ATR Imaging Pharmaceutical Tablets - Ulrika Lundgren FTIR product specialist April 2007
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ATR Imaging Pharmaceutical
Tablets
Ulrika Lundgren FTIR product specialist
April 2007Potential for ATR Imaging Pharmaceuticals
ATR advantages ATR drawbacks
Excellent specificity – mid-IR Sample is in contact with ATR
transmission like spectra element
Good signal to noise – high Flat surface required
efficiency designs possible Image area relatively small – up
IR imaging technology well to ca 0.5x0.5mm
established
Excellent spatial resolution –
better than 4 microns at 1700
cm-1
Low sample penetration (~1-2
microns with Ge element)
Highly detailed images in
minutes
Page 2The innovative Spotlight 400…
Page 3
…more detail, faster, easier – the results will inspireSampling flexibility provides the most information…
Accommodates samples up to 10mm thick for the maximum
applications flexibiility
600 µ diameter crystal tip of which 500 µ guaranteed “defect
free”
• Enables 400 µ areas to be collected
• 100 x bigger than currently available
• More information from your samples
A number of rectangular or square areas can be selected
• Reducing redundancy and increasing the analysis time
Page 4
…the most efficientlyPreparing for Tablet ATR Imaging
Use standard KBr micro-pellet
press to prepare pure
component disks
Requires a few mg of material
Hand-pressure required
Disks typically e.g 2mm
diameter
Can use larger presses (larger
pressures required
Place 2 discs in the die and
place directly in the ATR
accessory
Page 5Example Suspected Raw Ingredients Spectra
Microcrystalline cellulose
Calcium phosphate
%T A
Magnesium stearate
Starch
Povidone (PVP
(not present!)
4000.0 3000 2000 1500 1000 720.0 4000.0 3000 2000 1500 1000 720.0
cm-1 cm-1
ATR spectra 1st derivative
Page 6Example Testing for Presence of Raw Ingredients
Avicel Starch
Raw ingredient
(1st derivative)
A A
Least squares fit
4000.0 3000 2000 1500 1000 720.0 4000.0 3000 2000 1500 1000 720.0
cm-1 cm-1
Page 7Testing for Presence of Raw Ingredients (II)
Calcium phosphate Magnesium stearate
Raw ingredient
(1sr derivative)
A A
Least squares fit
4000.0 3000 2000 1500 1000 720.0 4000.0 3000 2000 1500 1000 720.0
cm-1 cm-1
Page 8Generation of Individual Ingredient Distributions
Once presence of all components is established, least squares
full spectrum curve fitting is used to generate individual
ingredient distributions
Each pixel spectrum is fitted to a linear combination of the raw
ingredient spectra
Care should be taken when strong cross-correlations exist
between raw ingredient spectra
MIR ATR raw ingredient spectra generally show low
correlations between individual ingredients
Individual ingredient images may be overlaid to generate
composite images….
Page 9Composite Image from 4 of the Major Components
Avicel
Starch
Calcium phosphate
Magnesium stearate
Page 10Least Squares Fitted Image for Microcrystalline Cellulose
Raw Ingredient
spectrum
Spectrum from
Image
Page 11Distribution for Magnesium Stearate
Raw Ingredient
spectrum
Spectrum from Image
Page 12ATR Particle Image Shapes – Comparison with SEM
Pure Microcrystalline Cellulose Calculated ATR Distribution
SEM Image In Tablet
Page 13Starch Granules more Spherical..
SEM ATR Image in Tablet
Calculated
Shadow
applied
Page 14Example 2. Over the Counter Analgesic Tablet
Main Ingredients Other Ingredients
Aspirin Lactose
Paracetamol Microcrystalline cellulose
Calcium carbonate
Caffeine
Various starches
Silicon dioxide
Citric acid
Example: 14 ingredients listed
Page 15NIR Imaging Reveals Coarse Structure
Diffuse reflectance
measurements
Major ingredient domains
identified
Typically over 100 microns
Fine detail/minor ingredients usually not ~2mm
reported
Page 16ATR Imaging Reveals Coarse and Finer Structure
~0.3mm
Pure ingredient
A
From Image
4000.0 2000 1000 720.0
cm-1
Aspirin
Page 17Overlaying Paracetamol Distribution
Pure ingredient
A
From Image
4000.0 2000 1000 720.0
cm-1
Paracetamol
Page 18Overlaying Microcrystalline Cellulose
Pure ingredient
A
From Image
4000.0 2000 1000 720.0
cm-1
Microcrystalline
cellulose
Page 19Revealing Minor Constituents – Calcium Carbonate
From Commercial
Library
A
From Image
4000.0 2000 1000 720.0
cm-1
Page 20Exploded view of Calcium Carbonate Image
~6 microns separation
(red vs blue)
Page 21Calcium carbonate ‘within’ the aspirin domains
Aspirin
Calcium carbonate
Page 22Use of Pixel Counting
Histograms of image intensities can help characterise images
more objectively
High contrast images contain 2 or more ‘modes’ in the
histogram
• Comparing pixel numbers between modes can provide
estimates of concentration in favorable situations
• Particle statistical analysis can work well with ATR.
Domains are quite discrete
– Particle diameter, area, circularity, nearest-neighbour
distances etc., can be related to quality attributes
Page 23Individual Ingredient Distributions as Histograms
Plot #pixels vs intensity
A clean, 2 component
distribution gives a bimodal
distribution (A and B)
Where is A-B cutoff?
A B
Page 24Use of Pixel Counting Techniques
Histogram representation can be a powerful tool to help
characterise images
Use of particle counting techniques is possible with derived
ATR images
Certain results can be sensitive to the thresholds applied to
produce the binary images – use with care!
Product quality attributes have been related to certain particle
size/distribution metrics
Page 25ATR Imaging Pharmaceutical Tablets
NIR Imaging excellent for revealing larger domains
Mid-IR ATR imaging shows much improved spatial resolution
and image fidelity
ATR imaging reveals distribution information which is difficult
if not impossible to obtain with current NIR technology
Many thanks to Dr. Jerry Sellors, providing data for this
presentation and the best knowledge in this field of work
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