Solid Dose Pharmaceutical PAT and
Process validation
Presented By
Chinese Name: ZILING CHEN
English Name: Vincent
TU student number:X00168656
Bsc in Pharmaceutical Science
Department of Science Technological
University Dublin
Supervisor name: Andrew O Connor
November 2022
0
Abstract
As a senior level 8 student majoring in pharmacy, we have learned drug
analysis technology, pharmaceutical plant equipment design, GMP and SOP in
the university. It is time to link all the knowledge we have learned together.
Starting from raw materials, this experiment gives us a chance to simulate the
whole process of producing solid tablets in pharmaceutical factories. This
experiment applied a variety of methods and instruments to examine and
compare the various characteristics of the powder, which is used to proceed
further production. For example, Vibrating sieving, tap density, Eyecon, Leica
camera and Malvern is used to analyze the bulk powder in this experiment.
Aside from this, Aspirin is one of the most widely used drugs with a long history
in the world. It is very valuable for us to have a deep understanding of its
manufacturing process in pharmaceutical factories. For raw material, four
kinds of dehydrated lactose were used as fillers of tablets in this experiment,
together with API aspirin, filler starch and lubricant magnesium stearate. We
will analyze the similarities and differences of the characters of these powders
before and after mixing.
1
Content
1.0 Aim…………………………………………………………………….………….3
2.0 Objectives………………………………………………………………………..3
3.0 Introduction………………………………………………………………………3
3.1 Lactose…………………………………………………………..…………..3
3.2 aspirin………………………………………………………………………..4
3.3 Sieving equipment…………………………………………………………..5
3.4 Bulk and Tapped Density…………………………………………..…...….6
3.5 Eyecon……………………………………………………………………….7
3.6 Microscopy/Leica camera………………………………………………….8
3.7 Malvern……………………………………………………………………....8
3.8 Blender TURBULA………………………………………………………….9
3.9 UV-160A……………………………………………………………………..9
3.10 ATR………………………………………………………………………..10
3.11 NIR………………………………………………………………………...10
4.0 Material and Methods………………………………………………………….11
5.0 Result and discussion…………………………………………………………11
5.1 Sieving result……………………………………………………………….11
5.2 Compressibility result of raw material……………………………………12
5.3 Leica camera image of raw material………………………………….....13
5.4 Malvern result of raw material…………………………………………….13
5.5 Eyecon result of raw material……………………………………………..14
5.6 Compressibility result of samples after blending…………………….....17
5.7 Leica camera image of samples after blending…………………………18
5.8 Eyecon result of samples after blending………………………………...18
5.9 Malvern result of samples after blending………………………….....….20
5.10 NIR results…………………………………………………………...……21
5.11 ATR result and Comparison against NIR……………………………....22
5.12 UV-160A results…………………………………………………………..23
6.0 Conclusion……………………………………………………………………...24
7.0 Reference………………………………………………………………………25
2
1.0 Aim
Investigate the difference in physical characterization result of four kinds of
lactose excipient used in tablet compaction.
Investigate physical compatibilities of active active pharmaceutical ingredient
(API) and excipients.
Blend uniformity testing.
2.0 Objective
Measure and compare the particle size, compressibility and bulk density of
four types of lactose and API.
Compare the similarity and differences of NIR and ATR spectrum.
Measure the difference in physical characterization result of four kinds of
lactose excipient used in tablet compaction through different types of
techniques.
Run Malvern analysis of all material including magnesium sterate.
Run blend uniformity studies (time versus lactose types).
3.0 Introduction
3.1 Lactose
Lactose is a disaccharide sugar
synthesized by galactose and glucose
subunits and has the molecular
Figure 1: The structure of lactose
formula C12H22O11. Its systematic
name is β-D-Galactopyranosyl-(1→4)-D-glucose. The chemical structure of
lactose is shown in figure1.
The intestinal villi secrete the enzyme lactase (β-D-galactosidase) to digest it.
This enzyme cleaves the lactose molecule into its two subunits, the simple
sugars glucose and galactose, which can be absorbed. The production of
3
lactase gradually decreases with maturity of infant mammals due to a lack of
continuing consumption.
