volume 32 number 2, 77–160 volume 32 number 2 february...
TRANSCRIPT
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The Future of Miniature Mass Spectrometers
Chromatographic Modeling for LC Method Development in a
Quality-by-Design Framework
Pesticide Analysis in Fruits and Vegetables
Using QuEChERS, GC–MS, and LC–MS
The Role of Selectivity in Extractions
Volume 32 Number 2 February 2014www.chromatographyonline.com
Triazole Bonded Stationary Phase
Alternative Selectivity for HILIC Analysis
www.nacalaiusa.com
COSMOSIL HILIC
Column size: 4.6mmI.D. 250mm
Mobile phase: Acetonitrile/50mmol/l CH3COONH4 = 80/20
Flow rate: 1.0ml/min Temperature: 30
Detection: ELSD
Sample: 1. meso-Erythritol (1.0mg/ml)
2. Tris (1.0mg/ml)
3. Glyceric Acid (2.0mg/ml) Injection Vol: 3.0μl 1. meso-Erythritol
Neutral2. TrisBasic
3. Glyceric Acid Acidic
COSMOSIL HILIC TSKgel Amide-80(Basic/Neutral)=1. 48,
(Acidic/Neutral)=4.36(Basic/Neutral)=3.07,
(Acidic/Neutral)=2.04
Atlantis HILICZIC-HILIC(Basic/Neutral)=4.45,
(Acidic/Neutral)=1.71(Basic/Neutral)=5.03,
(Acidic/Neutral)=1.47
COSMOSIL HILIC HPLC ColumnThe positively charged triazole bonded stationary phase
provides alternative selectivity to other HILIC columns.
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The Future of Miniature Mass Spectrometers
Chromatographic Modeling for LC Method Development in a
Quality-by-Design Framework
Pesticide Analysis in Fruits and Vegetables
Using QuEChERS, GC–MS, and LC–MS
The Role of Selectivity in Extractions
Volume 32 Number 2 February 2014www.chromatographyonline.com
Confi dence means a return on investment that includes quality results, time
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Used under license from Shutterstock.com
Polymer HPLC columns have a lot of benefi ts. They don’t require
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80 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
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CONTENTS
The Future of Miniature Mass Spectrometers
Chromatographic Modeling for LC Method Development in a
Quality-by-Design Framework
Pesticide Analysis in Fruits and Vegetables
Using QuEChERS, GC–MS, and LC–MS
The Role of Selectivity in Extractions
Volume 32 Number 2 February 2014www.chromatographyonline.com
®
LCGC North America (ISSN 1527-5949 print) (ISSN 1939-1889 digital) is published monthly with 1 additional issue in August as Buyers Guide by Advanstar Communica-tions Inc., 131 West First Street, Duluth, MN 55802-2065, and is distributed free of charge to users and specifiers of chromatographic equipment in the United States and Canada. Single copies (prepaid only, including postage and handling): $15.50 in the United States, $17.50 in all other countries; back issues: $23 in the United States, $27 in all other countries. LCGC is available on a paid subscription basis to nonqualified readers in the United States and its possessions at the rate of: 1 year (13 issues), $74.95; 2 years (26 issues), $134.50; in Canada and Mexico: 1 year (13 issues), $95; 2 years (26 issues), $150; in all other countries: 1 year (13 issues), $140; 2 years (26 issues), $250. Periodicals postage paid at Duluth, MN 55806 and at additional mailing offices. POSTMASTER: Please send address changes to LCGC, P.O. Box 6168, Duluth, MN 55806-6168. PUBLICATIONS MAIL AGREEMENT NO. 40612608, Return Undeliverable Canadian Addresses to: IMEX Global Solutions, P. O. Box 25542, London, ON N6C 6B2, CANADA Canadian GST number: R-124213133RT001. Printed in the USA.
COLUMNS
92 SAMPLE PREP PERSPECTIVESThe Role of Selectivity in Extractions: A Case Study
Douglas E. RaynieThe selective removal of a fat substitute in food products is discussed to demonstrate options for obtaining selectivity during extraction.
98 LC TROUBLESHOOTINGLC Method Scaling, Part I: Isocratic Separations
John W. DolanWhat kind of adjustments need to be made when scaling an isocratic method?
104 MS – THE PRACTICAL ARTThe Future of Miniature Mass Spectrometers and a Path
Forward: A Few Thoughts from an Academic Researcher
Zheng OuyangA discussion of the future role of miniature MS systems, the need for simplification in operation, the role of ambient ioniza-tion, and challenges in development and commercialization.
158 THE ESSENTIALSTroubleshooting Real GC Problems
Key considerations for setting up or troubleshooting a GC method.
PEER-REVIEWED ARTICLES
116 Significant Improvements in Pesticide Residue
Analysis in Food Using the QuEChERS Method
Walter J. Krol, Brian D. Eitzer, Terri Arsenault, Mary Jane Incorvia Mattina, and Jason C. WhiteThe analysis of pesticide residues in food samples from the state of Connecticut’s regulatory monitoring pro-gram are compared to USDA and US FDA results.
126 Rapid UHPLC Method Development for Omeprazole
Analysis in a Quality-by-Design Framework and
Transfer to HPLC Using Chromatographic Modeling
Alexander H. Schmidt and Mijo StanicQuality-by-design principles are applied to build in a more scien-tific and risk-based multifactorial strategy in the development of a UHPLC method for analyzing a drug and its related impurities.
ON THE WEBWEB SEMINARS
Editors’ Series: Analytical Tools for the Characterization of Bio-pharmaceuticals: Part 1, Chromatographic Methods Davy Guillarme, University of Geneva and University of Lausanne
Editors’ Series: Analytical Tools for the Characterization of Bio-pharmaceuticals: Part II, Mass Spectrometry Detection Sarah Cianférani, University of Strasbourg
Multi-Antibiotic Residue Detection in Food: An Improved Method for Screening and Confirmation Testing, in Accordance with EU Commission Decision 2002/657/ECNelli Jochim, Eurofins WEJ Contaminants
chromatographyonline.com/WebSeminar.
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DEPARTMENTSPeaks of Interest . . . . . 90 Product Showcase . . .149 Ad Index . . . . . . . . . . . 156
v����� 32 n����� 2 february 2014
Cover photography by Joe Zugcic, Joe Zugcic Photography
Cover materials courtesy of Perkin- Elmer and Restek Corporation
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before. Now imagine all this happening at the push of a button. This goes far beyond the power of mass detection.
This is the ACQUITY QDa™ Detector from Waters. SEPARATING BEYOND QUESTION.™ Visit waters.com/separate
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86 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
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Publishing & Sales
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88 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
Kevin D. Altria GlaxoSmithKline, Ware, United Kingdom
Jared L. Anderson The University of Toledo, Toledo, Ohio
Daniel W. Armstrong University of Texas, Arlington, Texas
Michael P. Balogh Waters Corp., Milford, Massachusetts
Brian A. Bidlingmeyer Agilent Technologies, Wilmington, Delaware
Dennis D. Blevins Agilent Technologies, Wilmington, Delaware
Peter Carr Department of Chemistry, University
of Minnesota, Minneapolis, Minnesota
Jean-Pierre Chervet Antec Leyden, Zoeterwoude, The Netherlands
John W. Dolan LC Resources, Walnut Creek, California
Michael W. Dong Genentech, San Francisco, California
Roy Eksteen Sigma-Aldrich/Supelco, Bellefonte, Pennsylvania
Anthony F. Fell School of Pharmacy, University of
Bradford, Bradford, United Kingdom
Francesco Gasparrini Dipartimento di Studi di Chimica e Tecnologia delle
Sostanze Biologicamente Attive, Università “La Sapienza,” Rome, Italy
Joseph L. Glajch Momenta Pharmaceuticals, Cambridge, Massachusetts
Davy Guillarme University of Geneva, University
of Lausanne, Geneva, Switzerland
Richard Hartwick PharmAssist Analytical Laboratory,
Inc., South New Berlin, New York
Milton T.W. Hearn Center for Bioprocess Technology,
Monash University, Clayton, Victoria, Australia
Emily Hilder University of Tasmania, Hobart, Tasmania, Australia
John V. Hinshaw BPL Global, Ltd., Hillsboro, Oregon
Kiyokatsu Jinno School of Materials Science, Toyohashi
University of Technology, Toyohashi, Japan
Ira S. Krull Northeastern University, Boston, Massachusetts
Ronald E. Majors LCGC columnist and analytical
consultant, West Chester, Pennsylvania
R.D. McDowall McDowall Consulting, Bromley, United Kingdom
Michael D. McGinley Phenomenex, Inc., Torrance, California
Victoria A. McGuffin Department of Chemistry, Michigan
State University, East Lansing, Michigan
Mary Ellen McNally E.I. du Pont de Nemours
& Co., Wilmington, Delaware
Imre Molnár Molnar Research Institute, Berlin, Germany
Glenn I. Ouchi Brego Research, San Jose, California
Colin Poole Department of Chemistry, Wayne
State University, Detroit, Michigan
Fred E. Regnier Department of Chemistry, Purdue
University, West Lafayette, Indiana
Pat Sandra Research Institute for Chromatography, Kortrijk, Belgium
Peter Schoenmakers Department of Chemical Engineering,
University of Amsterdam, Amsterdam, The Netherlands
Kevin Schug University of Texas, Arlington, Texas
Dwight Stoll Gustavus Adolphus College, St. Peter, Minnesota
Michael E. Swartz Ariad Pharmaceuticals, Cambridge, Massachusetts
Thomas Wheat Waters Corporation, Milford, Massachusetts
CONSULTING EDITORS: Jason Anspach, Phenomenex, Inc.; Stuart Cram,
Thermo Fisher Scientific; David Henderson, Trinity College; Tom Jupille, LC
Resources; Sam Margolis, The National Institute of Standards and Technology;
Joy R. Miksic, Bioanalytical Solutions LLC; Frank Yang, Micro-Tech Scientific.
Editorial Advisory Board
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90 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
PEAKS of Interest
National Institute of Standards
and Technology Makes Polycyclic
Aromatic Hydrocarbon Structure
Index Publicly Available
The National Institute of Standards
and Technology (NIST), an agency of
the U.S. Department of Commerce,
has made a polycyclic aromatic hydro-
carbon (PAH) structure index data-
base publicly available on-line
(http://pah.nist.gov/). A by-product of
hydrocarbon fuel combustion, PAHs
can have significant adverse health
and environmental impacts. The web-
site contains data on more than 650
PAH compounds, with more to be
added in the future.
According to NIST, the Chemical
Informatics Research Group of NIST’s
Material Measurement Laboratory
created the site to provide standard
reference data to industry, academia,
and the US public, and builds on
NIST Special Publication 922: Polycy-
clic Aromatic Hydrocarbon Structure
Index (SP922) by Lane C. Sander and
Stephen A. Wise of NIST. Publication
SP922 indexed a large number of PAH
structures and provided parameters
for estimating retention indices for
liquid chromatography using a simple
model. The new database expands on
this by providing data from further
experimental data including a collec-
tion of thermochemical data on gas-
phase PAH compounds, and UV–vis-
ible spectra.
Duke Molecular Physiology
Institute Receives Agilent Grant
Agilent Technologies (Santa Clara,
California) has awarded a grant to
the Duke Molecular Physiology Insti-
tute, Duke University (Durham, North
Carolina) to support research into the
metabolic and physiological aspects
of major chronic diseases such as
cardiovascular disease. The institute
researchers perform a range of ana-
lytical chemistry techniques, including
liquid chromatography and gas chro-
matography coupled to mass spec-
trometry, to characterize molecular
pathways in disease.
The group is headed by Christopher
Newgard, a professor at Duke Uni-
versity School of Medicine’s Depart-
ment of Pharmacology and Cancer
Biology and director of the Sarah W.
Stedman Nutrition and Metabolism
Center and the Institute for
Molecular Physiology.
“The Duke Molecular Physiology
Institute seeks to combine strong
genomics, epigenomics, transcrip-
tomics, and metabolomics platforms
with computational biology, clinical
translation, and basic science exper-
tise to gain new insights into the
mechanisms of cardiometabolic dis-
ease,“ Newgard said, adding “We
thank Agilent for supporting our
research and look forward to collabo-
rating to advance the understanding
of cardiovascular and undiagnosed
metabolic diseases.” ◾
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92 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
SAMPLE PREP PERSPECTIVES
Many of the extraction
techniques developed over
the past generation tout
selectivity among their
advantages. In reality,
solvent selection and the
use of stationary (sorbent)
phases are the main
mechanisms for providing
selectivity. Therefore,
selectivity is often limited
to isolation of classes of
compounds rather than
individual structures. In
this column installment,
the selective removal of
a fat substitute in food
products is discussed
to demonstrate options
for obtaining selectivity
during extraction.
Douglas E. Raynieis the guest author
of this installment.
Ronald E. Majorsis the editor of Sample
Prep Perspectives.
Over the past generation or so,
myriad extraction techniques were
developed that have generally
improved yields, lessened the amount of
organic solvent used, and minimized time.
Additionally, many of these techniques
claim advantages concerning selectivity.
Selectivity is the ability to determine
the analytes of interest in preference
to other sample components (potential
interferents). A recent installment of
this column (1) advocated that selec-
tivity can stem from any point in the
analytical process, but as a general rule,
selectivity arises from separations, selec-
tive detection schemes, and selective
chemical reactions. These approaches
can balance each other. For example, if
an analytical separation is not completely
sufficient, the use of a selective detection
method like mass spectrometry (MS) or
fluorescence spectroscopy can offer the
balance of the required selectivity pro-
vided that the unseparated components
do not suppress the detector signal.
Majors described “just enough” sample
preparation (2) in which method selectivity
is matched to the qualitative or quantitative
analytical requirements. For example, the
QuEChERS (quick, easy, cheap, effective,
rugged, and safe) method for extract-
ing pesticides from fruits and vegetables
combines salting out partitioning with
dispersive solid-phase extraction (SPE)
to remove matrix components, allowing
effective chromatography and MS detec-
tion. As Majors points out and illustrates
in Figure 1 from his original column,
increasing complexity in an analytical pro-
cedure typically leads to greater selectivity.
Turning our attention back to modern
extraction methods, the fundamental
driving force of the technique leads to
the element of selectivity. A number of
sorbent-based methods, such as SPE,
solid-phase microextraction, and stir-bar
sorbent extraction, use chromatographic
stationary phases to isolate solutes of
interest from gaseous or liquid samples.
