y = mx + c, was fitted to the data of each

magnesium stearate concentration, where y is the coefficient of variation of tablet weights (%), m is the gradient of

the line, x is starch concentration (%), and c is the extrapolated y intercept.

Figure 11: The mean coefficient of variation (%) of tablet formulations with 5.0%, 7.5%, and 10.0% starch

concentrations respectively, shown as a function of magnesium stearate concentration (%). Each point represents the

mean of n = 3 calculated values. Error bars represent one standard deviation from the mean. A line of best fit, y = mx

+ c, was fitted to the data of each starch concentration, where y is the coefficient of variation of tablet weights (%), m

is the gradient of the line, x is starch concentration (%), and c is the extrapolated y intercept.

Page 19 of 25


C) (iii) (2) Tablet Friability

Figure 12: The mean tablet friability (%) of tablet formulations with 0.25%, 0.75%, and 1.50% magnesium stearate


3 measured values. Error bars represent one standard deviation from the mean. Note y axis begins at 1.0%, and x axis

begins at 3% starch for graph clarity. A line of best fit, y = mx + c, was fitted to the data of each magnesium stearate

concentration, where y is tablet friability (%), m is the gradient of the line, x is starch concentration (%), and c is the

extrapolated y intercept.

Figure 13: The mean tablet friability (%) of tablet formulations with 5.0%, 7.5%, and 10.0% starch concentrations


measured values. Error bars represent one standard deviation from the mean. Note y axis begins at 1.0% for graph

clarity. A line of best fit, y = mx + c, was fitted to the data of each starch concentration, where y is the tablet friability

(%), m is the gradient of the line, x is magnesium stearate concentration (%), and c is the extrapolated y intercept.

Page 20 of 25


D) Discussion

Optimisation carries many advantages in oppose to random ‘hit and miss’ experimentation. For example, the

direction of product development is driven by scientific and mathematical reasoning, and thus leads to reduced

costs, time and staff. However, higher skilled staff are required and high quality data is essential for valid

predictions16. Two common optimisation methods are ‘model-dependent’, where experiments are planned

beforehand by factorial design, and ‘model-independent’, where each experiment is planned after another, being

influenced by previous results. The tablets produced were optimised via a model-dependent method.

Model-dependent optimisation is advantageous against model-independent optimisation for many reasons. For

instance, it’s easy to identify a maximum and minimum from a model-dependent contour plot, whereas with the

model-independent method, the minimum/maximum achieved may not necessarily be the global optimum.

Furthermore, knowing how many experiments are required from the start allows for appropriate budgeting/staff

management, whereas the model-independent method has no definitive end point. Moreover, the model-

dependent method acquires a large quantity of data from which a compromise between all variables can be made,

- this is not possible with the model-independent method. However, disadvantages to the model-dependent

method include that only two independent variables can be tested at one time, and that due to requiring many

experiments, it can sometimes take longer to achieve an optimum than the model-independent method.

For the disintegration testing, a basket rack assembly was used and the method was to record the time it took for

the last tablet in a batch to disintegrate. This method is simple and in accordance with BP standards, and thus

easily comparable to other disintegration experiments. However, the experiment’s performance is highly

susceptible to the volumes of the immersion fluid17 used in each beaker, and results can be distorted if BP

specifications are not adhered to strictly. Furthermore, by only measuring the last tablet’s disintegration time, a

misleading result could be given if it was significantly longer than the rest of the batch. A potential improvement

to the disintegration time experiment would be to measure the disintegration time of each tablet in a batch and

take the mean. Though it may be impractical to observe 36 tablets at a time, each batch could be tested

individually if staff and time were available. This would produce a disintegration time more representative of the

whole batch. Lastly, disintegration time is a good indicator of tablet uniformity, but it is not a measure of drug

bioavailability11. To predict the potential bioavailability achieved with a tablet formulation, several other tests,

including dissolution testing, would be required.

From the experiment, it was observed that increasing starch concentration, decreased disintegration time. These

were expected results. Starch is a commonly used disintegrant and is known to lower tablet disintegration time by

a variety of mechanisms. Firstly, starch is suggested to decrease disintegration time by capillary action7. A

mechanism by which it attracts water into pores, breaks physical bonds between particles, and thus fragments the

tablet. A second mechanism that starch is also suggested to work via, is swelling. Starch is a very hygroscopic

substance, and thus easily absorbs moisture8. It is suggested that starch’s hygroscopic nature causes it to swell

when in water, forcing the tablet apart7.