About 60%–70% of pharmaceutical dosage forms contain lactose. Lactose can
have several functions in a dosage form: as a filler to provide bulk to for
instance tablets, as a binder to provide the strength to a dosage form to keep it
together, and to provide the flow to a formulation to be capable of producing it.
Next to that, the excipient can assist in delivering the drug to the place of
action. Lactose is a versatile excipient that is safe to use, relatively cheap, and
widely available in many forms.[1] 4 kinds of lactose (AN21, AN22, AN24,
DOMO) are to be used as filler in this experiment，they play the role of
excipient together with lubricant magnesium stearate and filler starch.
3.2 Aspirin
Following the advent of synthetic salicylate,
Felix Hoffman, working at the Bayer company in
Germany, made the acetylated form of salicylic
acid in 1897. This drug was named “Aspirin”
and became the most widely used medicine of
all
Figure 2: Chemical structure of
aspirin
time.
In
mechanism
1971,
by
Vane
which
discovered
aspirin
exerts
the
its
anti-inflammatory, analgesic and antipyretic
actions. He proved that aspirin and other non-steroid anti-inflammatory drugs
(NSAIDs) inhibit the activity of the enzyme now called cyclooxygenase (COX)
which leads to the formation of prostaglandins (PGs) that cause inflammation,
swelling, pain and fever.[2]
The starch, the active ingredient, and the lubricant are weighed separately in
sterile canisters to determine if the ingredients meet pre-determined
specifications. All components are poured into the Mixer. Mixing blend the
ingredients to achieve uniformity as well as exhaust air from the mixture. The
mixture is then mechanically separated into units, which are called slugs. Then,
4
Large batches in sizable manufacturing outlets are filtered through a machine
called a Fitzpatrick mill to undergo dry screening.
Figure3 (left): Three steps before aspirin production: weighing, mixing and dry sieving
Figure4 (right): tablet compaction with one set of tooling
After that, the mixture is compressed into tablets either by a single-punch
machine or a rotary tablet (multi-punch) machine for large scale. The
compressed tablets are subjected to quality control tests such as tablet
hardness and friability test, as well as a tablet disintegration test, etc. A line is
usually drawn on the finished aspirin to facilitate the pharmacist to break the
tablet in half. The tablets are transferred to an automated bottling assembly
line where they are dispensed into plastic bottles or glass bottles. The bottles
are then labeled with product information and expiration date.[3]
3.3 Sieving equipment
Vibrating sieving system is the most widely used
particle
size
distribution
method
using
in
pharmaceutical industry. They are Inexpensive, quick
and simple to be operated to have an overall view of
raw material. The procedure is to shake the sample
through a series of continuously smaller sieves
(upper sieves has bigger mesh size). Weigh the
Figure 4: vibrating sieving
5system apparatus
portion of sample remaining on each sieve, the data will finally be formed as a
bar chart. Vibrating sieving system have no account of particle shape and
broad size range as material left on sieve has a particle size range starting
form that sieve size up to the size of the sieve attached above, which is the
reason of bar chart output on percent weight instead of numbers of particles.
Critical parameters are vibration time and oscillation width.
3.4 Bulk and Tapped Density
Flowability of powders is an important aspect in the
manufacturing of solid dosage forms. In recent years the
compressibility index first described by Carr or closely
related Hausner’s ratio have become the simple, fast,
and popular methods of predicting powder flow
characteristics. To calculate these parameters, which
Figure
machine
5:
Tapping
are not intrinsic properties and can be influenced by size
and shape, surface area, moisture content, and
cohesiveness of the material, it is necessary to determine the unsettled
apparent volume and final tapped volume or the corresponding bulk and
tapped density.[4] Poured bulk density is volume measured after pouring
powder into a cylinder without any outside force and shake, creating a
relatively loose structure with air between large particles and small particles.
The Tapped Bulk density is the maximum density that can be achieved after
deaeration by tapping, as small particles enter the gap between large particles.
During this experiment, we set the tapping time at 10, 500 and 1250 and
compare the difference of their results. Lager CI indicates worse flowability.
Figure 6: CI index and Hausner ratio formulation
6
3.5 Eyecon
The Eyecon particle sizing technology was
also tested. This is a very recent 3D-imaging
system that allows the determination of the
PSD for moving particles using a flash imaging
technique (Figure 5). The equipment can either
Figure
6:
apparatus
Eyecon
camera
be
used
offline
or
in-process.