Analytes are retained by their attraction
to a stationary phase of similar polarity
and are selectively eluted via choice of an
appropriate solvent. The techniques aimed
at solid samples, including supercritical
fluid extraction (SFE), pressurized fluid
extraction, microwave extraction, and
ultrasound extraction, rely on the applica-
tion of energy (often heat) to drive the
analyte into an appropriate solvent. In all
of these techniques, both sorbent- and
solvent-based, the key to selectivity is
the match between analyte polarity and
polarity of the extracting phase. In other
words, “like dissolves like.” Thus, extrac-
tions are usually considered crude separa-
tion techniques, providing compound class
selectivity and less utility for the selective
isolation of specific, individual compounds.
Of course, volatility is the major contribu-
tor to selectivity for gas-phase techniques.
If the primary selectivity mechanism
in extractions is solute polarity (that is,
matching solute polarity with the solvent
or sorbent following the “like dissolves
like” principle), is selectivity possible dur-
ing chemical extraction? Is selectivity
beyond compound class selectivity pos-
sible? Do extractions need to be selective
or is selectivity solely a function of subse-
quent chromatography and detection?
To look at an example of extraction
selectivity within the “like dissolves
like” polarity context, let’s consider
the example of fat analysis in food
products and, more specifically, the
example of sucrose ester fat substitutes.
Fatty Acid Methyl Ester Analysis
The United States Nutrition Labeling and
Education Act (NLEA) of 1990 requires
The Role of Selectivity in
Extractions: A Case Study
94 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
the labeling of selected nutrients on pre-
packaged food products. One issue with
this requirement deals with the concept
of “total fat.” What is a “fat”? Are lipo-
proteins considered lipid or protein? The
next concern is their analysis. If “fats” are
based on the fatty acid moiety, how can
they be measured? Fatty acids are not
volatile enough for gas chromatography
(GC) analysis. They do not contain any
chromophores necessary for ultraviolet
detection in liquid chromatography
(LC). (Remember, at the time, LC–MS
was not as widely accepted as it is cur-
rently.) The polarity of the acidic group
can irreversibly adsorb to active sites on
chromatographic stationary phases via
hydrogen bonding, depending on the
type of chromatography. Consequently,
the total fat listed on nutritional labels
is based on the acid hydrolysis and for-
mation of methyl esters of an organic
extract, using a nonpolar solvent, of the
food product. The “total fat” listed on the
nutritional label is that of a triglyceride
based on the resulting fatty acid methyl
ester (FAME) composition (3,4). An
overview of the formation of methyl esters
from triglycerides is presented in Figure 2.
In the FAME method, samples are dis-
solved in a nonpolar solvent and a catalyst
like BF3 dissolved in methanol is added.
Sometimes methanolic acid or base is used.
After mild heating, back-extraction with
water removes the polar components. The
FAME sample is dried and characterized
by GC with flame ionization detection
(FID). The esterification is facilitated
with an alkylation derivatizing agent to
condense the carboxyl group of the fatty
acid with the methanol hydroxyl. The
catalyst aids the reaction by protonating
the acid group to promote the formation
of the ester and water. The stability of the
methyl ester, or FAME, allows GC separa-
tion by boiling point or unsaturation.
The Procter and Gamble Company
began marketing sucrose esters, called
olestra or the tradename Olean, as fat sub-
stitutes in the mid-1990s. The sucrose ester
structure is shown in Figure 3. In this fig-
ure, the R group is either hydrogen or any
fatty acid. By varying the number of fatty
acids connected to the sucrose molecule by
ester linkages or by changing the carbon
chain length of the fatty acids, the proper-
ties of the olestra molecule can be altered.
Under appropriate conditions, the olestra
molecule can have boiling points, viscosity,
mouth feel, and other properties similar
to common vegetable oils. Because they
are not naturally occurring lipids (though
they are made from naturally occurring
compounds), the sucrose esters are not sub-
ject to enzymatic digestive action. Hence,
they can be substituted for vegetable oils
in selected applications, such as the frying
of potato chips and similar salted snacks.
If we review the acid hydrolysis and
esterification reactions for the FAME
analysis, olestra in food products would
be hydrolyzed along with triglycerides
and other fats. The resulting FAMEs
would be indistinguishable regarding
their source, olestra or triglyceride. Thus,
a selective analysis to determine NLEA
“total fats” in the presence of olestra is
needed. Here we will present three pos-
sibilities to garner the necessary selectivity
during the sample preparation process.
Supercritical Fluid Extraction
Perhaps the easiest method, conceptu-
ally, to address the isolation of FAME
from total fats from those originating
from olestra would be at the level of the
extraction, meaning we would selectively
extract olestra from the total fats. (That
is, we’re assuming that we must perform
FAME analysis of total fats to comply
with the requirements of the NLEA.)
This brings us back to the issue of solvent
polarity or “like dissolves like.” Because
olestra is designed to have properties sub-
stantially similar to vegetable oils, which
are composed primarily of triglycerides,
the solvents used in the dissolution and
extraction of either olestra or triglycerides
would likely be very similar. This brings
us to the solvent extraction method where
we have the most variation in solubility
conditions with a single solvent: SFE.
SFE almost always uses carbon dioxide,
perhaps mixed with small amounts of
Methodology
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Figure 1: Just-enough sample preparation represents a continuum of methodologies.
Figure 2: Triglycerides are hydrolyzed and esterified with methanol to form FAME. The R groups of the triglyceride are typically fatty acids with a carbon chain length of 14–24 and up to two double bonds.
96 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
organic cosolvents, near or above its criti-
cal point of 31.1 °C and 72.9 atm. Lipids
and lipophilic materials are highly soluble
in supercritical carbon dioxide, and the
use of this solvent for the extraction and
fractionation of lipids is well-reviewed
(5–7). By making subtle changes in the
operating temperature or pressure, some-
what dramatic changes in solvating ability
can occur. These changes may allow the
fractionation of members of a single com-
pound class on the basis of either polarity
or molecular weight. Because the molecu-
lar weights of olestra molecules are at least
double that of triglycerides, it is conceiv-
able that SFE could be used to either
selectively extract olestra and triglycerides
from each other, or to selectively precipi-
tate one from the other. This has not been
reported in the peer-reviewed literature, so
will remain theoretical for now. No other
solvent extraction methods will be able to
achieve this level of selectivity as easily.
Solid-Phase Extraction
The next step up in complexity toward
gaining the requisite selectivity during the
sample preparation of olestra-containing
food products would be to use a sorbent-
based method to separate olestra from
total fats postextraction. SPE is the most
basic of these techniques and perhaps the
most directly applicable to our hypotheti-
cal scenario. SPE can, in many ways, be
regarded as an elementary form of LC. A
stationary phase is placed onto a support
material and put into a cartridge, disk, or
other vehicle. Liquid samples are placed
onto the SPE sorbent where total retention
is achieved. Then analytes and interfer-
ents are isolated from each other by the
judicious elution with selective solvents.
Tallmadge and Lin (8) used reversed-
phase LC to determine the percent
olestra in lipid samples. They found an
octadecylsilane column (Zorbax, Agilent
Technologies) appropriate to separate
olestra from other lipophilic sample com-
ponents in samples of soybean-oil olestra
and heated or unheated cottonseed-oil
olestra in soybean oil. The percentage
of olestra in these samples varied from
5% to 90% and relative recoveries of
99.2% to 106.0% were reported. Thus,
it seems possible that with minimal
additional method development a pro-
tocol could be developed that involves
an extraction of total fats and olestra
from the sample food product, SPE
separation of olestra from the total fats,
and FAME analysis of the total fats.
Lipase Hydrolysis
Simultaneously, perhaps the most obvious
and the most direct means of address-
ing the proposed situation is to explore
the fundamental chemistry behind the
problem. Again, olestra is created by esteri-
fication of sucrose with fatty acids, but
because it lacks the glycerol backbone, it is
not subject to enzymatic digestion as are
triglycerides. Can this resistance to diges-
tion be exploited in the conversion of total
fats to FAMEs to the exclusion of olestra?
This is the approach taken in a method
validated under the Association of Official
Analytical Chemists (AOAC) Peer-Verified
Methods Program (9). A modified version
of AOAC Method 983.2.3 was used, in
which a chloroform–methanol extraction
of olestra-containing snacks was performed.
This extract contained both the total fat
and olestra. The hydrolysis portion of the
FAME analysis used a lipase to hydrolyze
the total fats, leaving the unaltered olestra.
The fatty acids resulting from the lipase
hydrolysis were precipitated as calcium
salts and the olestra was extracted with
hexane. The fatty acid salts were redis-
solved and esterified before GC analysis.
Recoveries of 101% (6% relative standard
deviation [RSD]) for total fat and 104%
(6% RSD) for saturated fat were reported.
Repeatability and reproducibility were also
studied and the method was standardized
for fatty acid carbon chains of 6–24. This
Figure 3: Structure of sucrose ester (oles-tra) fat substitutes created from sucrose esterified with six to eight fatty acids.
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FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 97www.chromatographyonline.com
represents the official method for the deter-
mination of total fats in packaged food
products containing olestra fat substitute.
Summary
Analytical selectivity can occur during
any step of an analytical method, but
typically it occurs during the separation or
detection steps rather than during sample
preparation. Selectivity during chemical
(analytical) extractions is almost exclusively
limited to solute polarity. Consequently,
selective extractions beyond compound
class separations will be difficult. Although
selective sample preparation is not the
typical case, increasing complexity of the
procedures can lead to selective analy-
sis. This column installment presented a
scenario in which selectivity during the
characterization procedure was not pos-
sible, but selectivity during solvent extrac-
tion (SFE) and sorbent-based extraction
(SPE) or via selective reactions was shown.
References
(1) R. Majors and D. Turner, LCGC North Am.
30(2), 100–110 (2012).
(2) R. Majors, LCGC North Am. 30(12), 1024–
1031 (2012).
(3) AOCS Method Ce 1-62, “Fatty Acid Composi-
tion by Gas Chromatography,” American Oil
Chemists Society Official Methods (2005).
(4) AOAC Method 996.06, “Fat (Total, Saturated,
and Unsaturated) in Foods,” 18th edition
Association of Official Analytical Chemists
Methods.
(5) J. Martinez and A.C. deAguiar, Curr. Anal.
Chem. 10, 67–77 (2014).
(6) F. Sahena, I.S.M. Zaidul, S. Jinap, A.A. Karim,
K.A. Abbas, N.A.N. Norulaini, and A.K.M.
Omar, J. Food Eng. 95, 240–253 (2009).
(7) F. Temelli, J. Supercrit. Fluids 47, 583 (2009).
(8) D.H. Tallmadge and P.Y. Lin, J. AOAC Intl. 76,
1396–1400 (1993).
(9) D. Schul, D. Tallmadge, D. Burress, D. Ewald,
B. Berger, and D. Henry, J. AOAC Intl. 81,
848–849 (1998).
Douglas Raynieis an Associate Research Professor at South Dakota State University. His research interests include green chemis-try, alternative solvents, sample preparation, high resolution chromatogra-phy, and bioprocessing in supercritical fluids. He earned his PhD in 1990 at Brigham Young University under the direction of Milton L. Lee.
Ronald E. Majors“Sample Prep Perspec-tives” Editor Ronald E. Majors is an analyti-cal consultant and is a member of LCGC’s editorial advisory board. Direct correspondence about this column to
“Sample Prep Perspectives,” LCGC, Woodbridge Corporate Plaza, 485 Route 1 South, Building F, Suite 210, Iselin, NJ 08830, e-mail [email protected].
For more information on this topic,
please visit
www.chromatographyonline.com/majors
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98 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
LC TROUBLESHOOTING
What kind of adjustments
need to be made when
scaling an isocratic method?
LC Method Scaling, Part I:
Isocratic Separations
John W. DolanLC Troubleshooting Editor
Today we are often confronted with
many different types of liquid chro-
matography (LC) methods. These
may use conventional 250 or 150 mm ×
4.6 mm, 150 mm × 2.1 mm, 50 mm ×
2.1 mm, and many other column con-
figurations packed with particles generally
ranging from <2 μm to 5 μm, and some-
times even 10 μm in diameter. One of the
challenges this variety presents is transfer-
ring a method from one column configu-
ration to another and still obtaining the
same resulting separation. For example,
you may use an ultrahigh-pressure LC
(UHPLC) system to develop methods
quickly in your research and development
(R&D) laboratory, but want to transfer it
to a conventional LC system for routine
use. Or your conventional method with
ultraviolet detection (LC–UV) may need
to be transferred to an LC system with
mass spectrometry detection (LC–MS).
Alternatively, you may want to adjust a
pharmacopeial method to use a different
column configuration. In many of these
cases, the method must be moved from
one column size to another, yet maintain
the same separation. The conversion is
not difficult, but you do have to be care-
ful to make the appropriate adjustments.
Isocratic separations, in which the mobile-
phase concentration is constant, are sim-
pler to convert than gradient methods,
where special care has to be taken to avoid
inadvertent chromatographic changes.
This month’s “LC Troubleshooting” dis-
cussion focuses on isocratic separations,
and next month we’ll look at gradients.
Resolution Is the Key
Equivalent separations require that the
resolution stays the same when conditions
are changed. In the method development
classes we teach, we use what is often
referred to as the “fundamental resolu-
tion equation” as a guide for the method
development process. We can use this
same equation to guide us in method
conversion:
Rs = ¼N 0.5(α – 1)(k/[1+k]) [1]
where Rs is resolution, N is the column
plate number, α is the separation factor,
and k is the retention factor. The first
caveat is that the chemistry of the system
cannot change when a change in the col-
umn or other conditions changes. This
means that the mobile phase must remain
the same, as well as the column tempera-
ture and column chemistry. With today’s
columns, it usually is valid to assume that
the same brand name description of a col-
umn (for example, ACE C18 [Advanced
Chromatography Technologies Ltd.) will
have the same column chemistry, no mat-
ter what the particle size is (2, 3, 5 μm,
and so forth). You’ll recall that the reten-
tion factor is defined as:
k = (tR – t0)/t0 [2]
where tR is the retention time of a solute
and t0 is the column dead time (retention
time of an unretained peak). If we keep
the chemistry of the system constant, the
retention time relative to the dead time
should stay constant, so k will remain
unchanged. Any change in retention
because of a change in column length,
diameter, or flow rate will have a propor-
tional change for tR and t0, so k will stay
constant in this case as well. For example,
doubling the flow rate will halve tR and t0,
and k will be unchanged.