It was also observed that the effect increasing starch concentration had on decreasing disintegration time was

enhanced by increasing magnesium stearate. This was an unexpected result as magnesium stearate is known to

interact with starch, forming a hydrophobic film around it and increasing disintegration time18. Therefore it

would be expected that as magnesium stearate concentration increased, the effect increasing starch concentration

had on disintegration time would be decreased. However, the use of discs in the basket rack apparatus has been

shown to be able to mask the effect of magnesium stearate on starch’s disintegration time lowering ability, and

thus could have been responsible for why the opposite effect was observed19.

Figure 1 had small error bars and a high R2 value (See ‘Section C’ for details), and thus the above conclusions

are based on trends from reliably modelled disintegration time data.

Furthermore, as seen in Figure 2, it was observed that increasing magnesium stearate concentration, increased

disintegration time. This was an expected result. Magnesium stearate is hydrophobic, and works as a lubricant

via a mechanism known as boundary lubrication. It forms an adsorbed film around particles, which lowers shear

resistance and thus reduces the friction between particles and the tablet machine’s die wall10. However, due to

this same mechanism, when mixed with starch, magnesium stearate forms a film around the starch particles,

Page 21 of 25


positioning its hydrocarbon chain perpendicularly outwards5, thus preventing water access. As a result,

increasing magnesium stearate concentration increases the formation of this film, consequently increasing

disintegration time.

It was also observed that the effect of increasing magnesium stearate concentration on increasing disintegration

time was reduced by increasing starch concentration. This was an expected result, as using higher starch

concentrations can overcome the magnesium stearate-starch interaction. Though, a further improvement for

future experiments could be to add the surfactant sodium lauryl sulphate to the formulation, which can also be

used to overcome the effect of magnesium stearate on disintegration time by increasing wetting7.

Figure 2 had small error bars and a high R2 value (See ‘Section C’ for details), and thus the above conclusions

are based on trends from reliably modelled disintegration time data.

For the tablet strength tests, the method had several advantages and disadvantages. Firstly, tensile strength was

used in opposed to tablet hardness alone. This is advantageous as calculating tensile strength takes into account

tablet diameter and thickness, as well as hardness. However, a disadvantage is that the calculation is only suitable

for cylindrical tablets, and therefore if the tablet was chipped/uneven, the formula would not represent the

tablet’s tensile strength correctly. An automated electronic hardness tester was used to measure tablet hardness,

this was advantageous as it reduced operator variability in comparison to hand operated hardness testers. Though,

the C50 model used in the experiment is an old and no longer manufactured version, and an enhancement for

future experiments could be to use the new, improved C53 model which has replaced it20.

From the experiment, it was observed that increasing starch concentration had no effect on tensile strength. This

was not the expected result. However, the low R2 value in Figure 5 suggests that conclusions drawn from the

model would be unreliable, as it does not represent the data well. The most reliable model was for tablets with

0.25% magnesium stearate, which had 25% of its tensile strength data variation attributable to a linear

relationship between tensile strength and starch concentration. The data from these tablets presented that

increasing starch concentration decreased tensile strength. This was an expected result. It is known that

increasing starch concentration increases water absorption due to starch’s hygroscopicity. The absorbed water

affects the viscoelasticity of starch particles, as well as forming a film that disrupts starch particle bonds21. As a

result, the tablet’s compressibility is significantly lowered, leading to weaker tablets.

Why the tablets with 0.75% and 1.50% were not weakened by increasing starch concentration is unknown.

Though, a possible reason for this, could be that these tablets had sufficient lubricant to form a hydrophobic film

around starch particles, preventing moisture absorption from weakening the tablet22. Or, it is also possible that

the starch concentration range used in the experiment was not adequate to see an effect on tensile strength.

Further research shows that starch can be used as a disintegrant in concentrations from 3-25%,8 and it could be

that extending the range, for example using 5%, 10%, and 15%, is needed to see a more dramatic effect on tensile

strength.

From Figure 6, it was also observed that increasing magnesium stearate concentration, decreased tensile strength.

This was an expected result as magnesium stearate’s film forming properties interrupt inter-particle bonds.

Magnesium stearate replaces the stronger host particle bonds with weaker lubricant-lubricant bonds23, and as a

consequence weakens the tablets, reducing tablet tensile strength.