During
measurements, a powerful short light pulse is
created and provided that the particle movement during this pulse is negligible
a sharp image without blurring is captured. The particles are illuminated with
red, green, and blue LEDs from different angles.
The color on the surface of the particle
is captured in an image, and for each
individual pixel, a map of the surface
height is built. Furthermore, using
image gradient data an ellipse is fitted
Figure 7: Working principle of eyecon
on the particle edges, and its maximum
and minimum diameters are obtained.
These are used to calculate the average aspect ratio (AAR) of particles as an
indicator of their sphericity by means of the following equation: AAR=Dmax/Dmin
where Dmax represents the maximum measured diameter and Dmin the
minimum measured diameter. Also, the average diameter can be assessed
according to the following equation: d=(Dmax+Dmin) /2
Each captured image is analyzed by Eyecon resulting in a group of ellipses.
Results can either be computed using only the current image or also include
data from previous images and are presented as a histogram. The D values
are calculated by ordering particles in order of ascending relative mass. Firstly,
the total mass is computed, and then, an iterative algorithm adds up starting
with the smallest of the particles. As the running total reaches 10%, 25%, 50%,
7
75%, and 90% of the total mass, the diameter of the last added particle is
recorded as being the D10, D25, D50, D75, and D90 diameter, respectively.[5]
3.6 Microscopy/Leica camera
Microscopy is the technical field of using microscopes
to view objects and areas of objects that cannot be
seen with the naked eye (objects that are not within the
resolution range of the normal eye). There are three
well-known branches of microscopy: optical, electron,
and scanning probe microscopy, along with the
Figure 8: Leica camera
apparatus
emerging field of X-ray microscopy. [6]
Optical microscopy and electron microscopy involve
the diffraction, reflection, or refraction of electromagnetic radiation/electron
beams interacting with the specimen, and the collection of the scattered
radiation or another signal in order to create an image. Leica camera using
white light particles between 1 micron to about 10 mm to create image. They
are good for qualitative particle shape while they are tedious to generate
particle size distribution. They can only be used to have overall quick
qualitative check on particle shape.
3.7 Malvern
Malvern, also known as the Laser light scattering
is used for generating very high-resolution data
of particle size distribution. As the scattering
pattern, scattered intensity as a function of
scattering
Figure 9: Malvern equipment
dependent,
angle,
it
is
follows
largely
particle
size
that
particle
size
information can be extracted from the experimentally determined pattern.
Older instruments mainly rely on the Fraunhofer approximation to derive
particle size information from the scattering pattern, while recent light
8
diffraction particle size analyzers are based on Mie’s theory (big particles
scatter at small angle).[7]
3.8 Blender TURBULA
TURBULA
mixer
interaction
of
applies
rotation,
the
harmonic
translation
and
inversion throughout the mixing process. It
can achieve a high level of uniformity during a
short period of blending time. It has the
advantages
Figure 10: Image of TURBULA
of
easy
maintenance
and
cleaning, dust-free production, low shear
T2F
force, etc. The equipment is widely used in food, pharmaceutical and cosmetic
industries. We use TURBULA T2F to mix three samples of mixture of
acetylsalicyclic acid lactose, magnesium stearate and starch by different times.
3.9 UV-160A
The UV-VIS spectrophotometer operates
according to the following principle: the
absorption spectrum is produced by an
electronic energy level change after some
Figure11: UV-160A apparatus
groups in the molecule absorb UV-VIS light. A
substance's ability to absorb light energy will differ depending on its molecules,
atoms, and molecular space configurations. Therefore, the absorption spectra
curve for each material is distinct and fixed. This property allows for the
investigation of compounds on a qualitative level. The content of the substance
can be measured by measuring the absorbance or transmissivity of the
substance because the absorbance at specific characteristic wavelengths in
the absorption spectrum is also different depending on the substance's
quantity. This is the basis of qualitative and quantitative spectrophotometric
analysis, and is also the working principle of the ultraviolet visible
9
spectrophotometer of the analytical instrument.