The separation factor α is simply the
ratio of k values for two adjacent peaks, k1
and k2:
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100 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
α = k2/k1 [3]
So if we keep k constant, as discussed
above, α will be unchanged. If k and α
are kept constant, to keep Rs constant
(equation 1), all that remains is to make
sure that the column plate number stays
constant.
Keeping the Plate
Number Constant
Fortunately, the relationship between the
column plate number, N, the column
length, L, and particle diameter, dp, are
well defined and the effect of a change
in L or dp can be determined by a simple
calculation. And for you purists, yes, flow
rate does affect N, but for real samples
under real operating conditions, this effect
usually can be ignored for a change in
flow rate by a factor of two with particles
of dp ≤ 5 μm. N is directly proportional to
column length and inversely proportional
to particle size, so if L/dp is kept constant,
the plate number should remain constant.
Because the number of available col-
umn lengths and particle sizes is some-
what limited, the U.S. Pharmacopeial
Convention (USP) (1) suggests that
the plate number should be considered
equivalent if L/dp is a constant -25% to
+50%. For example, we can consider the
following columns to have equivalent plate
numbers (all lengths are in millimeters
and particle diameters in micrometers):
L/dp: 150/5 ≈ 100/3 ≈ 50/1.8
Ratio: (30) (33) (28)
You can see by the ratios shown below
each column configuration that each of
these columns has a ratio in a range of
±10%, so they can be considered equiva-
lent in terms of plate number. It should
be noted that the USP (1) also suggests
allowing other combinations of L and
dp to be used as long as N stays within
-25% to +50%, as would be the case for
core–shell particles, which provide larger
plate numbers than their particle diameter
might suggest.
Maintaining the Linear Velocity
It is customary to keep the linear velocity
(in units of millimeters per second) of the
mobile phase constant when the column
size is changed. The linear velocity is
independent of the column length, but
proportional to the cross-sectional area of
the column. So,
F2 = F1(πr22)/(πr1
2) [4]
or
F2 = F1(dc2/dc1)2 [5]
Where F is the flow rate, r is the col-
umn internal radius, and dc is the
column internal diameter; subscripts
1 and 2 are for the original and new
column, respectively. For a change from
a 4.6-mm i.d. column to a 2.1-mm
column, equation 5 generates a ratio of
(4.6/2.1)2 = 4.8 ≈ 5. Because this change
in diameter is the most common one we
encounter, I like to remember the fac-
tor of five so I can do the quick mental
math. Thus, a 4.6-mm i.d. column
operated at 1 mL/min would mean that
an equivalent linear velocity would be
obtained with a 2.1-mm i.d. column at
0.2 mL/min.
What About Pressure?
Pressure in LC separations is a result of
the separation conditions used, and in
itself is important only relative to the
pressure capability of the instrument.
The exception to this generalization is
that sometimes selectivity (peak spacing)
will change when large changes in pres-
sure occur, such as when switching from
conventional LC pressures to UHPLC
pressures. Although we generally run
conventional LC systems at half to three
quarters of their pressure capability,
all can generate pressures of 400 bar
(6000 psi). UHPLC comprises instru-
ments with a pressure capability of >400
bar, and in some cases up to 1300 bar
(19,000 psi), but most workers operate
their UHPLC systems at 600–1000 bar
(8700–14,500 psi).
Pressure is directly related to column
length and inversely related to the col-
umn cross-sectional area. It is directly
related to the flow rate and inversely
related to the square of the particle size.
Pressure also is influenced by the mobile-
phase viscosity and the column tempera-
ture, but for the present discussion, we’re
assuming that these remain constant so
that selectivity is not changed. Combin-
ing these factors, we have the following
relationship for pressure, P:
P2 = P1(L2/L1) (dc1/dc2)2 (dp1/dp2)
2 (F2/F1)
[6]
where P1 and P2 are the initial and new
pressures, respectively. If we want to
maintain linear velocity, F2 will be deter-
mined by the column diameter change
as in equation 5. If we are not concerned
about linear velocity (usually the case
for ≤3 μm dp particles and often for ≤5
μm ones), F2 may be adjusted to obtain
a desired pressure P2. Examples are dis-
cussed below.
And the New
Retention Time Is . . .
Many of the changes discussed above
will result in a change in the retention
time of each peak. Because we’re only
considering isocratic separations and we
have been careful to avoid making any
chemical changes to the system, we can
calculate what the new retention time
will be. We can use an equation similar
to equation 6 (but be careful which terms
are in the numerator and denominator):
tR2 = tR1(L2/L1) (dc2/dc1)2 (F1/F2) [7]
where tR1 and tR2 are the original and new
retention times, respectively. That is, the
same factors affect retention time as those
that affect pressure, with the exception
that particle diameter does not come into
play for retention. An example is included
in the discussion below.
Example
Let’s look at two examples. In the first
example, let’s consider a hypothetical,
compendial method that uses a 250 mm
× 4.6 mm, 5-μm dp column operated
at 1.0 mL/min, as is typical for many
of the older pharmacopeial methods.
Let’s assume that the retention time of
the analyte of interest is 17 min. The
current method conditions generate a
system pressure of 110 bar (1600 psi),
but for the new method we’re willing
to tolerate 300 bar (4300 psi). To speed
things up, let’s move the method to a
3-μm dp column and to save solvent,
we’ll use a 2.1-mm i.d. column. How do
we go about this?
First, to maintain resolution, we want
to keep N constant, which means L/dp
should be constant within -25% to +50%.
So we can calculate the desired column
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102 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
length and then choose an available one that is close to satisfying
this relationship:
L2 = L1dp2/dp1 [8]
or (250 mm × 3 μm/5 μm) = 150 mm. Because 150-mm col-
umns are readily available, the new column’s dimensions will be
150 mm × 2.1 mm and it will be packed with 3-μm dp particles.
Next, we might optionally calculate the flow rate required
for a constant linear velocity with the new column. Using
equation 5, 1.0 mL/min × (2.1 mm/4.6 mm)2 = 0.21 mL/
min, so a new flow rate of 0.2 mL/min would keep the linear
velocity constant.
Now we can calculate what the new pressure would be using
equation 6: 110 bar × (150 mm/250 mm) × (4.6 mm/2.1 mm)2
× (5 μm/3 μm)2 × (0.2 mL/min/1.0 mL/min) = 175 bar (2550
psi). Because this is an isocratic method, we don’t have to be too
concerned about linear velocity, so we can increase the flow rate
to 0.3 mL/min to speed up the method, which would generate an
expected pressure of ~265 bar (3850 psi), well within our desired
maximum pressure.
Finally, we can calculate the new retention time using equation
7: 17 min × (150 mm/250 mm) × (2.1 mm/4.6 mm)2 × (1.0
mL/min/0.3 mL/min) = 7.1 min. All the other peaks in the chro-
matogram will change by the same factor, so for a shortcut, use
the ratio 7.1 min/17 min = 0.41 as the multiplier to determine the
retention times of the other peaks.
As a second example, let’s convert an existing conventional
method to UHPLC conditions. Our original method uses a 150
mm × 4.6 mm column packed with 5-μm dp particles operated
at 1.5 mL/min. The retention time of the active ingredient is 12
min and the pressure is 150 bar (2175 psi). We want to use a 1.7-
μm column with a maximum pressure of 1000 bar (14,500 psi).
First, find the desired column length with the help of equation
8: 150 mm × 1.7 μm/5 μm = 51 mm, so we’ll use a 50 mm ×
2.1 mm column packed with 1.7-μm dp particles. For the flow
rate conversion, let’s just use our factor of five for the 4.6 mm
to 2.1 mm i.d. change. This gives us (1.5/5) = 0.3 mL/min as a
starting flow rate with constant linear velocity.
The pressure calculation, using equation 6, gives a new pres-
sure of 415 bar. Because we can tolerate up to 1000 bar, we can
increase the flow rate to 0.7 mL/min and have a predicted pressure
of 970 bar. The predicted retention time using equation 7 will be
reduced from 12 min down to 1.8 min. The retention times for
the remaining peaks will change by a factor of 1.8/12 = 0.15.
In both of these examples, our next step would be to run the
desired new conditions and observe what happens. Because we
expect the chemistry to be the same and the same plate number
was chosen, the resolution should remain the same. The retention
times should also be close to the calculated values. The observed
pressure will likely deviate from the calculated one somewhat —
for example, because of the additional pressure generated by very
small tubing diameters used for UHPLC.
A Simpler Way
The calculations above are not difficult, but they can be tedious
to perform on a routine basis. You can do as I’ve done and put the
equations into an Excel spreadsheet, making the calculations sim-
ple. Some of the data system software packages now have method
conversion calculators built in. Alternatively, there are several of
these calculators that are free on the internet. Just use a search term
such as “HPLC method transfer calculator,” and you will find sev-
eral choices. I used one of these to double-check my calculations.
Stay tuned for next month’s “LC Troubleshooting,” where we’ll
extend the current discussion to include scaling gradient methods.
Reference
(1) General Chapter 621 “Chromatography, Pharmacopeial Forum
PF38(2)” in United States Pharmacopeia 35–National Formulary 30
(United States Pharmacopeial Convention, Rockville, Maryland,
2012), www.usppf.com.
For more information on this topic,
please visit www.chromatographyonline.com/dolan
John W. Dolan“LC Troubleshooting” Editor John Dolan has been writing “LC Troubleshooting” for LCGC for more than 30 years. One of the industry’s most respected professionals, John is currently the Vice President of and a principal instructor for LC Resources in Walnut Creek, California. He is also a member of LCGC’s editorial advisory board. Direct correspondence about this column via e-mail to [email protected]
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MS – THE PRACTICAL ART
Mass spectrometry (MS)
serves as a versatile and
effective tool in chemical
analysis. It provides
highly specific molecular
information at excellent
sensitivity. The emerging
miniature MS systems
could potentially be
used outside analytical
laboratories by personnel
not trained in analytical
chemistry, and thereby
the range of applications
for MS could also be
significantly broadened.
This column installment
defines the future role
of miniature MS systems
in specialized analysis,
justifies the need for
simplification in operation,
proposes a development
approach involving ambient
ionization, and delineates
challenges in development
and commercialization.
Zheng Ouyang is the guest author of this
month’s installment.
Kate Yu is the editor of
MS—The Practical Art.
When we mention miniature
mass spectrometers, it often
brings to mind handheld
research prototypes such as the Mini 10
or Mini 11 systems developed at Purdue
University (West Lafayette, Indiana) or
commercial products that specialize in
homeland security applications (1). A
marked advance in the same category
is the recent development at Purdue of
a backpack mass spectrometer that has
a sampling probe that can scan ground
surfaces for in-field detection of explo-
sives (2). In this column installment,
however, we contemplate a different
type of miniature mass spectrometry
(MS) analysis systems, such as the Mini
12 system (3). Also developed at Pur-
due, the Mini 12 system weighs 25 kg,
is as compact as a desktop computer,
and could prove useful in the field of
biomedicine as well in the pharma-
ceutical, chemical, and agrochemical
industries. A primary motivation for
developing such a system is to enable
physicians, nurses, and biologists to
analyze samples at their desks, obviat-
ing the need to send the samples to an
analytical laboratory.
Miniature Mass Spectrometry
Analysis System Defined
In the past, the term miniature mass
spectrometer has been used for a vari-
ety of devices that fall within a broad
range of system completeness or self-
sustainability. The miniature mass
analyzers or vacuum manifold assem-
blies by themselves have all been called
miniature mass spectrometers previously.
Finally, complete instrument packages
were developed to perform vacuum
pumping, ionization, mass analysis,
instrument control, and data acquisi-
tion. As demonstrated by the Mini 11,
a mass spectrometer, even with multi-
stage MS-MS capability, can be made
to weigh only 4 kg (4). Such a minia-
turized instrument by itself, however,
would not be practically useful because
it could not perform complete chemi-
cal analyses starting from raw samples
(1). As for a mobile chemical analysis
laboratory, additional equipment for
sample preparation and chromato-
graphic separation is always needed and
could require more space than the mass
spectrometer. Thus, sample prepara-
tion before MS analysis must also be
done using miniaturized equipment and
highly autonomous procedures.
Assuming such miniaturization is
feasible at a system level, a biologist
doing a preclinical study could almost
effortlessly perform routine work such
as finding the concentration of a drug
metabolite in blood. To do that, he or
she would draw about 0.5 μL of blood
from a study animal (for example, a
mouse), drop the blood onto a paper
substrate inside a disposable sample
cartridge, push the cartridge into the
analysis system, and then wait 60 s
for a report of the concentration. With
such a small amount of sample required,
this type of analysis would be mini-
mally invasive. More importantly, the
biologist would not need to program the
instrument, telling it what to look for or
what to do. Instead, a bar code on the
cartridge would be scanned, and a pre-
saved scan function would be automati-
cally loaded and executed. The biologist
also would not need to be concerned
The Future of Miniature Mass
Spectrometers and a Path
Forward: A Few Thoughts
from an Academic Researcher
FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 105www.chromatographyonline.com
about the accuracy of measuring a 0.5-
μL sample, because he or she would use
a precut capillary, taking the blood by
capillary action. The biologist could also
expect a high degree of precision for the
quantitation result because the internal
standard (IS) would be precoated on
the inside wall of the capillary (5), and
the concentration calculated according
to the analyte/IS ratio measured and a
presaved calibration curve.
A similar system could be used by a
nurse performing a blood test to iden-
tify a smoker (6), by a physician who
must perform therapeutic drug monitor-
ing to prescribe the correct dosage of
cancer or immunosuppressive drugs (7),
or by a police officer or anxious parent
who wants to determine the presence or
absence of illicit drugs in urine (8). To
do these things, complete systems much
smaller than the current systems used
in analytical laboratories must be devel-
oped. Nevertheless, though we could
never overemphasize the importance
of a system’s operational simplicity, we
might indeed overemphasize the impor-
tance of its small size. Yet we must avoid
doing so. If we can accommodate print-
ers or copiers of various sizes, it might
be ok for us to accept MS systems of 50
kg, as long as they can be operated like
a printer or copier and fit unobtrusively
in our offices.
Development Strategy
The focus of miniaturization used to
apply mainly to instrumentation. How-
ever, the development of applications
for small instruments such as the Mini
11 revealed that beyond the mass spec-
trometer itself, much remained to be
addressed before a complete solution for
chemical analysis could be offered out-
side the laboratory. Mass spectrometers
are always at the end of the food chain
and they just don’t take raw stuff very
well! The Mini 12, as a proof-of-concept
prototype, was developed for exploring a
solution at the system level.