Figure 6 also suggested that increasing starch concentration had no influence on the degree of the effect that

increasing magnesium stearate concentration had on decreasing tablet tensile strength. This was not an expected

result. It was expected that increasing starch concentration would increase magnesium stearate’s effect on

reducing tensile strength. This is due to starch having glidant properties at concentrations between 3-10%,8 thus

increasing powder flow, and it is stated that powders with better flow are more susceptible to being coated by

magnesium stearate21. Therefore, increasing starch concentration should increase flow, increase magnesium

stearate coating, and thus increase magnesium stearate’s ability to lower tensile strength. Though, this was not

observed. A possible reason for this is that the mixing time between the lubricant and the other tablet excipients

was limited to only 2 minutes in order to reduce magnesium stearate coating starch particles, and it seems this

may have been achieved in this respect.

Page 22 of 25


Overall, from overlapping the contour plots, it was suggested that a tablet with approximately 9.5-10.0% starch

and 0.0-0.4% magnesium stearate would give optimum tensile strength and disintegration time. The contour plots

that were overlapped were Figure 4 and Figure 8. Both contour plots were the result of multiple linear regression

analysis, both with linear regression equations that produced respective high coefficients of determination.

Therefore, it is suggested that both models were reliable and fitted the data well, and thus, subsequent predictions

were also reliable.

However, though the coefficient of determination (R2 value) was used as a measure of how reliable a model was

at representing the data, how much the data variation in the dependent variable was attributable to a linear

relationship with the independent variable, it has its limitations. For example, a high R2 value does not confirm

that an independent variable caused the change in the dependent variable, but only that a relationship exists.

Correlation is not necessarily causation and this is a fact to be wary of when interpreting results. Furthermore,

outliers can distort R2 values, and thus for future experiments, an improvement would be to perform a full

residual analysis, and remove outliers24.

In addition to this, the HL combination (10.0% starch, 0.25% magnesium stearate) used in the experiments was

within the range of the optimum formulation range from the contour plots (approximately 9.5-10.0% starch with

0.0-0.4% magnesium stearate). From Table 4, it is presented that all batches from the HL combination passed the

BP uniformity of weight test. Therefore, it can be assumed that tablets made with the optimum combination

suggested from the contour plots would also pass BP weight uniformity specifications, adding to the good

properties of the combination.

Tensile strength and tablet friability are linked and are an indicator of a tablet’s durability. However, despite this

link between tablet properties, this was not observed with the results. It would have been expected for tablet

friability to be higher in tablets with low tensile strength as both are affected by inter-particle bond strength23.

Therefore, increasing magnesium stearate concentration should have increased tablet friability the same way it

lowered tablet tensile strength, - due to the lubricant preventing the interlocking of particles. Increasing starch

concentration should also have increased friability the same way it lowered tensile strength, by absorbing water

and disrupting starch particle bonds.21

It was also expected that the coefficient of variation of tablet weight would decrease with increasing magnesium

stearate concentration, however this was not presented in the results. Increasing magnesium stearate

concentration should have decreased the coefficient of variation of the tablet weight due to its anti-adherent and

glidant properties9. Magnesium stearate forms a film around particles, reducing cohesion, and increasing flow

from the tablet machine hopper into the feed die, and therefore should have resulted in a more consistent weight9.

Starch concentrations between 3-10% are also known to have glidant properties8, and thus also should have

decreased the coefficient of variation of tablet weight and shown an increase in tablet uniformity of weight.

The reasons for the unusual friability and tensile strength results are unknown. However, it could have been due

to temporary confusion in the batch labelling system, for example believing LH meant low magnesium stearate,

and high starch for some bags, rather than its actual meaning of low starch, high magnesium stearate. However, it

is just a theoretical explanation of possible human error involved in these results. The friability and tensile

strength experiments should have been repeated to confirm/disprove this. However, due to strict time constraints

this was not possible.

Page 23 of 25


E) Conclusion

The aim of the study was to formulate a high dose tablet containing 400 mg of paracetamol via direct

compression, and to optimise this formulation using a model-dependent method. This aim was achieved

successfully, and 27 batches of 400 mg paracetamol containing tablets were produced, and underwent several

tests in order to optimise the formulation.

It was found that increasing magnesium stearate concentration, decreased tablet tensile strength and increased

tablet disintegration time. It was also found that increasing starch concentration, decreased tablet tensile strength

and decreased disintegration time.

The intended use of the tablet was be to be administered orally to a patient, and thus the tablets produced should

have demonstrated good uniformity of weight, low friability, high tensile strength and low disintegration time, in

order to be suitable for this purpose. The starch and magnesium stearate concentrations required in order to

produce tablets with high tensile strength and low disintegration time were successfully predicted using multiple

linear regression analysis, with reliable models. But the optimum concentrations required to achieve low

friability or good uniformity of weight were not found.

