Webinar: Case Studies in Foreign Particulate Analysis

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Case Studies in Foreign
Particulate Analysis
© Gateway Analytical, LLC, 2015
Welcome to Today's Webinar Presented by
Gateway Analytical
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Start Time: 2 pm am EDT (U.S & Canada)
Duration: 45 min. including Q&A time
Join Gateway Analytical scientists as they dive into best practice
methods for characterizing and identifying foreign particulate

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About Gateway Analytical
Located in Gibsonia, Pennsylvania, USA
Particulate
Identification Services
Detailed Report
Characterizing and
Identifying particulate
Customer Support to
help identity the source
of contaminates.
cGMP-compliant | FDA Registered & Inspected | ISO 17025 & ISO 9001

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About Gateway Analytical
Located in Gibsonia, Pennsylvania, USA
Particulate happens, but that
shouldn't stop your progress.
Our focus is to remove the
hurdles involved with identifying
foreign particulate and guide our
customers to fast remediation.

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Meet the Presenters
David Exline
Vice President
Gateway Analytical
exlined@gatewayanalytical.com
Julia Patterson
Scientist
Gateway Analytical
pattersonj@gatewayanalytical.com
Marina Parra
Scientist
Gateway Analytical
parram@gatewayanalytical.com

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Outline
• What is foreign particulate matter?
• Commonly found sources of particulate
contamination
• How manual analysis compares to automated
technologies
• Sample preparation
• Specialized foreign particulate testing methods
• Foreign particulate analysis methods and case
study examples

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Common Characteristics of Foreign
Particulate Matter
• Visible and sub-visible particles
• Stains and discoloration
• Often charred from sterilization processes
• Precipitated materials
• Typical in all process related manufacturing equipment
– Cleaning system
– CIP
– Protective Clothing
– Stainless steel tanks
– Filter systems
– Storage containment

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Why is Foreign Particulate Matter So
Common?
• Product constantly in contact with process
• Process of manufacturing has so many stages
• Chemical breakdown and aging
• Process precipitation
• Raw material contamination
• Containers and packaging
• Washing and storage process
• Customer site contamination
• Environment
• Sterile does not mean “particle free”

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Common Types of Foreign Particulate
Contaminations in Pharmaceutical
Manufacturing
 Stainless Steel
 Human/Animal Hairs
 Paint
 Glass
 Rubber (stoppers)
 Polymers
 Insects
 Silicone Products
 Teflon
 Synthetic Fibers
 Natural Fibers
 Labels
 Burned Material
 Paper products
 Metals
 Environment
• Often found during 100%
inspection process
• Mechanical Failure
Investigation
• Customer Return Samples
• Contamination studies of
processes
• Evaluation of raw
materials
• Foreign particulate can be
detected at any stage in
the manufacturing
process

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Pharmaceutical Forensics
• Application of forensic testing & problem solving methods
• Answer specific questions like:
– How, why and when did it break?
– What is this foreign material?
– Where did it come from?
• Typical Applications:
– Particle contamination / Source Determination
– Deviations from in process methods
– Product returns
– Foreign particulate matter identification
– Tablet non-conformance investigation
– Parenteral particulate characterization
• Visible and sub-visible
• 100% Particle inspection approach

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Overall Sample Flow for Manual or
Automated Analysis
Non-
Conformance
Issue
Sample
Collection/
Evaluation
Manual Analysis
SEM-EDS
FTIR
Raman
Optical/ PLM
Glass
Delamination
Automated
Analysis
CCSEM
SPE

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Manual vs. Automated
Manual Analysis
• Typically longer analysis time per
sample
• Better suited for a smaller
number of samples
• Can determine the size, shape,
and color of each individual
particle.
• Can determine both the
elemental composition of the
sample and spectral data
Automated Analysis
• Faster analysis
• Better suited for a larger number
of samples
• Can provide information on the
size bins of the particles in a
population
• Sometimes you will not obtain as
much data from each individual
particle: Elemental composition
OR spectral data

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Typical Sample Flow for
Manual Analysis
Sample Collection /
Evaluation
Physical Properties
Color, shape, texture
Optical Evaluation
Fiber, glass, paint, metal, organic,
inorganic
Sample
Isolation
Non-conformance
Issue
Organic
Analysis
FT-IR, Raman,
Chemistry,
Chromatography
Inorganic
Analysis
SEM/EDS, XRD, Inorganic
Chemistry
Identification of Foreign
Material
Comparison
Foreign material with
known
Evaluation
Source Determination

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Isolation of Particulate
Manual Analysis
• Initial collection
– Filtration of parenteral product
– Manual isolation
• Washing/ rinsing of samples
• Preparation for Analysis
– Microscopy preparations
– FTIR preparations
– SEM/EDS preparations
– Raman preparations

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Preparation of Filter
Manual Analysis

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Sample Collection / Isolation
Manual Analysis
• Isolation / cleaning of sample critical step
• Understand substrate conditions

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Particle Isolation – Analysis Substrates
Manual Analysis
Microscopy – Temporary
mount with glass slides
FTIR – Low-e slide Raman – Al Slide
SEM – Stub with carbon tape