The incremental approach to reduc-
ing equipment size (for instance, by
adopting microextraction or microflu-
idic technologies for traditional sample
preparation and chromatographic sepa-
ration) might eventually deliver some
good integrated solutions. However,
direct MS analysis using ambient ion-
ization has certainly already shown its
potential (9–11). The term ambient ion-
ization, coined by Professor R. Graham
Cooks at Purdue, originally referred to a
class of sampling ionization technologies
for direct ionization of chemicals from
samples in their raw or unprocessed
“ambient” state (12). I often wonder
whether by now Graham has regretted
using this term, for so many research-
ers misconstrue ambient ionization as
meaning ambient pressure ionization and
therefore atmospheric pressure ionization,
which refers to electrospray ionization
(ESI) or atmospheric pressure chemical
ionization (APCI). Both ESI and APCI
are used under atmospheric pressure,
but traditionally only with compounds
extensively purified following sample
preparation.
The potential of ambient ioniza-
tion was originally demonstrated with
desorption electrospray ionization
(DESI) and direct analysis in real
time (DART) (13), not to mention
another 30-plus ambient ionization
methods developed thereafter (9–11).
Remarkable limits of detection have
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been achieved using direct sampling
analysis without any chromatographic
separations. Examples include the
detection of chemical warfare agents
at low-parts-per-billion (ppb) levels
using DART (14), 0.62 pg/mL nicotine
in gas-phase samples using extractive
electrospray ionization (EESI) (15), 100
fmol of peptides using electrospray-
assisted laser desorption ionization
(ELDI) (16), and 0.2–40 ng amounts
of drug molecules in plasma using
DESI (17).
A promising strategy for the future
development of miniature MS analysis
systems, as the Mini 12 system has dem-
onstrated, would be to combine ambient
ionization methods with miniature mass
spectrometers (18). In the Mini 12 sys-
tem, paper spray ionization (7) (Figure
1) is used with a miniature ion-trap mass
spectrometer. A blood sample is depos-
ited on the triangle paper substrate inside
a sample cartridge, forming a dried blood
spot. After it is pushed into the system,
about 10–30 μL of organic solvent is
automatically added to the cartridge, and
a voltage of about 4 kV is applied. The
solvent elutes the organic compounds,
such as drugs and their metabolites,
and spray ionization occurs at the tip of
the paper substrate. Two MS-MS scans
are automatically performed on the
analyte and its internal standard, which
can be mixed in the sample by using
an IS-coated capillary (5) or IS-printed
paper substrate (19). As an example of
the quantitation performance possible
using the Mini 12, consider the analy-
sis of amitriptyline in blood (3), which
returned an limit of detection (LOD) of
7.5 ng/mL and a relative standard devia-
tion (RSD) better than 10% (Figure 2).
Challenges and Solutions
The challenges associated with bring-
ing miniaturized MS analysis systems
to end users are quite considerable. The
instrumentation and application must
be researched and developed much
further, and a good strategy will even-
tually be needed to develop the initial
market for the products. Before we even
begin to address those challenges, we
must overcome a psychological barrier.
MS has established itself as the “gold
standard” for chemical analysis, and it
is proudly announced as the most sensi-
tive and specific technique for “general
purpose” analysis. The development and
continuous refinement of conventional,
general-purpose MS analysis systems
has, in turn, led to better resolution,
mass accuracy, and wider dynamic
ranges for both mass-to-charge ratio
(m/z) and concentration. MS systems
meeting with these criteria are therefore
highly effective for analyzing a plethora
of chemical and biological compounds
over wide ranges of concentration and
molecular weight. For example, Figure 3
shows a subset of chemical and biologi-
cal compounds, ranging in mass from
several hundred daltons to 16 kDa, in
human blood that includes therapeutic
drugs, amino acids, lipids, and proteins.
In concentration, these compounds vary
by more than nine orders of magnitude.
Following delicate sample prepara-
tion and chromatographic separation,
they can all be quantitatively analyzed
using modern, commercial mass spec-
trometers. Indeed, the success of mass
spectrometers has produced the high
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FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 107www.chromatographyonline.com
standard by which we judge their
performance and guide instrument
development. However, any attempt to
transfer the capability of conventional
mass spectrometers to miniature MS
systems would sink the ship before the
journey starts. To gain the convenience
of using small systems, we must forgo
something; we must compromise, and
we must do so in a significant way.
Can we make small MS systems with
each specialized only for one compound
from one sample? In such a case, we
need to worry about only a narrow
concentration range, a narrow m/z
range (though perhaps not for hemoglo-
bin — at least not yet), a single SRM
(MS-MS) scan, and a single calibration
curve. The chance for packaging these
functions into a unit operated with
minimal human intervention would be
significantly larger. One must question
whether manufacturers would profit by
systems of restricted application range,
but which would, nonetheless, reflect
significant development and production
costs. At the moment, we might have to
blindly believe that the high-volume sale
10 μL
kV
0.4 μL
LOQ: 1ng/mL
Measu
red
co
nce
ntr
ati
on
(μg
/mL)
RSD < 8%
T
4
3
2
1
00 1 2
Theoretical concentration (μg/mL)3 4
Figure 1: Paper spray ionization and direct quantitative analysis of imatinib in blood. Adapted from reference 7.
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108 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
of units and their associated consum-
ables, simply because of the convenience
of use, would take care of the profit.
This would make it critical to identify
killer applications for launching the
product.
Here I am depicting a future of MS
with two distinct paths: one for the cur-
rent commercial MS systems further
advanced for discovery and research
work and the other for the specialized
and turnkey miniature MS systems
developed for routine analysis.
Some technical challenges have
already been identified. They include
efficient extraction of target compounds
from the complex sample; efficient
transfer of the ions into the miniature
mass spectrometer; and adequate per-
formance for compound identification,
in light of “compromised” instrument
capability. Rapid development in the
field of ambient ionization offers us
hope that miniature MS systems using
consumable sample cartridges would
perform with adequate sensitivity.
A critical development in operation
procedure would be the accurate trans-
fer of small amounts of samples and the
incorporation of internal standards for
quantitation. The practical challenge
lies in the associated procedures, which
must be simple enough for users who are
untrained in analytical techniques (5).
The interface for coupling an ambient
ionization source with a miniature mass
spectrometer is another challenge. For
instruments fitted with small pumps,
ion transfer from air to mass analyzer
has proved difficult. Currently, the only
method developed is the discontinuous
atmospheric pressure interface (20) used
in the Mini 12 (3) and its predecessors,
the Mini 10 (20) and Mini 11 (4). This
is one area in the instrument development
that particularly needs some major effort.
People are also generally nervous about
the mass accuracy and mass resolution
3
2
A/IS
1
00 100 200
Concentration (ng/mL)
300 400 500
Therapeutic range
RSD < 10%
LOQ: 7.5 ng/mL
Figure 2: Plot showing the performance of the Mini 12 MS system for the quantitation of therapeutic drugs in a blood sample. Adapted from reference 3.
FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 109www.chromatographyonline.com
of the miniature mass spectrometer,
which no doubt would be somewhat
compromised to achieve smaller size,
lower weight, and lower cost of the
system. Before we put enormous effort
into tackling this problem, we should
ask this question: How much could we
tolerate the mass shifts and overlap of
the isobaric peaks if MS-MS transitions
are used for compound identification?
Formulating a general answer would
be difficult right now, and we probably
should not look for a general solution
in the future for miniature MS systems
either. For a special package with a sam-
pling ionization method optimized for
target analytes, the specificity and reli-
ability based on MS-MS can easily be
tested. On-cartridge, real-time reactions
can also be incorporated, improving the
specificity based on the chemical struc-
tures of the target compounds (19).
The Path Forward in Research
and Commercialization
The miniaturization of mass spectrom-
eters used to be solely for instrumental-
ists. Now, however, the future devel-
opment of complete analysis systems
requires a major contribution by ana-
lytical chemists who possess extensive
knowledge and experience in sample
treatment and chromatography. We will
need to persuade many of them to shift
their interest from liquid chromatogra-
phy (LC) columns to sample cartridges
with integrated functions for real-time
extraction and sampling ionization.
Developing miniature MS analy-
sis systems requires a comprehensive
engineering capability for research and
development, certainly a stretch for
academic, analytical chemistry research
groups, which have historically made
major efforts to develop instrumenta-
tion for chemical analysis. In the past,
the Jonathan Amy Facility for Chemical
Instrumentation (JAFCI) at Purdue has
served as an effective model for enabling
the engineering capability to analyti-
cal chemists. In fact, the JAFCI model
has been adopted by other chemistry
departments nationwide. Current eco-
nomic constraints, however, make estab-
lishing new facilities or even maintain-
ing current ones difficult. Searching for
alternatives, some analytical chemistry
divisions have exploited their intrinsic
connections with academic engineering
departments such as chemical engineer-
ing and biomedical engineering. Some
new initiatives nationwide among these
departments suggest that their faculty’s
holding positions in both chemistry
and engineering departments might
be a sustainable way of creating and
maintaining multidisciplinary research
environments for developing chemical
instrumentation. Such a setup would
also provide an opportunity for engi-
neering students and researchers to play
a more active role, versus a supportive
one in the JAFCI model, in the research
and development of chemical instru-
mentation; as long as we tell them we
are now stepping into the era of “MS
sensors” and that Rapid Communications
in Mass Spectrometry (RCM), Inter-
national Journal of Molecular Sciences
(IJMS), Journal of Mass Spectrometry
(JMS), or Journal of The American Soci-
ety for Mass Spectrometry (JASMS) are
actually all engineering journals.
The future of the miniature MS
analysis systems could be very bright;
the path for their commercialization,
110 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
Dedication to R. Graham Cooks:
An “Acorn” in Mass Spectrometry
This article is based on my thoughts
and those of my former mentor
and current colleague at Purdue
University, Professor R. Graham
Cooks (though without his knowl-
edge). Each year, the university’s
vice president for research hosts
a dinner for “Boilermakers” who
have brought in substantial grants,
and awards each of them a “brass
acorn,” the university’s symbolic
“Seed for Success.” With more
than 100 PhD students graduated,
Graham is truly one of the most
productive acorns in the field of
MS. He has promoted analytical
instrumentation his entire, lengthy
career and has been one of the most active advocates for mass spectrometer minia-
turization. In recognition of his contribution to the advances in chemical instru-
mentation, Graham was awarded the 2013 Dreyfus Prize in the Chemical Sciences.
In his plenary talk at the 50th American Society for Mass Spectrometry (ASMS)
Conference in 2002, Graham cited a poem by Stephen Spender as a dedication to the
pioneers in mass spectrometry. Here I dedicate the same poem to him, R. Graham
Cooks, a warrior, a wanderer, and a gentleman in the field of mass spectrometry.
“I Think Continually of Those Who Were Truly Great”
by Stephen Spender
I think continually of those who were truly great.
Who, from the womb, remembered the soul’s history
Through corridors of light where the hours are suns
Endless and singing. Whose lovely ambition
Was that their lips, still touched with fire,
Should tell of the Spirit clothed from head to foot in song.
And who hoarded from the Spring branches
The desires falling across their bodies like blossoms.
What is precious is never to forget
The essential delight of the blood drawn from ageless springs
Breaking through rocks in worlds before our earth.
Never to deny its pleasure in the morning simple light
Nor its grave evening demand for love.
Never to allow gradually the traffic to smother
With noise and fog the flowering of the spirit.
Near the snow, near the sun, in the highest fields
See how these names are feted by the waving grass
And by the streamers of white cloud
And whispers of wind in the listening sky.
The names of those who in their lives fought for life
Who wore at their hearts the fire’s centre.
Born of the sun they travelled a short while towards the sun,
And left the vivid air signed with their honour.
Professor R. Graham Cooks of Purdue University and two of his apprentices, Scott McLuckey (left) of the Department of Chemistry, and the author, Zheng Ouyang (right), of the Weldon School of Biomedical Engineering. Photo taken at the 2013 “Acorn Awards” dinner at Purdue University.
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FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 111www.chromatographyonline.com
however, could still be very difficult.
It is not a natural move for any of the
current major instrument companies to
initiate the production of small systems.
No doubt they all retain top-quality
instrumentation scientists who can
produce products of novel capabilities;
however, it can be mentally torching to
ask the builders of Mercedes-Benz auto-
mobiles to shift their interests to mak-
ing scooters. Besides, market research
plays such an important role nowadays
in deciding which products to develop,
and no valid data would be available for
anything truly groundbreaking. Unless
a “dictator” with a vision like Steve Jobs
appeared in one of the large instrument
corporations, development of miniature
MS products would more likely be pur-
sued by some desperate startups that
really want to go beyond the homeland
security market. Even then, however,
patent issues can be formidable for such
small companies because technical areas
are well-covered by the major players in
the industry.
China, however, is uniquely positioned
to assume a major role in commercial-
izing miniature MS analysis systems.
Traditionally, instrumentation companies
have not applied for patent protection for
their technologies in China. Therefore,
it is easier to produce a product package
that includes the best suitable technolo-
gies in China than to do so in North
America, Europe, Japan, or Australia.
Would the size of the market in China
justify such a development? Indeed it
would. China has become the world’s
number-two market for MS products.
Given the high cost of materials in the
production-based economy, improper use
of cheap materials and illicit additives is
a problem in China that calls for product
quality control. This is a major appli-
cation area well suited for specialized
MS systems. Since 2004, the Chinese
government has invested in MS product
development, and the funding amount
was dramatically increased recently, with
each individual project funded at $10M
or higher. Although the direct product
outcomes of these investments remain
to be seen, the development activities
have certainly trained many researchers
and developers in the requirements of
10-1 10-4
Concentration (g/mL)
Hemoglo
bin
Sphingom
yelin
Cyclophosp
hamid
e
Lidocain
e
Amin
o acids
Amitr
ipty
line
Tamoxife
n
Topotecan
10-5 10-6 10-7 10-8 10-9
Figure 3: Exemplary chemical and biological compounds in human blood.
112 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
the MS instrument industry. Because
it lacks a major player in that industry,
China has been striving to establish one,
and the concept of small instruments for
specialized applications has long been
considered as a good foothold for break-
ing into the business of MS manufacture.