3.10 ATR
Total internal reflection, which produces an evanescent wave, is a quality used
by ATR. An infrared laser beam is directed through the ATR crystal so that it
bounces off the interior surface in contact with the sample at least once. The
evanescent wave that penetrates the sample is created by this reflection. The
exact value depends on the light wavelength, angle of incidence, and indices
of refraction for the ATR crystal and the material being probed. The penetration
depth into the sample is normally between 0.5 and 2 micrometers. The
incidence angle can be changed to alter the number of reflections. As the
beam leaves the crystal, a detector then captures it. Most modern infrared
spectrometers can be converted to characterize samples via ATR by mounting
the ATR accessory in the spectrometer's sample compartment. The
accessibility, rapid sample turnaround and ease of ATR-FTIR has led to
substantial use by the scientific community.[8]
3.11 NIR
The near-infrared (NIR) spectrum belongs to the double
frequency and dominant frequency absorption spectrum
of the molecular vibration spectrum. It is mainly
generated when the molecular vibration transits from the
ground state to the high energy level due to the
non-resonance of the molecular vibration, and has
Figure 3: Feed inlet of
strong penetrability. Near infrared light mainly refers to
NIR apparatus
the frequency doubling and combined absorption of the
vibration of hydrogen containing group X-H (X=C, N, O), which contains the
information about the composition and molecular structure of most types of
organic compounds. When near-infrared light is irradiated, the light with the
10
same frequency and the group will have resonance, and the energy of light will
be transferred to the molecule through the change of molecular dipole moment;
Since near-infrared light has a frequency that is distinct from the vibration
frequency of the sample, it will not be absorbed. Because of this, when
near-infrared light with continuously varying frequency is used to irradiate a
sample, due to the sample's selective absorption of near-infrared light with
various frequencies, the near-infrared light passing through the sample will
become weak in some wavelength ranges, and the transmitted infrared light
will carry the information of organic composition and structure. Analyzing the
optical density of light that is transmitted or reflected via the detector can be
used to determine the content of this component.
4.0 Material and Methods
We didn’t do FT4 freeman analysis while all the other steps and procedures
are same as manual.
5.0 Result and Discussion
5.1 Sieving result
Table 1: percent weight of sieving result
Lactose
Group
710um
500um
250um
150um
125um
90um
50um
36um
21 AN
1
0.02%
0.04%
80.08%
11.40%
2.92%
3.70%
1.44%
/
22 AN
2
0.00%
0.00%
48.53%
30.65%
7.97%
/
/
13.80%
24 AN
3
0.00%
0.00%
17.17%
35.03%
11.92%
/
/
35.99%
Domo
4
0.10%
0.20%
1.70%
35.66%
20.44%
/
/
41.83%
Aspirin
5
2.84%
10.44%
73.70%
11.70%
0.74%
/
/
/
type
From table1 above, the particle size of most lactose particles is less than
500um. The particles of most AN21 and aspirin are concentrated between
250um and 500um, while the particle size of 22AN particles is concentrated
between 250um and 500um and between 150um and 250um. However, the
particles of 24AN and DOMO are not distributed much between 125um and
500um, and many particles remain on the 36um sieve. We can infer that some
11
of their particles should be distributed on the 90um sieve and 50um sieve that
we did not add in the sieving system.
Except Group1, other groups didn’t add 90um and 50um mesh size sieve to
the sieving system due to height and time limitation. So, the data produced is
of low quality. We can hardly tell the full particle size distribution from the data
in the table. Combining the image from microscopy, we now know why 21AN
and aspirin have the similar weight percent distribution in sieving analysis as
these two kinds of particles all have a large size under Leica camera.
5.2 Compressibility result of raw material
Table2: Tapping results of different kinds of lactose and aspirin.
Lactose
type
21 AN
22 AN
24 AN
Domo
Aspirin
Group
1
2
3
4
5
V0(cm3) V10(cm3) V500(cm3) V1250(cm3)
145
129
150
142
134
135
120
148
130
128
119
117
143
126
122
117
116
142
125
121
CI
19.31%
10.07%
5.33%
11.97%
9.70%
In terms of absolute value, 21AN lactose decreased by 28 cubic centimeters
after 1250 taps, ranking first among all kinds of lactose and aspirin. In contrast,
24AN has reduced by 8 cubic centimeters, with the least volume reduction.