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Preparation of Filter – Automated Raman
Automated Analysis
Gold Coated Polycarbonate Filter Filtration Preparation
• Low blanks
• Cleanroom manufactured
• System integrated
• High sensitivity
• No background signal for ID

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Microscopy – Key Techniques
Manual Analysis
• Size
• Morphology
• Consistency
• Color
• Documentation
• Unique features
• Organic vs. inorganic
• Comparison
• Optical properties
• Fluorescence properties

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Optical Microscopy
Manual Analysis
• Efficient method of particle characterization
• Cost effective
• Critical evaluation for particle comparison and differentiation
Optical and Polarized Light Microscopy
Fluorescence Microscopy

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Fourier Transform Infrared Spectrometry (FTIR)
Manual Analysis
• A microscope attachment is
usually required for precise
analysis
• Light can be passed through the
sample (transmission) or reflected
through the sample (reflectance)
• The interaction of the light with
the sample is interpreted as an
FTIR spectrum
100015002000250030003500
Wavenumber cm-1
0.20.40.60.81.01.21.41.6
AbsorbanceUnits
Polyethylene

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Raman Spectroscopy
Manual Analysis
• Generally a surface analysis
method
• Useful for:
– Embedded materials
– Pigments
– Oxides
– Amorphous Carbon
• Is a complementary
technique to FTIR analysis

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Manual SEM-EDS
Manual Analysis
• The analyst manually
drives the instrument to
perform the analysis.
• Useful for determining:
– Surface features of a
sample
– Elemental composition
of the sample
• Can visualize and
analyze different areas
of a heterogeneous
sample
500 µm 100 µm
keV
14121086420
Counts
2,500
2,000
1,500
1,000
500
0
CO
Fe
Fe
Fe

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Automated CCSEM
Automated Analysis
• The analyst inputs an
area and analysis
criteria for the
instrument to scan and
analyze.
• Useful for determining:
– Elemental
composition
– Size
for a population of
particles

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Glass Delamination
Specialized Analysis
What is Glass Delamination?
• Small, thin, glass fragments,
termed “glass lamellae”,
which are shed from the
interior portion of glass
containers and vials
• Glass lamellae are shed into,
and suspended in the liquid
drug contained in the glass
vial
• Detection of glass lamellae
can be very difficult during
visual product inspections
High resolution SEM imaging analysis
identifying regions on the interior vial surface
which show indications of pitting and
delamination

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Why Does Glass Delamination Occur?
Specialized Analysis
• Glass delamination is
an effect of glass
corrosion
• Glass corrosion can
occur in silicate
glasses through
three types of
chemical reactions:
– Acidic (H3O+)
– Basic (OH-)
– Neutral (H2O)
keV
109876543210
Counts
6,000
4,000
2,000
0
C
O
Na
Al
Si
Automated SEM-
EDS analysis
identifying Si-rich
particles which are
elementally and
morphologically
consistent with
delamination

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Screening Studies per USP General
Chapter <1660>
PARAMETER TEST PARAMETER ANALYTICAL METHODS
Glass surface
• Degree of surface pitting
• Chemical composition as
a function of depth
• DIC Microscopy or EM
• SIMS
Extracted elements in
solution
• Conductivity/pH
• Individual and total
extractables
• SiO2 concentration
• SiO2/B2O3 or Si/Al
ratio
• Conductivity/ pH meter
• ICP-MS or ICP-OES
Visible/ Subvisible glass
particles
• Particle number and size
• Particle morphology and
composition
• Particle size analyzer
• SEM-EDS

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Specialized Analysis - Automated Raman
Spectroscopy Overview

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How Does Combined Raman/LIBS Compare
to Other Technologies?
Method
Sizing and
counting
Elemental Chemical Automation Specific
Level of
expertise
Cost Speed
Optical
Microscopy
Yes No No Possible No High Low Slow
HIAC Yes No No Yes No Low Low Fast
Manual
Raman
No No Yes Possible Yes High Middle Fast
Automated
Raman
Yes No Yes Yes Yes High Middle Fast
FTIR No No Yes Possible Yes High Middle Fast
SEM-EDS Yes Yes No Possible Yes Middle High Fast
Automated
LIBS
YEs Yes Yes Yes Moderate High High Fast

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Overall Filter Montage
Automated Raman Spectroscopy

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Database Search of Selected Particles
Automated Raman Spectroscopy
Raman Database Search Consistent with Plunger Material