Also, the culture of “wide mass range,”
“high dynamic ranges,” and “ultimately
high resolution and precision” is not so
deeply rooted in China as it is in other
places. Thus it would come as no surprise
to soon see some miniature MS products
manufactured there and packaged into
different systems suitable for various
needs in different global regions.
References
(1) Z. Ouyang and R.G. Cooks, Annu. Rev.
Anal. Chem. 2, 187–214 (2009).
(2) P.I. Hendricks, J.K. Dalgleish, J.T. Shel-
ley, M.A. Kirleis, M.T. McNicholas, L. Li,
T.-C. Chen, C.-H. Chen, J.S. Duncan, F.
Boudreau, R.J. Noll, J.P. Denton, Z. Ouy-
ang, and R.G. Cooks, submitted to Analyti-
cal Chemistry, 2013, under review.
(3) L. Li, T.-C. Chen, Y. Ren, P.I. Hen-
dricks, R.G. Cooks, and Z. Ouyang,
submitted to Analytical Chemistry, 2013,
under review.
(4) L. Gao, A. Sugiarto, J.D. Harper, R.G.
Cooks, and Z. Ouyang, Anal. Chem. 80,
7198–7205 (2008).
(5) J. Liu, R.G. Cooks, and Z. Ouyang, Anal.
Chem. 85, 5632–5636 (2013).
(6) H. Wang, Y. Ren, M.N. McLuckey, N.E.
Manicke, J. Park, L. Zheng, R. Shi, R.G.
Cooks, and Z. Ouyang, Anal. Chem. 85,
11540–11544 (2013).
(7) H. Wang, J. Liu, R.G. Cooks, and Z. Ouy-
ang, Angew. Chem., Int. Ed. 49, 877–880
(2010).
(8) Y. Su, H. Wang, J. Liu, P. Wei, R.G. Cooks,
and Z. Ouyang, Analyst 138, 4443–4447
(2013).
(9) R.G. Cooks, Z. Ouyang, Z. Takats, and J.M.
Wiseman, Science 311, 1566–1570 (2006).
(10) Z. Ouyang and X. Zhang, Analyst 135,
659–660 (2010).
(11) M.E. Monge, G.A. Harris, P. Dwivedi, and
F.M. Fernández, Chem. Rev. 113, 2269–
2308 (2013).
(12) Z. Takáts, J.M. Wiseman, B. Gologan, and
R.G. Cooks, Science 306, 471–473 (2004).
(13) R.B. Cody, J.A. Laramee, and H.D. Durst,
Anal. Chem. 77, 2297–2302 (2005).
(14) J.M. Nilles, T.R. Connell, and H.D. Durst,
Anal. Chem. 81, 6744–6749 (2009).
(15) C. Berchtold, L. Meier, and R. Zenobi, Int.
J. Mass Spectrom. 299, 145–150 (2011).
(16) I.X. Peng, R.R.O. Loo, E. Margalith, M.W.
Little, and J.A. Loo, Analyst 135, 767–772
(2010).
(17) J.H. Kennedy and J.M. Wiseman, Rapid
Commun. Mass Spectrom. 24, 309–314
(2010).
(18) L. Gao, R.G. Cooks, and Z. Ouyang, Anal.
Chem. 80, 4026–4032 (2008).
(19) J. Liu, H. Wang, N.E. Manicke, J.-M. Lin,
R.G. Cooks, and Z. Ouyang, Anal. Chem.
82, 2463–2471 (2010).
Zheng Ouyangis an Associate Professor in the Wel-don School of Bio-medical Engineering at Purdue University (West Lafayette, Indiana). He has a research interest in developing instrumentation and applica-tions for mass spectrometry, with results published in more than 110 peer-reviewed publications. He has received a number of awards including the Wallace H. Coul-ter Foundation Early Career Translational Research Award in Biomedical Engineering, a China National Natural Science Foundation Award for Distinguished Overseas Young Scholars, a USA National Science Foundation Early Career Award, the American Society for Mass Spectrometry Research Award, and the International Mass Spectrometry Society Curt Brunnée Award for outstanding contri-butions to the development of instrumenta-tion for mass spectrometry.
Kate Yu“MS — The Practical Art” Editor Kate Yu joined Waters in Mil-ford, Massachusetts, in 1998. She has a wealth of experience in applying LC–MS technologies to vari-ous application fields such as metabolite identification, metabolomics, quantitative bioanalysis, natural products, and environ-mental applications. Direct correspondence about this column to [email protected]
For more on mass spectrometry, see the
full “MS–The Practical Art” column at
www.chromatographyonline.com/MSPA.
Also, see our ongoing supplement series,
Current Trends in Mass Spectrometry, under
“Publications,” then “Supplements.”
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Walter J. Krol, Brian D. Eitzer, Terri Arsenault, Mary Jane Incorvia Mattina, and Jason C. WhiteThe Connecticut Agricultural Experiment Station, Department of Analytical Chemis-try, New Haven, Connecticut. Direct corre-spondence to: [email protected]
Significant Improvements in Pesticide
Residue Analysis in Food Using the
QuEChERS Method
The quick, easy, cheap, effective, rugged, and safe (QuEChERS) sample
preparation procedure combined with both gas chromatography–mass
spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–
MS) was adopted in our laboratory for the analysis of pesticide residues in
food samples as part of the state of Connecticut’s regulatory monitoring
program. In 2006, data from a QuEChERS-based sample preparation
procedure were compared to data from our previous analytical method. In
this article, these results are further compared to those of the U.S. Food and
Drug Administration’s pesticide residue monitoring program and the U.S.
Department of Agriculture’s pesticide data program.
Since its inception in 1963, the pesti-
cide residue program in the Depart-
ment of Analytical Chemistry at
The Connecticut Agricultural Experiment
Station (CAES) has made major advance-
ments in the analyses of pesticide resi-
dues present in food — primarily but not
exclusively produce. In 1992, the method
of Pylypiw (1) was used in our laboratory
to replace our older methods (2) for the
extraction of organochlorine and organo-
phosphorous pesticides from food samples.
At the time, residues were analyzed by
gas chromatography (GC) with element-
selective detection. Beginning in 1993,
mass spectrometry (MS) was introduced
for the confirmation of violative residues.
By 1999, all samples were subjected to
MS analysis for the presence of pesticide
residues (3). In 2006, following the acqui-
sition of a ion trap liquid chromatogra-
phy–mass spectrometry (LC–MS) system,
a direct comparison was made between
the Pylypiw method and the then newly
published quick, easy, cheap, effective,
rugged, and safe (QuEChERS) method
(4). In 2011, an orbital trap LC–MS sys-
tem (Thermo Scientific Exactive Orbitrap)
was added to our program and is currently
used for the exact-mass confirmation of
violative pesticide residues.
In 2006, we compared the Pylypiw
method (1), which offers petroleum ether
extracts that are amenable to GC analysis,
with an adaptation of the recently intro-
duced QuEChERS method (4), which
offers acetonitrile or toluene extracts that
are amenable to both GC–MS and LC–
MS. Approximately 181 samples obtained
for analyses in the Connecticut program
were tested using a paired sample blind
study protocol (vide infra). The extracts
from the Pylypiw method were analyzed
by GC–MS and GC with micro electron-
capture detection (ECD), and the QuECh-
ERS extracts were analyzed by GC–MS
and LC–MS as outlined in Figure 1.
The Connecticut program is similar to the
larger United States (US) Food and Drug
Administration (FDA) program in that it
tests a wide variety of samples available to
the consumer in the market place. The sam-
ples tested in these two surveys can be com-
prised of nearly any type of food offered for
sale to the consumer. On an average annual
basis from 1990 to 2010 the Connecticut
program tested 37 different commodity
types of fresh food and 14 different com-
modity types of processed food. These two
programs contrast to the US Department of
Agriculture (USDA) pesticide data program
(PDP) which, on average, targets 12 fresh
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MAKING A DIFFERENCE
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118 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
CT no residue found
CT violative samples
Pe
rce
nt
of
sam
ple
s w
ith
no
re
sid
ue
s
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
Pe
rce
nt
of
sam
ple
s w
ith
to
lera
nce
vio
lati
on
Left ordinate axis
FDA no residue found
Right ordinate axis
FDA violative samples
PDP no residue found
PDP violative samples
12.080.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
10.0
8.0
6.0
4.0
2.0
0.0
Year
Figure 2: Comparison of the Connecticut, FDA, and PDP monitoring programs for pesticide residues in food.
and four processed samples per year. Owing
to the fact that the results obtained from the
Connecticut and FDA programs are derived
from nontargeted sources (5), as opposed to
those in the PDP (6), the results obtained
through the Connecticut program are
thought to be more representative of those
in the larger FDA program.
From 1990 through 2005, the results
obtained from the Connecticut program
closely matched those obtained in the larger
FDA pesticide residue monitoring program
(Figure 2). During this timeframe, the FDA
program analyzed 167,215 samples (5); the
Connecticut program separately analyzed
4871 food samples (3). The Connecticut
program analyzed only about 3% (2.91%)
of the total samples in the FDA program. It
is noteworthy that there is not a significant
difference in the proportions of pesticide
residue–free samples, 63.3% reported by
Connecticut and 64.2% reported by FDA
(5) (Figure 2), over the 16-year timeframe
(1990–2005) when the data are compared
using a z-test (P = 0.230; z = 1.200). The
average violation rate over the same period
was similar, 1.5% for the Connecticut pro-
gram and 2.8% (5) for the FDA program,
but statistically different (P = <0.001; z =
5.114). These results imply that the sam-
pling design in Connecticut closely paral-
lels the larger program of the FDA, that
the analytical methodology used in the two
surveys was comparable over the timeframe
1990–2005, and that the smaller Con-
necticut subsample is representative of the
larger with respect to samples containing
pesticide residues.
From the inception of the USDA PDP
study in 1992 and through 2005, the results
obtained from the Connecticut program
contrasted sharply to those obtained in the
PDP study by as much as 38% (Figure 2).
During this timeframe the PDP targeted
112,395 samples (6), and the Connecticut
program tested 4150 samples. When com-
pared, the percentages of pesticide resi-
due–free samples over the inclusive 14-year
timeframe (1992–2005), 62.7% reported
by Connecticut and 38.8% reported by the
PDP, was not similar nor was it statistically
significant (P = <0.001; z =34.117). The
average violation rate reported, 3.5% by
the PDP (6) and 1.7% by Connecticut, was
likewise statistically dissimilar (P = <0.001;
z = 6.208). These results suggested that the
sampling designs of the two programs were
dissimilar and that the analytical method-
ology used in the two studies was likely
dissimilar.
Experimental
Sample Collection
All of the fresh and processed fruit and
vegetable samples examined in this work
were collected by inspectors from the Con-
necticut Department of Consumer Pro-
tection (DCP). The samples consisted of
fruits and vegetables grown in Connecti-
cut, other states, or foreign countries and
were collected at different Connecticut
farms, producers, retailers, and wholesale
outlets located within the state. The sam-
ples collected were brought to our labora-
tory in New Haven by the DCP inspectors
for pesticide-residue testing. In all cases,
these samples were collected without prior
knowledge of any pesticide application.
Sample Homogenization
In most cases, each sample was prepared
in its natural state as received, unwashed
and unpeeled, but in all cases samples were
processed according to the Pesticide Ana-
lytical Manual (7). Whole food samples
were homogenized before extraction using
Homogenized sample
QuEChERS extracts
181 Samples41 Processed
140 Fresh
Pylypiw extract
181 VegPrep extracts (petroleum ether)
Blind362 total extracts
181 QuEChERS extracts (acetonitrile–toluene)
GC–MS
GC–ECD
GC–MS
LC–MS
Figure 1: Flowchart of 2006 sample extract and analysis.
FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 119www.chromatographyonline.com
a food chopper or a commercial blender
equipped with an explosion-proof motor.
Liquid and powdery samples were mixed
thoroughly before subsampling for extrac-
tion. In all cases, a portion of each sample
(approximately 500 g) was retained and
frozen in plastic bags until analysis and
reporting of the results were completed.
Sample Extraction
Pylypiw Method
The method described by Pylypiw (1)
was used with minor modifications. A
50-g subsample of homogenized material
was weighed into a blender jar (1 L) and
blended with 50 mL of isopropyl alcohol
and 100 mL of petroleum ether for approx-
imately 5 min. After the mixture settled, it
was filtered through a plug of glass wool
into a 500-mL separatory funnel to remove
insoluble particulates. Interfering coex-
tracted compounds and the isopropyl alco-
hol were removed from the petroleum ether
extract by sequential washing with water
(3 × 200 mL). Saturated sodium sulfate
solution (50 mL) was added to the first
and the final wash to enhance partitioning
and phase separation. After the final wash,
the organic extract was collected in 40-mL
glass vials containing anhydrous sodium
sulfate (approximately 10 g) as a drying
agent. After 2 h, a portion of the sample
extract was transferred to a chromatogra-
phy vial and stored at room temperature
until analysis. It should be noted that this
extraction method results in a twofold dilu-
tion factor of the original sample.
QuEChERS Method
The QuEChERS method described by
Anastassiades and colleagues (4) was mod-
ified for this work. For the 990 samples
tested in this work, a 15-g subsample of
homogenized material was weighed into
a 50-mL disposable polypropylene centri-
fuge tube. The tube was then amended
with [U-ring]-13C6-Alachlor internal
standard (600 ng; prepared from mate-
rial purchased from Cambridge Isotope
Laboratories), anhydrous magnesium sul-
fate (6 g), anhydrous sodium acetate (1.5
g), and acetonitrile (15 mL) and the mix-
ture was shaken on a Burrell Model 75
Wrist Action shaker (Burrell Scientific)
for approximately 1 h. The tube was cen-
trifuged using a Centra GP6 centrifuge
(Thermo IEC) at 3000 rpm (2087g) for 10
min at approximately 25 °C to separate the
acetonitrile from the aqueous phase and
solids. Acetonitrile (10 mL) was decanted
into a 15-mL polypropylene Falcon cen-
trifuge tube (Corning) containing anhy-
drous magnesium sulfate (1.5 g); primary
and secondary amine (PSA) bonded silica
(0.5 g) and toluene (2.0 mL). The mixture
was shaken by hand for approximately 5
min and centrifuged at 3000 rpm (2087g)
for 10 min at 25 °C. Then 6 mL of the
extract was added to a concentrator tube
and blown down to just under 1 mL (but
not to dryness) under a stream of nitrogen
at 50 °C. The concentrated material was
reconstituted to a final volume of 1.0 mL
with toluene. It should be noted that this
extraction method results in a fivefold con-
centration of the original sample.