It was predicted that the optimum tablet formulation would be achieved with approximately 9.5-10.0% starch

with approximately 0.0-0.4% magnesium stearate. From the concentrations tested in the experiment, this

formulation was predicted to give the lowest disintegration time of 120 -240 seconds, and the highest tensile

strength of 2.3-2.5 MPa. As a result, using this formulation should produce tablets that are able to fragment and

disintegrate quickly when swallowed, as well as be durable enough to withstand transit and storage.

However, the optimum formulation could be improved in many ways. Firstly, the formulation’s predicted

friability and uniformity of weight weren’t able to be obtained due to unreliable results from these experiments.

Though, as tensile strength is closely linked to friability, it could be assumed that this formulation would have

low friability as it has high tensile strength, but a repeat test would be necessary to affirm this. Repeating the

experiment and redoing the friability and uniformity of weight tests would be beneficial.

Secondly, crospovidone was the originally selected disintegrant, but it was not available in the lab. Crospovidone

is a super-disintegrant which can be used in lower concentrations than starch, and it also carries the additional

benefit of not having as high a lubricant sensitivity as starch1. Therefore, future studies with the use of

crospovidone instead of starch, could improve this formulation.

Furthermore, another potential future study is the addition of the surfactant sodium lauryl sulphate. Sodium

lauryl sulphate could improve the formulation further as it is known to increase wetting, and thus could be used

to overcome the effect that increasing magnesium stearate concentration has on increasing disintegration time7.

Though, not only could the formulation be improved, but also the experiment. Some improvements suggested in

Section C include: measuring the disintegration time of each tablet in a batch, and taking the mean in order to get

a value more representative of the whole batch; and performing a full residual analysis of data, with outliers

removed, to prevent biased R2 values.

Lastly, if the unexpected friability and uniformity of weight results were suspected to be due to human error. The

experiment should have been repeated to confirm/disprove this. However, due to strict time constraints this was

not possible.

Page 24 of 25


F) References

1 DFE Pharma Introduction to Tableting by Direct

Compression,

http://www.dfepharma.com/en/downloads.aspx?id={1E3139

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the different excipients useful for the direct compression of

tablets, 2000, Pharmaceutical science & technology

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3 McCormick,D., Evolutions in Direct Compression, 2005,

Pharmaceutical Technology, 52-62

4 Banker G., Rhodes C., Drug and Pharmaceutical Sciences:

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Volume 121, 462

5 Florence, A. T, Materials Used in Pharmaceutical

Formulation, 1984, Blackwell Scientific Publications, 44

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Varghese Publishing House, 328

7 Remington, J., Gennaro, A., Remington: The Science and

Practice of Pharmacy; 21st Edition, 2006, Lippincott

Williams & Wilkins, 891-893

8 Rowe, R., Sheskey, J., Owen, S., Handbook of

Pharmaceutical Excipients, 2006, London Pharmaceutical

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9 Carstensen J, Solid Pharmaceutics: Mechanical Properties

and Rate Phenomena, 1980, Academic Press, 96, 184

10 De Boer, A. H., Bolhuis, G. K., Lerk, C. F., Bonding

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11 Aulton M. E, Aulton's Pharmaceutics: The Design and

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12 Kikuta, J. I., Kitamori, N., Effect of mixing time on the

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characteristics of the compressed tablets, 1994, Drug

Development and Industrial Pharmacy, Volume 20, Issue 3,

343-355

13 WHO Excipient Guidelines,

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London Stationery Office

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specifications on disintegration test performance, 2010,

Dissolution Technologies, Volume 16, 6-10

18 Desai, D. S., Rubitski, A., Varia, A., Newman, W.,

Physical interactions of magnesium stearate with starch-

derived disintegrants and their effects on capsule and tablet

dissolution, 1993, International journal of pharmaceutics,

Volume 91, Issue 2, 217-226.

19 Bolhuis, G. K., Smallenbroek, A. J., Lerk, C. F.,

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20 http://www.engsys.co.uk/pages/products.php, Accessed

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starch in tablet formulations: properties on compaction,

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Page 25 of 25


G) Appendix

Figure 14: The absorbance values of various concentrations of paracetamol BP.

y = 0.0484x - 0.018R² = 0.9998

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 1 2 3 4 5 6 7 8 9

Ab

sorb

ance

Paracetamol BP Concentration (mg/L)

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Optimising the use of magnesium stearate and starch in ... · Optimisation of a Paracetamol Tablet Formulation Optimising the use of magnesium stearate and starch in direct compression