From the relative value, the CI value of 21AN is 19.3%, which is much larger
than the minimum 24AN (5.3%), while the other two kinds of lactose together
with aspirin, have similar CI around 10%, which is 10.07%, 11.97% and 9.7%
for 22AN, DOMO, and aspirin separately.
21AN has the highest CI value, which means it has the worst liquidity. On the
contrary, 24AN has the lowest CI value, which means it has the best liquidity.
Combining the results of Leica camera image and sieving, 21AN has the
largest average particle size, the largest CI value and the worst liquidity. To
sum up, we can confirm a theory we learned from the previous PAT class that
reducing the particle size to a certain extent can increase the particle mobility.
12
5.3 Leica camera image of raw material
Figure 13：Microscope image of 21 AN (left) and 22AN (right)
Figure 14：Microscope image of 24 AN (left) and DOMO (right)
Leica cameras are used for qualitative particle shapes. You can see the
particle of DOMO (figure5) is a total chaos and there are a lot of small granular
powder chips and some small lactose crystal. The shape of 21AN and 22AN
lactose are similar, 21AN and 22AN crystals have oblong shapes with smooth
edge and they can normally flow easily. (figure4) 24AN appears to have a
smoother surface, close to a spherical shape, which may be easier to flow than
21AN and 22AN lactose.
The Domo image is not clear enough to see the shape, this may be due to the
way the sample is placed on the plate, because the particles are stacked
together and their optical microscopes have smaller magnification than others.
It is best to put a small amount of powder and separate them on a plate
uniformly to clearly show the size of the particles.
5.4 Malvern result of raw material
13
Figure 15: Overlay diagram of particle size distribution (21AN, 22AN, 24AN, DOMO, pure
aspirin)
The particle size distribution of 21AN, 22AN, DOMO and aspirin have the
similar particle size distribution. Their peaks are all around 100um-1000um.
While the peak of 24 AN is at around 90um, much smaller than other three
kinds of lactose and aspirin. Meanwhile the peak width of its peak is much
larger than other raw materials, indicating the worst uniformity (particles size
distribute widely between 10um to 1000um.
Table3: different d-value of different particle type
Particle type
d(0.1)um
d(0.5)um
d(0.9)um
Uniformity
21AN
27.09
179.50
368.06
0.578
22AN
68.26
206.24
402.44
0.497
24AN
19.55
73.36
248.11
1.410
DOMO
45.14
141.01
255.99
0.442
Aspirin
70.80
322.01
638.73
0.527
Total
73.69
340.37
707.77
0.556
The d value of 24AN is 19.55, 73.36 and 248.11, which is smaller than any
other powders, which means it has the smallest particle size, being another
strong proof of the best flowability of 24AN.
5.5 Eyecon result of raw material
14
15
Figure 16: Average histogram of 21AN, 22AN, 24AN, DOMO and Aspirin raw material
(from top to bottom)
Eyecon has a worse resolution of particle size distribution and as a result, its
output still rely on bar chart. Most of the 21AN and 22AN particles are in the
100 to 600um size range, while 24AN and DOMO are both more concentrated
in the 200um to 400um size range. Unlike any of them, the bar chart of aspirin
shows a very wide particle size distribution, from 200um to 1400um, reflecting
the irregular crystalline shape of aspirin and sugges\ting that aspirin may have
a much poorer fluidity.
Figure 17: Malvern image of 21AN, 22AN, 24AN lactose
Figure 18: Malvern image of DOMO lactose and aspirin
The pictures of 21AN, 22AN and 24AN all have the same magnification and
show similar shapes: oblong shapes with smooth edge. While the image of
DOMO has smaller magnification and we could hardly tell the shape and
structure of its crystal and aspirin has a larger magnification which shows its
strip shape clearly.
16
Table4: D-value and AR value of raw material
Lactose type
D10
D50
D90
Aspect ratio
RSD%
21AN
217.6
354.2
454.8
1.2
11.4
22AN
218.4
343
448.4
1.2
11.6
24AN
208
308.9
452.2
1.1
9.9
DOMO
198.1
282.7
368.4
1.1
9.4
Aspirin
412
655.2
1180.6
1.2
14.4
The aspect ratio of 21AN, 22AN and Aspirin is 1.2, and that of 24AN and
DOMO is 1.1. The smaller the Aspect ratio, the closer the particle is to the
spherical shape, the smoother its surface, and the better its fluidity. The d
value of DOMO is the smallest, and the d value of aspirin is the largest, and
the d value of the other three lactose is in the middle. At the same time, 24ANs
and DOMOs with smaller Aspect ratios also have smaller relative standard
deviations. Because Eyecon conducts particle size analysis based on phase
principle, it is more likely that more spherical particles will be photographed
with the same particle size by the camera, which may also be the reason for
the smaller RSD value of these particles.