Whereas QuEChERS normally requires
the use of acidified acetonitrile when sodium
acetate is used for salting out (4,8,9), it was
intentionally not used in this modification.
The exclusion of acid provides better PSA
cleanup yet may lead to lower recoveries of
a few base sensitive pesticides (10). To mini-
mize potential lower recoveries, extracts are
stabilized by reconstitution in toluene fol-
lowing their concentration. Excluding the
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120 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
acid during the extraction eliminates the need for its neutralization
before concentrating the extract. Failure to neutralize the added acid
would expose the extracts to a concentrated acid environment fol-
lowing the concentration step used in the present protocol and lead
to rapid GC column degradation.
Instrumental Analysis
Pylypiw Extracts
From 1990 to 1999, 3547 extracts were analyzed by GC as
described by Pylypiw (1). Beginning in 1994, violative samples
were confirmed by MS using a model 5890 GC system equipped
with an HP-7673 autoinjector and an HP 5972A MSD system
(all from Hewlett-Packard Co.). Injections (2–4 μL) were made
onto a 30 m × 0.53 mm, 0.5-μm df SPB-5 fused-silica capillary
column (Sigma-Aldrich). From 1999 to 2006, samples prepared by
the Pylypiw method were analyzed using a model 6890 plus GC
equipped with dual 7683 series injectors, and a 7683 autosampler
(collectively known as an automatic liquid sampler [ALS]), a model
G2397A μECD system in the rear position, and a model 5973
MSD system in the front position (all from Agilent Technologies).
A programmable temperature vaporization (PTV) was installed on
the front inlet and a Merlin MicroSeal system (Merlin Instrument
Co.) on the rear inlet; dual 30 m × 250 μm, 0.25-μm df Supelco
MDN-12 fused-silica capillary columns (Sigma-Aldrich) were
used. Injections (2 μL) were made simultaneously onto both col-
umns. All data were collected and analyzed using MSD Productiv-
ity Chemstation software version B.02.00 (Agilent Technologies).
QuEChERS Extracts
Samples prepared by the QuEChERS method were analyzed by
GC–MS and LC–MS. For the GC analysis, a model 6890N GC
system equipped with a 7683 series ALS autosampler and a model
5975 MSD system were used (all from Agilent Technologies). The
inlet used a Merlin MicroSeal system with injections made onto
a 30 m × 250 μm, 0.25-μm df J&W Scientific DB-5MS+DG
column (Agilent Technologies). Data were collected and analyzed
using MSD Chemstation software version D.02.00.275 (Agilent
Technologies). The LC–MS analyses were made using a model
1100 LC system and a 150 mm × 2.1 mm, 5-μm dp Zorbax SB-C18
column (Agilent Technologies) with eluent flowing to a Thermo
Electron Finnigan LTQ ion-trap MS system through 2009. In
2010, the model 1100 LC system was replaced with a model 1200
Rapid Resolution LC system and a 50 mm × 4.6 mm, 1.8-μm
dp Zorbax XDB-C18 column (both from Agilent Technologies).
Data were collected and analyzed using Xcalibur software version
2.0 (Thermo Scientific). Beginning in 2010, confirmatory data
for violative samples were obtained using a model 1200 LC sys-
tem and a 150 mm × 2.1 mm, 5-μm dp Zorbax SB-C18 column
(both from Agilent Technologies) with eluent flowing to a Exac-
tive Orbitrap MS system (Thermo Scientific). Data analysis was
performed using ToxID version 2.1.2 and Xcalibur Qual Browser
version 2.1.0.1140 (both from Thermo Scientific).
2006 Blind Study Design
All samples were collected and homogenized as described above.
Subsamples of the homogenate were extracted and analyzed con-
currently by both the Pylypiw and QuEChERS protocols as out-
lined in Figure 1 by different laboratory personnel. The results
FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 121www.chromatographyonline.com
of the analyses performed were maintained
in separate databases by the laboratory per-
sonnel responsible for performing the indi-
vidual analysis. At the end of the one-year
study, the data obtained were reconciled
into a single database for statistical analysis.
Reproducibility of Results
All samples examined in this work were
individually homogenized, extracted,
and analyzed by GC and LC once. Inter-
and intralaboratory studies over a wide
range of pesticides, pesticide concentra-
tions, and matrices and its validation as
an Association of Analytical Communi-
ties (AOAC) method (4,8,9) have dem-
onstrated that a single, homogenized
extract is sufficient to obtain accurate
quantitation of pesticide residue con-
centrations. Anastassiades and cowork-
ers (8) have developed a database of
more than 150,000 recovery figures on
over 650 different pesticide residues. All
violative samples were re-extracted, ana-
lyzed, and quantified in duplicate using
portions of the original sample retained
from the homogenization step. One of
these duplicate samples was spiked with
the pesticides in question at a concen-
tration slightly above the originally
determined value. Quantitative values
of the pesticides in these extracts were
compared to the concentration found
in the original analysis. Beginning in
2010, exact MS data were also obtained
on those residues found to be violative.
Results and Discussion
In 2006, a comparison was made for 181
samples of fresh (140, 77.3%) and processed
Different active ingredients found
Residues/sample with pesticides
90Pre-QuEChERS QuEChERS
Secondary axis
3.5
2.5
1.5
3.0
2.0
1.0
0.5
0.0
50
40
30
20
10
02000 2002 2004 2006
Year
2008 2010
80
70
60
Percent sample with pesticides
Pri
mary
axis
Seco
nd
ary
axis
Average overall residue level (μg/g)
Figure 3: Impact of QuEChERS on the numbers and levels of detected pesticide residues found in Connecticut food samples.
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(41, 22.7%) samples between the Pylypiw
and QuEChERS extraction methods.
The 181 homogenized samples were each
divided, extracted, and analyzed as depicted
in Figure 1. There were a total of 362
extracts analyzed. It needs to be noted that
because of the extraction protocols used, the
Pylypiw extracts were 10 times more dilute
than the QuEChERS extracts (vide supra).
Of the 181 samples analyzed by the
Pylypiw protocol, 98 (54.2%) of the sam-
ples contained no detectable pesticide resi-
dues, 79 (43.6%) contained non-violative
residues (0.001–12.00 ppm), and 4 (2.2%)
contained violative residues (0.014–0.900
ppm). A total of 133 individual pesticide
residues were found on the 83 samples con-
taining pesticide residues.
By contrast, when the same 181 samples
were extracted by the QuEChERS method
and the extracts were analyzed by GC–MS
and LC–MS, 73 (40.3%) of the samples
were found to contain no detectable pes-
ticide residues (see Figure 2). The remain-
ing 108 samples contained 181 different
individual pesticide residues; 89 samples
(49.2%) contained nonviolative residues
(0.001–3.90 ppm) and 20 (11%) contained
violative residues (0.002–0.752 ppm). Of
these 181 residues, 42 were detected by GC
alone, 70 were detected by LC alone, and
69 residues were found by both instrumen-
tal methods of analysis.
The dramatic decrease in the number of
samples found to be pesticide residue free
when using the QuEChERS approach in
place of the Pylypiw protocol (40.3% vs.
54.2%) represents a major advancement
(13.9%) for our laboratory in the analy-
sis of pesticide residues in food. In 2006,
more violative residues (21 total; 11.6%)
were found than in any other year in our
survey. The Pylypiw method found only
one violation not found by the QuECh-
ERS approach, whereas the QuEChERS
method found 17 residues not found by the
Pylypiw method. It should be noted that
the number of 2006 violations was slightly
skewed owing to nine findings of atrazine.
A more thorough discussion about the
atrazine residues found has been presented
by Krol (11). Ultimately, it was found that
many of the residues were the result of
plant uptake when atrazine was applied in
a previous growing season. If the atrazine
violations are omitted from consideration,
there would have only been 12 violations
(6.6%) reported in 2006; and the violation
rate from the QuEChERS method would
have been nearly halved to 6.1% from the
11% reported above.
In 2006, it is clear that the Connecti-
cut Pylypiw results did not exactly match
those of the FDA study. Both studies how-
ever indicated that the majority of samples
tested, 98 (54.2%) and 3699 (67.1%)
respectively, were free from pesticide resi-
dues. The poor correlation is likely because
of a yearly fluctuation in the proportions
of residues present in the samples analyzed
over the course of this one year study.
These yearly fluctuations have been pres-
ent since 1990. The results of the QuECh-
ERS protocol in 2006 (Figure 2) indicate
that the majority of the food purchased for
consumption contain pesticide residues; in
fact 59.7% of the sampled food offered for
sale in Connecticut contains at least one
pesticide residue. The results obtained in
2006 more closely mimic those reported
in the PDP.
By way of comparison, in 2006 the
FDA reported (5) that it tested 5512 sam-
ples and found that 3699 (67.1%) of the
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samples contained no detectable pesticide residues; 1578 (28.6%)
contained nonviolative residues; 235 (4.3%) contained violative
residues. The USDA PDP (6) tested 9818 samples and found
that 3717 (37.9%) of the samples contained no detectable resi-
dues; 5767 (58.7%) contained nonviolative residues; 334 (3.4%)
contained violative residues.
To confirm the findings of our blind study and to address
potential yearly fluctuations in the data, we continued forward
with our work extracting all samples through the QuEChERS
protocol and analyzing the extract by both LC–MS and GC–MS.
We also continued with an indirect annual comparison of our
findings to those of the FDA pesticide monitoring program and
the PDP. Because of the fact that the LC–MS library used in the
QuEChERS screening needed to be established, the numbers of
different analytes detected has continually increased through the
course of the study.
As can be seen in Figure 2, beginning in 2006, the FDA
and Connecticut surveys dramatically diverge, and the results
of the Connecticut survey more closely matches those of the
PDP. On average, over the three years during 2006–2008, the
QuEChERS protocol in the Connecticut survey found that
36.3% of the samples contained no residues, compared to
66.9% reported by the FDA. During this same timeframe the
Connecticut violation rate was 6.9% as compared to the 3.9%
reported by the FDA.
A z-test comparison was made between the Connecticut data
obtained by the QuEChERS protocol (776 samples) and the
PDP data (40,726 samples) between 2006 and 2009. The pro-
portions of pesticide residue-free groups in the two studies were
found to be statistically significant (P = 0.783; z = 0.275).
The FDA program (12) currently uses multiresidue methods
(MRMs) and single-residue methods (SRMs) as described in the
Pesticide Analytical Manual (7) to determine the approximately
400 pesticides with Environmental Protection Agency (EPA) tol-
erances (12,13). Alternatively, the PDP laboratories have modi-
fied their protocols to take advantage of more-recent technological
advancements for the identification and quantification of pesticide
residues (6).
The 2006 Connecticut study has provided convincing evi-
dence that the use of the QuEChERS sample preparation
procedure combined with the complementary analyses of the
extracts by both GC–MS and LC–MS is preferred for deter-
mining pesticide residues in food. There are three key factors
responsible for this finding. First, the ability of the QuECh-
ERS method to extract greater and broader numbers of pesti-
cide active ingredients with adequate recoveries as documented
by Anastassiades (4) and others (8) has increased the number
of analytes routinely tested for in our laboratory. From 1990 to
2005, we reported on 18 different active ingredients, on aver-
age. Owing partly to the addition of active ingredients to our
spectral libraries, since 2006 we reported on an average of 52
different active ingredients.
Second, the QuEChERS extracts are amenable to both LC and
GC analysis providing complementary coverage of pesticide resi-
dues which cannot be determined by one instrumental method or
the other. In addition, because of the greater sensitivity provided
by LC–MS, it is not surprising to observe that the number of resi-
dues seen by LC rapidly outpaced those seen by GC. Third, the
fact that the final stage of the QuEChERS protocol allows for a
concentration step (in our work by a factor of 5) leads to greater
overall method sensitivity. This has led to the overall detection
of more pesticide residues at lower levels in the samples analyzed
(Figure 3). Taken together, these factors have led to a more accu-
rate picture of the occurrence of pesticide residues in the Con-
necticut food supply.
Conclusions
The vast majority of the fruits and vegetables we consume, with
the exception of organically grown produce, have been treated
with pesticides during the course of their production. If the pes-
ticides used during the production of this food have been used
in accordance with the approved use of the pesticide product, the
levels resulting on the food will be below the EPA tolerance (13).
In the past, because of the sensitivity and selectivity of the instru-
ments used at the CAES and in other pesticide residue monitor-
ing programs at both the Federal and state level, many of the
residues have gone undetected. By changing the extraction and
analysis methodologies used in our work, the results obtained in
the Connecticut studies which once showed statistical similari-
ties to FDA data, now show those similarities to data generated
by the USDA in their PDP studies. Because of the increased sen-
sitivity of our instrumentation and to the QuEChERS sample
preparation approach, our program is detecting greater numbers
of pesticides at lower levels. The results of this work allow the
consumer to gain a better understanding of the prevalence and
levels of pesticide residues in the food they consume.
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FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 125www.chromatographyonline.com
Acknowledgments
We would like to thank the Food Division
of the Department of Consumer Protec-
tion for providing samples for this study.
We would especially like to thank Ellen
Sloan for her tireless devotion and dedica-
tion to collecting the vast majority of the
samples included in this work.
References
(1) H.M. Pylypiw, Jr., J. AOAC Int. 76, 1369–
1373 (1993).
(2) H.M. Pylypiw and L. Hankin, Bulletin 900
(Connecticut Agricultural Experiment Sta-
tion, New Haven, Connecticut, 2006), p. 2
and references cited therein.
(3) W.J. Krol, T. Arsenault, and M.J.I. Mattina,
Bulletin 1006 (Connecticut Agricultural
Experiment Station, New Haven, Connecti-
cut, 2006), pp. 1–12.
(4) M. Anastassiades, S.J. Lehotay, D. Stajnbaher,
and F.J. Schenck, J. AOAC Int. 86, 412–431
(2003).
(5) Food and Drug Administration, Residue
Monitoring Reports 1993–2008, http://www.
fda.gov/Food/FoodborneIllnessContami-
nants/Pesticides/UCM2006797.htm.