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Particle Size and Identification Using SPE™
Automated Raman System
Spectra # Material
Size Distribution [µm]
2 - 10 10 - 25 25 - 50 50 - 100 100-1000 Totals
1 Amorphous Carbon 7 0 0 0 0 7
2 beta-Carotene 1 0 0 0 0 1
3 Blue Pigment 28 3 2 4 2 39
4 Boot cover 0 0 0 1 0 1
5 Boron Carbide 1 1 1 6 3 12
6 Calcium Chloride 1 0 0 0 0 1
7 Cellulose 1 0 0 1 0 2
10 storage bag 0 0 1 1 0 2
11 Filling suite, Ext 12 2 0 3 0 17
12 Filter from air line 0 0 0 0 1 1
13 Fluorescence 175 24 26 74 28 327
17 Gowning material 1 0 0 3 0 4
18 Plunger 0 1 6 26 10 43
20 Laurylsulfate Sodium, SDS 0 0 0 1 0 1
21 Nitrate Sodium 0 0 0 2 0 2
25 Plastic bags 0 0 0 1 0 1
26 Poly(acrylonitrile) 4 2 0 1 1 8
28 Polycarbonate 2 0 0 0 0 2
30 Polysulfone 1 0 0 0 0 1
31 Porous Particle Production Air 7 0 0 0 0 7
32 Sample 1 1 0 0 0 0 1
33 Sample 5 0 0 0 1 0 1
37 Smalt 1 0 0 0 0 1
38 Starch 1 0 0 1 0 2
40 Talcum 8 3 0 1 0 12
41 Titanium(IV)oxide, Anatase 2 0 0 1 0 3
42 gasket 0 0 1 0 0 1
All Particles 10,260 1548 460 128 45 12,441

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Looking at Unknown Clear Particles
Internal Case Study

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A Common Problem
• Clear particles are a common
form of particulate
contamination
• They can be anything from glass
to polymers, to cellulose, or
crystalized drug product
• Optical analysis can give you
some idea of what the particle is
however, further analysis is
often required
• Additional analysis can include:
– SEM
– PLM
– FTIR
– Raman

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Unknown Particle - Optical Image
Unknown particle
recovered from
membrane filter
Optical Image

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500 µm
keV
109876543210
Counts
12,000
10,000
8,000
6,000
4,000
2,000
0
C
O Al
1000 µm
filename=040215_CI-1111_A_mp_01.tif
SEM/EDS & FTIR of Clear Particulate
SEM / EDS Spectra
Y:Project_FoldersPractice ProjectsLS-15-0101FTIR040215_CI-1111_A_mp_01.1 040215_CI-1111_A_mp_01 4/2/2015
100015002000250030003500
Wavenumber cm-1
0.20.40.60.81.01.21.4
AbsorbanceUnits
Page 1/1
You can tell its not glass because it is carbon rich instead of silicon rich
FTIR Infrared Spectra

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Imbedded Foreign Particulate in Vial
Case Study

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Case Study: The Problem
• A drug developer had an issue
with vials that were flagged
during a visual inspection.
• They identified several vials
with a black and brown
material visible on the side of
the glass wall.
• The unknown contaminate
could not be reach for
extraction due to its location in
the vial.

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Case Study: The Solution
• Vials were sent to
Gateway Analytical for
extraction and analysis
• Vial was broken to expose
the unknown material
• Material was found to be
embedded in the vial wall
• Preformed SEM and
Raman on the material as
it could not be isolated
from the glass vial wall.

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Case Study: Iron Oxide Embedded
in Glass Vial

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Case Study: Iron Oxides (i.e. Rust)
Iron oxide particulates may be present in glass vial mold materials
50 µm
keV
109876543210
Counts
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
C
O
Na Al
Si
Fe
Fe
Fe
200 µm
filename = 062215_CI-8167_amf_01.TIF
Y:Project_FoldersLS-15-0416Raman062215_CI-8167_amf_01.0 062215_CI-8167_AMF_01 UNDEFINED 6/22/2015
200 400 600 800 1000 1200 1400
Wavenumber cm-1
1000200030004000
RamanIntensity
Page 1/1

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Hair Discovered in Manufacturing
Process
Case Study

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Hair Examination – Value
High resistance to degradation
Each species has characteristic color, length, shape, root
appearance, and internal characteristics
Human Hair
Racial Origin
Body area
Disease
Natural Vs. Forcibly Removed
Cosmetic Treatment
Environmental Factors
Comparison
mtDNA or nuclear DNA
Animal Hair
Species of Origin
Dyeing Methods
Possible Sources
Forensic Hair Comparisons required to associate source

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Case Study: The Problem
• Customer found a hair
in their manufacturing
process
• They were able to
isolate it with forceps
and package it between
two glass slides in order
to send it out for
analysis.

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Case Study: The Solution
• Gateway Analytical
utilized PLM analysis
to
– Confirm that the
sample was a hair
– Determine the species
of the hair (human or
animal)

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Case Study: PLM Analysis – Canine Hair
1. Spade shaped root 2. Wide, amorphous medulla
3. Physical damage – splitting 4. Narrow, tapered distal end

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It’s Time for the Q&A Session.
Please Submit Your Questions!

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Contact Us & Follow-up
Get Insights from our Blog:
www.gatewayanalytical.com/blog
Contact Information
David Exline
Vice President
Gateway Analytical
exlined@gatewaya
nalytical.com
Julia Patterson
Scientist
Gateway Analytical
pattersonj@gatew
ayanalytical.com
Marina Parra
Scientist
Gateway Analytical
parram@gatewaya
nalytical.com
Brittney Norris
Marketing &
Creative Director
Gateway Analytical
norrisb@gatewaya
nalytical.com
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For Attending
Today’s Webinar!
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Webinar: Case Studies in Foreign Particulate Analysis

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