5.6 Compressibility result of samples after blending
Table5: Tapping results of mixture samples after different blending time.
group
V0(cm3)
V10(cm3)
V500(cm3)
V1250(cm3)
CI
21AN 1min
50
48
46
45
10.00%
21AN 5min
56
a55
54
53
5.36%
21AN 10min
62
61
58
56
9.68%
22AN 1min
60.5
60
58
58
4.13%
22AN 5min
59
58
55
54
8.47%
22AN 10min
61
60
56
56
8.20%
24AN 1min
70
69
66
64
8.75%
24AN 5min
/
/
/
/
/
24AN 10min
59.7
59
55.4
54
9.55%
DOMO 1min
60.9
60
56.1
55
9.69%
DOMO 5min
59
57
55
54
8.47%
DOMO 10min
59.7
59
55.4
54
9.55%
The data of 5-min blending from the sample of 24AN is totally lost. For other
numbers, CI value has no significant relationship with mixing time. 21AN
reached the minimum CI value after 5 minutes of mixing and rose after 10
17
minutes. 22The CI value of AN was the lowest after 1 minute of mixing, but it
rose in the future. Like 21AN, DOMO has the lowest CI value at 5 minutes.
5.7 Leica camera image of samples after blending
Figure 19：Microscope image of 21 AN (from left to right: 1min, 5min, 10min)
Figure 20：Microscope image of 22 AN (from left to right: 1min, 5min, 10min)
Figure 21：Microscope image of 24 AN (from left to right: 1min, 5min, 10min)
Figure 22：Microscope image of DOMO (from left to right: 1min, 5min, 10min)
From figure 19, 20, 21 and 22, We can clearly see the long white aspirin
particles mixed in different kinds of lactose powders. However, the number of
aspirin particles in the image has no obvious relationship with the mixing time
of different samples. This may be due to the short mixing time, or the
randomness of image shooting and personnel operation variables.
5.8 Eyecon result of samples after blending
18
Figure 23：Eyecon image of 21 AN (from left to right: 1min, 5min, 10min)
Figure 24：Eyecon image of 22 AN (from left to right: 1min, 5min, 10min)
Figure 25：Eyecon image of 24 AN (from left to right: 1min, 5min, 10min)
Figure 26：Eyecon image of DOMO (from left to right: 1min, 5min, 10min)
From figure 23, 24, 25 and 26, We can clearly see the long white aspirin
particles mixed in different kinds of lactose powder. However, the number of
aspirin particles in the image has no obvious relationship with the mixing time
of different samples. This may be due to the short mixing time, or the
randomness of image shooting and personnel operation variables.
Table 6: d value of samples from different blending time
Group
Number
Blending
time(min)
D10
D50
D90
Aspect
ratio
RSD%
21AN
1
350.4
569.5
1143.4
1.2
13.2
5
259.1
416.2
700.7
1.2
11.7
10
293
445.1
822.2
1.2
13.7
1
257.7
432.5
693.1
1.2
12.8
5
429
817
1236.7
1.2
15.8
10
363.6
514.3
926.9
1.2
12.4
1
372.3
521.2
889.9
1.2
12.6
5
371.5
671.1
1069.3
1.2
12
10
334.4
534.6
873.1
1.2
13.5
22AN
24AN
19
DOMO
1
343.5
524
895.3
1.2
13.9
5
/
/
/
/
/
10
357.5
623.4
943
1.2
16.5
All Aspect ratio become 1.2 because of blending while all RSD% become
larger than raw material as the mixture of big particle (aspirin) and small
particle (lactose). All kinds of lactose seem to have the largest d90 after 5
minutes blending, but we can’t confirm it as the loss of data from DOMO 5-min
blending.