(6) United States Department of Agriculture Pes-
ticide Data Program, Databases and Annual
Summaries 1992–2009, http://www.ams.
usda.gov/AMSv1.0/ams.fetchTemplateData.
do?template=TemplateG&topNav=&leftNav
=ScienceandLaboratories&page=PDPDownl
oadData/Reports&description=Download+P
DP+Data/Reports&acct=pestcddataprg
(7) Pesticide Analytical Manual Volume I (3rd
Ed., 1994 and subsequent revisions), available
from FDAs website at http://www.fda.gov/
food/foodscienceresearch/laboratorymethods/
ucm2006955.htm, and Volume II (1971 and
subsequent revisions), available from National
Technical Information Service, Springfield,
Virginia. Food and Drug Administration,
Washington, DC.
(8) M. Anastassiades et al., DataPool of the EU
Reference Laboratories for Residues of Pesti-
cides, http://www.eurl-pesticides-datapool.eu/.
(9) Official Methods of Analysis of AOAC Inter-
national (2011) 18th Ed., online, Official
Method 2007.01. http://www.eoma.aoac.org/
(10) F.J. Schenck and J.W. Wong, “Two Modi-
fied QuEChERS Methods for the Mul-
tiresidue Determination of Pesticides in
Produce Samples” presented at the 45th
Annual Florida Pesticide Residue Work-
shop, St. Pete Beach, Florida, 2008, http://
f lworkshop.com/09documents/2009-Pre-
sentations/08_Schenck.pdf
(11) W.J. Krol, B.D. Eitzer, T. Arsenault, and
M.J.I. Mattina, Bulletin 1012 (Connecticut
Agricultural Experiment Station, New Haven,
Connecticut, 2007), pp. 1–13.
(12) ibid. 5, Pesticide Monitoring Program FY
2008, Analytical Methods, http://www.fda.
gov/Food/FoodborneIllnessContaminants/
Pesticides/ucm228867.htm#Analytical_
Methods_and_Pesticide_Coverage.
(13) e-CFR (Electronic Code of Federal
Regulations) (2011) Title 40, 24, Part
180. http://ecfr.gpoaccess.gov/cgi/t/
text/text-idx?&c=ecfr&tpl=/ecfrbrowse/
Title40/40tab_02.tpl.
Walter J. Krol, Brian D. Eitzer,
Terri Arsenault, Mary Jane
Incorvia Mattina, and Jason
C. White are with the Department of
Analytical Chemistry at the Connecticut
Agricultural Experiment Station in New
Haven, Connecticut. Direct correspondence to:
For more information on this topic,
please visit
www.chromatographyonline.com
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Alexander H. Schmidt*,† and Mijo Stanic*, *Steiner & Co., Deutsche Arzneimittel GmbH & Co. KG, Berlin, Germany; and †Freie Universität Berlin, Institute of Pharmacy, Berlin, GermanyDirect correspondence to: [email protected]
Rapid UHPLC Method Development for
Omeprazole Analysis in a Quality-by-Design
Framework and Transfer to HPLC Using
Chromatographic Modeling
The aim of this study was to apply quality-by-design principles to
build in a more scientific and risk-based multifactorial strategy in the
development of an ultrahigh-pressure liquid chromatography (UHPLC)
method for omeprazole and its related impurities.
The qua l it y-by-design con-
cept was outlined years ago
by Joseph M. Juran (1) and is
used in many industries to improve
the quality of products and services
simply by planning quality from
the beginning. Since the US Food
and Drug Administration (FDA)
announced its “Pharmaceutical Cur-
rent Good Manufacturing Practices
(cGMPs) for the 21st Century” initia-
tive (2) in 2002, a quality-by-design
approach has also been sought in the
pharmaceutical industry.
Through the International Confer-
ence on Harmonization (ICH), this
concept resulted in ICH guideline
Q8(R2) in which quality-by-design
is defined as “a systematic approach
to development that begins with pre-
def ined objectives and emphasizes
product and process understanding and
process control, based on sound science
and quality risk management” (3).
Although ICH guideline Q8(R2)
doesn’t explicit ly take ana ly t ica l
method development into account
and no other regulatory guideline has
been issued, the quality-by-design
concept can be extended to a sys-
tematic approach that includes the
def inition of the methods goal, risk
assessment, design of experiments,
developing a design space, verif ica-
tion of the design space, implement-
ing a control strategy, and continual
improvement to increase method
robustness and knowledge (4). The
novelty and opportunity in this
approach is that working within the
design space of a specific method can
be seen as an adjustment and not a
postapproval change (4).
A systemat ic approach should
replace the sti l l common “screen-
ing,” also known as a trial-and-error
approach, in which one factor at a
time (OFAT) is varied until the best
method is found. The OFAT approach
is time-consuming and often results
in a nonrobust method because
interactions between factors are not
considered.
Today, systematic concepts use
experimental design plans as an effi-
cient and fast tool for method develop-
ment. In a full or fractional, factorial
design, a couple experiments are car-
ried out in which one or more factors
are changed at the same time. By using
statistical software tools (for example,
Design Expert from Stat-Ease, Inc.),
the effect of each factor on the separa-
tion can be calculated and the data can
be used to find the optimum separa-
tion (4). In our laboratory, this concept
is used when the development of non-
chromatographic methods is necessary.
However, the easiest and fasted way
of developing a liquid chromatographic
method is by using chromatography
modeling, especially in combination
with ultrahigh-pressure liquid chro-
matography (UHPLC) technology.
Kromasil Chiral
For faster chromatography
0 0.75 1.5[min]
Flow rate: 4.5 ml/min
0 2 4 6[min.]
0 1 2 3[min]
Flow rate: 1.0 ml/min
Flow rate: 2.0 ml/min
Baseline separation in less than 1 minute
Solute: Tröger’s baseMobile phase: Heptane/2-Propanol/DEA (90/10/0.1) Stationary phase: Kromasil AmyCoat, 3 μmColumn size: 4.6 x150 mmTemperature: 22°CDetection: UV @ 220 nm
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128 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
Based on a small number of experi-
ments, these software applications can
predict the movement of peaks when
parameters such as eluent composition
or pH, f low rate, column temperature,
column dimensions, and particle size
are changed (5–11). When necessary,
the developed method can be trans-
ferred (back) to high performance liq-
uid chromatography (HPLC).
In our laboratory we have been using
visual chromatographic modeling (soft-
ware packages) for many years now in
HPLC and UHPLC method develop-
ment and it has resulted in very robust
methods (4,12–14). The aim of this study
was to apply quality-by-design prin-
ciples to build in a more scientific and
risk-based, multifactorial strategy in the
development of a new UHPLC method
for testing the purity of omeprazole.
Omeprazole belongs to the group
of proton-pump inhibitors and is one
of the most widely prescribed drugs. It
suppresses gastric acid secretion by spe-
cific inhibition of the enzyme hydrogen-
potassium adenosine triphosphatase (H+,
K +-ATPase). Omeprazole formulations
are used to treat acid reflux, heartburn,
ulcer disease, and gastritis (15).
Omeprazole is described in the mono-
graph of the European Pharmacopeia (EP)
(16). Purity testing for omeprazole is
accomplished by using HPLC with UV
detection on a 125 mm × 4.6 mm, 5-μm
NameOmeprazole Impurity A (EP)
Impurity C (EP)Impurity B (EP)
Impurity D (EP)
Impurity F (EP) Impurity G (EP)
Impurity I (EP)Impurity H (EP)
Impurity E (EP)
OCH3
CH3
CH3
CH3
CH3
CH3
CH3
Cl
Cl
CH3
CH3
CH3
CH3
CH3
CH3
CH3
CH3
CH3
OCH3
OCH3
SH
OCH3
OCH3
OCH3
OCH3
OCH3
OCH3
OCH3
OCH3
H3CO
H3C
OCH3
OCH3
H3C
H3C
H3C
H3C H
3C
H3C
H3C
H3C
HN
N
HN
N
HN
N
HN
N
HN
N
N
N
N
N
HN
N
N
N
N
N
N
N
N
N
N
S
S
S
S
S
S
S
S
S
S
O
O
O
O
O O O
O
O
OO
OS
O
O
O
O
O
HN
N
HN
N
HN
N
N
HN
N
N
NH
N
N
NH
NS
S
N
OCH3
OCH3
OCH3
OCH3
OCH3
OCH3
OH3C
H3C
H3C
Chemical Structure Name Chemical Structure
Figure 1: Chemical structures of omeprazole and its related impurities.
Omeprazole
Time (min)
Time (min)
4 6 8 10
403020100
Imp
.H
Imp
.D
Imp
.D
Imp
.B
Imp
.B
Imp
.F–G
Imp
.F+G
Imp
.E
Imp
.E
Imp
.AIm
p.I
Imp
.AIm
p.I
Imp
.C
Figure 2: Typical chromatogram of a selectivity standard solution containing omeprazole and its related impurities A–I by using the purity method published in the European Phar-macopoeia. Column: 125 mm × 4.6 mm, 5-μm dp Symmetry C8 column; mode: isocratic; eluent: 27 vol% acetonitrile and 73 vol% disodium hydrogen phosphate [1.4 g/L], adjusted with phosphoric acid to pH 7.6; flow rate: 1 mL/min.
T(ºC)
tG(min)
pH
Figure 3: Graphical description of the design of experiments plan for the method development by using chro-matographic modeling: For each organ-ic eluent, methanol and acetonitrile, 12 experiments have to be performed with low and high values for T, tG, and pH.
Please visit us at PITTCON, Booth #3813 and ArabLab, Booth #1013
130 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
dp C8 column in isocratic mode with an
eluent consisting of 27 vol% acetonitrile
and 73 vol% disodium hydrogen phos-
phate solution (pH 7.6) and a flow rate
of 1.0 mL/min. On the basis of the syn-
thetic route, the monograph recommends
testing the impurities A, B, C, D, E, H,
and I by HPLC, and the impurities F
and G have to be tested by a photometric
method (chemical structures are shown
in Figure 1). A typical chromatogram of
a selectivity standard solution containing
omeprazole and its related impurities A–I
obtained using the EP method is given
in Figure 2 and shows that the method
was developed without any chromatog-
raphy knowledge. Some of the impurity
peaks show coelution, but the last three
peaks are separated from each other with
a huge distance of 10 min each.
Several analytical procedures for the
determination of omeprazole and its
related impurities have been described.
A review of the analytical methodolo-
gies for the determination of omepra-
zole, mostly in plasma and urine, was
published in 2007 (17). Only some
recent publications focus on stability-
indicating methods for the analysis of
impurities and degradation products in
omeprazole formulations (18–20). As
far as we know, no analytical method
has been published that would separate
all synthesis impurities and degradation
products mentioned in the EP mono-
graph. Therefore, there is a need for a
simple, fast, and reliable purity method
for the determination of omeprazole
and its related impurities in the active
pharmaceutical ingredient (API) and in
pharmaceutical formulations.
Experimental
Chemicals
Methanol and acetonitrile were HPLC-
gradient grade (Sigma). All other chemi-
cals were at least analytical grade and
were also purchased from Sigma. Ultra-
pure water was obtained using a TKA
water purification system (Thermo
Fisher Scientific).
Equipment and Chromatographic
Conditions
For the UHPLC experiments, an
Acquity UPLC H-class system consist-
ing of a quaternary solvent system with a
solvent-selection valve, a sample injection
Figure 4: Three-dimensional resolution cube (tG/T/pH model) and the corresponding two-dimensional resolution map (tG/T model) at pH 9.0 for methanol as the organic solvent in the UHPLC gradient method. The red regions in the resolution maps repre-sent the design space, in which the performance criteria are met.
Figure 5: Three-dimensional resolution cube (tG/T/pH model) and the corresponding two-dimensional resolution map (tG/T model) at pH 8.75 for acetonitrile as the organic solvent in the UHPLC gradient method. The large red regions in the resolution maps represent the design space, in which performance criteria are met.
8.5
pH
2.20
2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00 5 10tG (min)
30
40
50
60
T (
°C)
9
8
2.40
T (°C)
0.8
5.5
5
40
60
46.9
tG (min)
60
50
40
30
2.20
2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00 5
T (
°C)
tG (min)
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132 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
system, column management system, and a photodiode-array
detector, all controlled by Empower 2 C/S-software (Waters)
was used. The dwell volume of the system was 0.400 mL.
For the HPLC experiments an Alliance 2695 XE system
with a model 2996 photodiode-array detector, controlled by
Empower 2 C/S-software (Waters) was used. The dwell vol-
ume of the system was 1.000 mL.
A 50 mm × 2.1 mm, 1.7-μm dp Acquity UPLC BEH
C18 column (Waters) was used in the UHPLC study and
the equivalent 50 mm × 4.6 mm, 2.5-μm dp XBridge BEH
Table I: Verification study for the newly developed UHPLC method. A comparison of predicted and experimental
retention times of all components at the working point and six verification points are shown below and found
to be excellent with a correlation coefficient of R2 = 0.999, which can also be seen in the corresponding graphical
comparison (Figure 8a).
Working Point Verification
Point 1
Verification
Point 2
Verification
Point 3
Verification
Point 4
Verification
Point 5
Verification
Point 6
Flow rate (mL/min)
0.70 0.70 0.75 0.70 0.65 0.65 0.75
tG (min) 4.0 3.9 4.1 4.0 3.9 4.1 4.0
Temp. (°C) 35 37 33 33 35 35 37
pH 8.75 8.75 8.75 9.00 9.00 8.50 8.50
%start 10 9 10 11 10 11 9
%end 60 60 61 60 61 59 59
Retention time (min)
Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp.
Imp. A 1.06 1.14 1.13 1.18 1.04 1.09 0.96 1.08 1.09 1.15 1.07 1.21 1.10 1.19
Imp. I 1.45 1.48 1.50 1.52 1.37 1.41 1.30 1.32 1.43 1.46 1.54 1.61 1.53 1.62
Imp. E 1.71 1.74 1.75 1.77 1.65 1.68 1.57 1.59 1.69 1.73 1.81 1.86 1.77 1.85
Imp. D 1.97 2.00 2.01 2.02 1.91 1.93 1.79 1.83 1.90 1.91 2.14 2.18 2.07 2.16
Imp. B 2.17 2.21 2.20 2.21 2.11 2.14 2.06 2.08 2.15 2.18 2.30 2.32 2.22 2.30
Omeprazole 2.26 2.29 2.28 2.29 2.20 2.22 2.15 2.18 2.24 2.27 2.38 2.40 2.30 2.38
Imp. H 2.68 2.72 2.68 2.70 2.62 2.65 2.58 2.62 2.65 2.68 2.84 2.85 2.72 2.80
Imp. C 2.96 2.99 2.95 2.96 2.90 2.92 2.91 2.93 2.96 2.98 3.11 3.10 2.96 3.04
Imp. F 3.68 3.71 3.64 3.65 3.62 3.65 3.66 3.67 3.67 3.69 3.88 3.84 3.66 3.71
Imp. G 3.82 3.84 3.76 3.77 3.75 3.78 3.79 3.81 3.80 3.82 4.02 3.97 3.79 3.84
Time (min)
2.257Omeprazole
1.0
64 Im
p.A 1.5
40 Im
p.I
1.7
10 Im
p.E
1.9
72 Im
p.D
2.1
73 Im
p.B
2.6
83 Im
p.H
2.9
64 Im
p.C
3.6
85 Im
p.F
3.8
17 Im
p.G
3.0 4.02.01.00
Figure 6: Predicted UHPLC chromatogram for omeprazole and its related impurities for conditions at the working point (for details see text).