5.9 Malvern result of samples after blending
20
Figure 27: Malvern particle size distribution after blending (from top to bottom: 1min,
5min, 10min)
Above is the particle size distribution of 22AN, the uniformities of three
samples blended by different time are similar to each other, the trend of
d-value also have small difference from each other. The peak in all three
diagrams have large tail on the left and barely have no tail on the right.
Table 7：Malvern results of samples after blending
Particle
type
21AN
22AN
24AN
DOMO
Blending
time(min)
1
5
10
1
5
10
1
5
10
1
5
10
d(0.1)um
d(0.5)um
d(0.9)um
Uniformity
53.74
58.35
57.62
80.38
78.18
90.17
41.47
72.40
29.68
61.94
75.76
68.45
289.86
302.93
289.08
323.44
306.74
334.19
290.41
430.81
182.02
247.83
319.56
273.85
635.93
672.59
633.44
672.34
638.77
701.69
691.01
913.39
638.81
614.24
816.23
704.44
0.604
0.608
0.594
0.551
0.552
0.550
0.697
0.580
1.060
0.682
0.712
0.712
5.10 NIR results
Figure 28: NIR spectrum of 21AN lactose after blending (1min, 5min, 10min and pure)
21
Figure 29: NIR spectrum of 22AN lactose after blending (1min, 5min, 10min and pure)
Figure 30: NIR spectrum of 24AN lactose after blending (1min, 5min, 10min and pure)
Figure 31: NIR spectrum of DOMO lactose after blending (1min, 5min, 10min and pure)
When mixing continues, the ATR spectra at different times can overlap. When
they are nearly identical, it means that the mixing is uniform. From the
operation of this ATR experiment, except that the 5 minute and 10-minute
atlases of 21AN are similar, others are different. In addition, due to the missing
data of DOMO for five minutes and 10 minutes, we can’t further compare the
differences in the time of mixing of different lactose samples.
5.11 ATR result and Comparison against NIR
Figure 32: ATR spectrum of 21AN lactose after blending (1min, 5min, 10min and pure)
Figure 33: ATR spectrum of 22AN lactose after blending (1min, 5min, 10min and pure)
22
Figure 34: ATR spectrum of 24AN lactose after blending (1min, 5min, 10min and pure)
Figure 35: ATR spectrum of DOMO lactose after blending (1min, 5min, 10min and pure)
After the addition of aspirin, there was a significant difference between the
mixed
samples
and
the
NIR
spectra
of
pure
lactose.
At
the
wavenumber=1000cm-1, a large peak of pure lactose is replaced by a large
number of small peaks in the sample spectrum. From this, we can also judge
that almost no aspirin was added to the sample after 24AN was mixed for 5
minutes and 10 minutes, because the spectrum of the sample after mixing was
not very different from the original pure lactose, because there was a big peak
at the specific wavenumber. At the same time, we can't see the exact
relationship between mixing time and sample spectrum from these images.
The data generation principles of ATR and NIR are roughly the same, and both
provide us with spectral information of sample composition and content, but in
different forms.
5.12 UV-160A result
Table 8: UV-160A result (1)
Initial
Aspirin
Aspirin
Aspirin
Aspirin
Averages
Weight mg
10.4
11
10.5
9.6
10.27
vol
50
50
50
50
50
Abs 10/50
1.12
1.37
1.3
1.6
ppm
41.6
44
42
38.4
40 ppm
38.462
36.364
38.095
41.667
Average
Abs/ppm
0.02912
0.037675
0.034125
0.0384
0.03483
Table 9: UV-160A result (2)
Lactose
Abs
Time
Weight
type
21AN
23
1
25.7
Abs Normal
Conc Aspirin
Target
Vol
50
Average Conc
Difference
10/50
25mg
ppm
75ppm
1.614
1.570038911
45.07720099
75ppm
Std dev
% RSD
0.214395875
0.473842674
PPM
-29.92279901
45.246215
21AN
5
25.2
50
1.597
1.584325397
45.48737861
75ppm
-29.51262139
21AN
10
25.2
50
1.586
1.573412698
45.17406542
75ppm
-29.82593458
22AN
1
23.8
50
1.542
1.619747899
46.50438987
75ppm
-28.49561013
22AN
5
25.2
50
1.61
1.597222222
45.85765783
75ppm
-29.14234217
22AN
10
26
50
1.627
1.564423077
44.91596546
75ppm
-30.08403454
24AN
1
25
50
1.787
1.787
51.3063451
75ppm
-23.6936549
24AN
5
24.7
50
2.059
2.084008097
59.83370936
75ppm
-15.16629064
24AN
10
26
50
1.792
1.723076923
49.47105722
75ppm
-25.52894278
DOMO
1
25.4
50
1.617
1.591535433
45.6943851
75ppm
-29.3056149
DOMO
5
25.7
50
1.543
1.500972763
43.09425101
75ppm
-31.90574899
45.75933772
0.79876352
1.745574913
53.53703723
5.529749576
10.32883002
44.00729399
1.462715694
3.323802854
24AN has the largest %RSD between samples blended through different times.
We focus on the target concentration 75ppm and the difference between
actual concentration of our samples and target concentration. The closer these
two data are, the more uniform the blend is. During this experiment, the
sample of 24AN blend in 5min by Kreat has the smallest difference between
target concentration, which means he has the best uniformity. For group2, the
lowest difference between sample and target occurs at 1min blend, and we
can’t tell a obvious trend among other data, and blending time seems not have
an impact on the sample uniformity. But this result is against theory, we think
the operator variance and short overall blend time may lead to its problem.
6.0 Conclusion
We used vibrating sieving system, Eyecon cameras, Leica camera and Laser
light scattering to observe and characterize the particle size and particle shape.
We run Malvern analysis for all materials including mixture after blending.
Besides, we do UV-160A for blend uniformity study for different lactose types
versus blending time. Unfortunately, we failed to find the trend of uniformity
study for lactose type versus blend time and the problem may be caused by
Operating errors due to various additional vibrations and shakes that we
impose on the sample when doing other characterization experiments with the
blended sample.
Based on the results of sieving, 21AN has the biggest particle size among
lactose and 24AN is the smallest while aspirin is basically larger than all kinds
24
of lactose. During tap density analysis, 21AN has the largest CI and 24AN has
the smallest CI before blending. On contract, samples from 22AN reach the
smallest CI (4.8% for 1-min blending). We still can’t find the relationship
between CI and blending time. For Leica camera and Malvern, their d value is
related to particle size no matter whether the sample is pure or mixed. We
compared the spectrum produced by NIR and ATR, the data generation
principles of ATR and NIR are roughly the same, and both provide us with
spectral information of sample composition and content, but in different forms.
This experiment is full of lost data due to operators and chaos, the messy
process brought a lot of difficulties to further data analysis. We need to practice
our lab skills more frequently.
7.0 Reference
[1] Chapter 5, Application of lactose in the pharmaceutical industry,
Evolutionary Role, Health Effects, and Applications 2019, Pages 175-229.
[2] The mechanism of action of aspirin, J.RVane, R.MBotting, Thrombosis
Research, Volume 110, Issues 5–6, 15 June 2003, Pages 255-258.
[3] Aspirin, Weissmann, Gerald, Scientific American. January, 1991, pages
84-90.
[4] Schussele A, Bauer-Brandl A. Note on the measurement of flowability
according to the European Pharmacopoeia. Int J Pharm. 2003;257(1–2):301–
4.
[5] Ana F.T. Silva, Anneleen Burggraeve, Quenten Denon, Paul Van der
Meeren, Niklas Sandler, Tom Van Den Kerkhof, Mario Hellings, Chris Vervaet,
Jean Paul Remon, João Almeida Lopes f,Thomas De Beer, Particle sizing
measurements in pharmaceutical applications: Comparison of in-process
methods versus off-line methods, European Journal of Pharmaceutics and
Biopharmaceutics 85 (2013) 1006–1018.
[6] The University of Edinburgh (March 6, 2018). "What is Microscopy?". The
University of Edinburgh. Retrieved April 9, 2018.
25
[7] A. Rawle, Basic Principles of Particle Size Analysis, Malvern Instruments
Ltd.,Technical Paper, Worcestershire, UK, 1993.
[8] F. M. Mirabella, Jr., Practical Spectroscopy Series, Internal reflection
spectroscopy, Theory and applications, Marcel Dekker, Inc., Marcel Dekker,
Inc., 1993, 17-52.
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