Time (min)
3.0 4.02.01.0
1.1
44 Im
p. A
1.4
79 Im
p. I
1.7
43 Im
p. E
2.0
02 Im
p. D
2.0
10 Im
p. B
2.7
18 Im
p. H
2.9
88 Im
p. C
3.7
11 Im
p. F
3.8
40 Im
p.G
2.293 Omeprazole
Figure 7: Experimental UHPLC chromatogram of omeprazole spiked with its related impurities A–I for conditions at the working point (for details see text).
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134 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
C18 column (Waters) was used in the
HPLC study.
All method development experi-
ment s were per formed on the
UHPLC system in gradient mode.
Eluent A was 10 mM ammonium
bicarbonate buffer at dif ferent pH
values (adjusted with ammonia) and
eluent B was acetonitrile. Eluent C
was methanol (for screening experi-
ments only). The f low rate was set to
0.7 mL/min and the injection volume
was 2 μL.
The temperature in the experi-
ments was optimized between 30 °C
and 60 °C. The UV detection of the
compounds of interest was carried out
at 303 nm and the UV spectra were
taken in the range of 200–400 nm.
Software
For chromatography modeling the
DryLab 4.0 software package (Mol-
nar-Institute) was used. The software
package includes PeakMatch and
3-D-Robustness modules.
Standard Preparation
A selectivity standard solution con-
ta in ing 0.2 mg/mL omepra zole
(in-house standard substance) and
approximately 0.002 mg/mL of each
of the nine impurities was prepared
with a 2:8 (v/v) mixture of acetoni-
trile and 10 mM ammonium bicar-
bonate buffer as the solvent. The
impurities A, B, C, E, H, and I were
obta ined from LGC. Impurity D
was purchased from the European
Directorate for the Quality of Medi-
cines (EDQM) and the impurities F
and G were obtained from the U.S.
Pharmacopeia l Convention (USP).
The selectivity standard solution was
protected from light by using amber
glassware.
Results and Discussions
Development Strategy
Our development strategy (4) follows
quality-by-design principles and can
be divided into six steps as follows:
Step 1: Definition of Method Goals
Our primary goal was to develop
a stability-indicating method that
separates the API from all impurities
Figure 8: Plots of experimental retention time versus predicted retention time for (a) the UHPLC method and (b) after method transfer to HPLC.
4.50(a)
4.00
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.000.00 1.00 2.00
Predicted retention time (min)
y=0.9813x + 0.0795R2 = 0.999
Exp
eri
me
nta
l re
ten
tio
n t
ime
(m
in)
3.00 4.00 5.00
7.00
Exp
eri
me
nta
l re
ten
tio
n t
ime
(m
in)
6.00
5.00
4.00
3.00
2.00
1.00
0.000.00 1.00
Predicted retention time (min)
2.00 3.00 4.00 5.00 6.00 7.00
y=0.952x + 0.1024R2 = 0.999
(b)
Triazole Bonded Stationary Phase
Alternative Selectivity for HILIC Analysis
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136 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
with a critical resolution (R s,crit) of no
less than 2.0. To speed up the devel-
opment process, UHPLC technol-
ogy was used; the f inal method was
intended to be transferred to HPLC.
Step 2: Risk Assessment
Using a fishbone diagram, an early risk
assessment was identified and possible
risk factors associated with sample
preparation as well as the instrumen-
tal analysis were prioritized. The ini-
tial list of potential parameters that
can affect critical quality attributes
(CQAs) were ranked and priori-
tized using failure mode and effects
analysis (FMEA).
It was obvious that resolution is a
CQA and the selectivity term α in
the general equation Rs = 0.25N1/2[(α
- 1)/α][k/(1 + k)] has the greatest
impact on the resolution. Selectiv-
ity is inf luenced by the mobile phase
composition, column chemistry, and
temperature (21), and the inf luence
should be investigated by design of
experiments (DoE).
Other CQAs that were taken into
account include the robustness of the
method and the run time.
Step 3: Design of Experiments
For the critica l process parameters
(CPPs), which have an impact on
the CQAs, experiments should be
conducted to determine accept-
able ranges. As the result of the risk
assessment, the four parameters gra-
dient time (tG), temperature (T ), pH
of the aqueous eluent A, and type of
the organic eluent B were screened
and opt imized because of their
strong known inf luential effects on
selectivity.
A set of 12 experiments was per-
formed for each of the two organic
eluents methanol and acetonitri le
under the following conditions: gra-
dient times: tG1 = 3 min and tG2 = 9
min; temperatures: T1 = 30 °C and
T2 = 60 °C. The pH values of the
buffer were pH1: 8.0, pH2: 8.5, and
pH3: 9.0. Because of prior knowl-
edge, a modern C18 column was used.
The ranges between these factors
were large enough to induce peak
This QbD
strategy can
be divided
into six steps,
from defining
the goals of
the method
through
continual
improvement.
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138 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
movements to discover hidden peaks
(4). A graphical description of the
DoE plan can be seen in Figure 3.
Step 4: Design Space
The retention times of all peaks of
interest in the 12 experiments were
entered into the chromatographic
modeling software and matched in
each of the chromatograms by using
the PeakMatch module.
Based on the limited set of only 12
experiments, the modeling software
builds a three-dimensional model
of the critica l resolution (the so-
called “knowledge space”), in which
the combined inf luence of the opti-
mized parameters are visualized. The
modeling software uses a color code
to represent the value of the critical
resolution: Warm, “red” colors show
large resolution values (Rs > 2.0), and
cold, “blue” colors show low resolu-
tion values (R s < 0.5) corresponding
to regions of peak overlaps. The red
geometric bodies within the knowl-
edge space, in which the performance
criteria are met, is called the design
space. The ICH Q8 guideline defines
the design space as follows (3):
“The multidimensional combination
and interaction of input variables
(e.g., material attributes) and pro-
cess parameters that have been dem-
onstrated to provide assurance of
quality. Working within the design
space is not considered as a change.
Movement out of the design space is
considered to be a change and would
normally initiate a regulatory post
approval change process.”
Figures 4 and 5 show the three-
dimensiona l resolution cubes for
methanol and acetonitri le as the
organic eluent in the UHPLC gradi-
ent method. A visual inspection shows
that the design space in the methanol
cube is much smaller than the design
space in the acetonitrile cube. That
means that the method with acetoni-
trile is more robust than the method
with methanol and the all peaks in the
chromatogram are well separated from
each other (baseline resolution).
An important
part of the
method
development
strategy is
to perform
robustness
testing of
the method
before the
validation
study.
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Therefore, acetonitri le was cho-
sen as the organic eluent and, from
the corresponding design space, the
working point was selected by visual
examination. There are several possi-
ble alternative working points within
the design space, but we looked for
the highest critical resolution (R s,crit)
and best robustness of the method.
This working point was found in the
cube at tG 4.0 min, T 35 °C, and pH
8.75. The predicted and experimen-
tal chromatograms for this working
point are shown in Figures 6 and 7.
A verif ication study comparing
predicted and experimental retention
times for the working point and six
verif ication points around the work-
ing point, but within the design space,
was found to be excellent with a cor-
relation coefficient of 0.999, as shown
in Table I and Figure 8a. This is also
in compliance to previous reported
data (4,22,23).
An important part of our method
development strategy is to perform
robustness testing of the developed
method before the validation study.
The ICH guideline Q2 (R1) (24)
defines robustness as follows:
“[. . .] the reliability of an analysis
with respect to deliberate variations
in method parameters. The robust-
ness of an analytical procedure is
a measure of its capacity to remain
unaffected by small, but deliberate
variations in method parameters
and provides an indication of its re-
liability during normal usage.”
The robustne s s of the deve l-
oped method was stud ied using
the robustness module of the chro-
matographic modeling software. In
a three-level, ful l-factoria l design,
the module used the previously con-
structed and verif ied design space
for “ in si l ico” robustness ca lcula-
tions (4). The six parameters tG (4
min ± 0.1 min), T (35 °C ± 2 °C),
pH (8.75 ± 0.1), f low rate (0.7 mL/
min ± 0.05 mL/min), and the %B
start (10% ± 1%) and %B end (60%
± 1%) of the gradient were varied at
three levels (+1, 0, -1).
Figure 9 shows the frequency of the
distribution of the resolution values
Rs,crit for all 729 experiments. It can
be seen that the required resolution of
2.0 can be reached in all experiments.
Therefore, the developed method is
robust against small changes of chro-
matographic parameters.
A formal validation study should
be performed before this new method
can replace the existing method.
Step 5: Method Control Strategy
The ICH Q8 guideline def ines the
control strategy as “a planned set of
controls, derived from current prod-
uct and process understanding that
ensures process performance and
product quality[. . .]” This means
that the control strategy should
be implemented to ensure that the
developed method is performing as
intended. Usually, this can be done
by using a system suitability test. In
our method development strategy,
the resolution of the critical peak pair
(R s,crit), was chosen as a system suit-
ability test parameter and should not
be less than 2.0.
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Step 6: Continual Improvement
In this last step further experiments can be planned and
repeated to try out better columns and eluents to further
Table II: Verification study after the method transfer to HPLC. A comparison of predicted and experimental
retention times of all components at the working point and six verification points are shown below and
found to be excellent with a correlation coefficient of R2 = 0.999, which can also be seen in the corresponding
graphical comparison.
Working Point Verification
Point 1
Verification
Point 2
Verification
Point 3
Verification
Point 4
Verification
Point 5
Verification
Point 6
Flow rate (mL/min)
1.9 1.9 2.0 1.9 1.8 1.8 2.0
tG (min) 7.0 6.8 7.2 7.0 6.8 7.2 6.8
Temp. (°C) 35 37 33 33 35 35 37
pH 8.75 8.75 8.75 9.00 9.00 8.50 8.50
%start 10 9 10 11 10 11 9
%end 60 61 61 60 61 59 59
Retention time (min)
Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp. Pred. Exp.
Imp. A 1.51 1.64 1.59 1.71 1.52 1.61 1.37 1.49 1.51 1.69 1.52 1.56 1.59 1.67
Imp. I 2.10 2.09 2.18 2.19 2.05 2.04 1.84 1.83 1.99 2.02 2.21 2.19 2.26 2.26
Imp. E 2.54 2.49 2.61 2.57 2.50 2.44 2.31 2.25 2.43 2.42 2.66 2.55 2.66 2.58
Imp. D 3.01 2.98 3.06 3.05 2.95 2.92 2.69 2.65 2.81 2.81 3.24 3.20 3.18 3.17
Imp. B 3.35 3.26 3.38 3.31 3.31 3.21 3.15 3.06 3.24 3.19 3.51 3.36 3.43 3.31
Omeprazole 3.50 3.40 3.52 3.44 3.45 3.35 3.31 3.21 3.39 3.32 3.66 3.50 3.56 3.44
Imp. H 4.24 4.13 4.23 4.14 4.20 4.09 4.06 3.94 4.10 4.03 4.46 4.28 4.28 4.15
Imp. C 4.73 4.59 4.69 4.58 4.70 4.55 4.64 4.51 4.65 4.55 4.92 4.72 4.70 4.54
Imp. F 6.00 5.84 5.90 5.77 5.97 5.81 5.95 5.77 5.89 5.78 6.27 6.05 5.90 5.73
Imp. G 6.23 6.08 6.12 5.99 6.20 6.04 6.18 6.03 6.10 6.00 6.52 6.29 6.12 5.95
60
40
N
20
2.12 2.17 2.22 2.27
Rs, crit
2.32 2.370
Figure 9: Frequency distribution of the Rs,crit values for all 729 experiments of the robustness study on the UHPLC system. The six parameters tG (4 min ± 0.1 min), T (35 °C ± 2 °C), pH (8.75 ± 0.1), flow rate (0.7 mL/min ± 0.05 mL/min), and the %B start (10% ± 1%) and %B end (60% ± 1%) of the gradient were var-ied at three levels (+1, 0, -1). All experiments fulfill the require-ment for resolution Rs,crit no less than 2.0. That means that the failure rate is 0, so there will be no method-related out-of-specification (OOS) results and production quality control will be smooth and robust.
Time (min)
3.0 4.0 5.0 6.02.01.0
1.5
06 Im
p. A
2.0
98 Im
p. I
2.5
43 Im
p. E
3.0
06 Im
p. D
3.3
51 Im
p. B
4.2
40 Im
p. H
4.9
731 Im
p. C
5.9
96 Im
p. F
6.2
26 Im
p. G
3.495 Omeprazole
Figure 10: Predicted HPLC chromatogram for omeprazole and its related impurities for conditions after the transfer to the HPLC system (for details see text).
adjust or improve the position of the working point. In
addition, business needs — for example, the transfer of
the developed UHPLC method (such as from the research
and development [R&D] laboratory) to HPLC conditions
(such as into the quality control [QC] laboratory) — can
be taken into account.
To transfer the UHPLC method to HPLC conditions,
the changed column dimensions, particle sizes, and system
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dwell volumes were used to scale up
the f low rate and gradient time. This
can be made by using free available
method transferring tools (such as the
Acquity Columns Calculator from
Waters). A smart way is to use the
modeling software for the transfer
and calculate the gradient time and
f low rate. At the same time, the cor-
responding chromatograms can be
visualized.
Small adjustments of the scaled
conditions for f low rate and gradient
time had to be made to reduce the
back pressure in the HPLC system.
The predicted and experimental chro-
matograms for the up-scaled HPLC
method can be seen in Figures 10 and
11. A second verification study for the
working point on the HPLC system
and six verification points around the
working point conf irmed the accu-
racy of the prediction (see Table II
and the corresponding graph in Fig-
ure 8b). In addition, the robustness
study after the transfer to the HPLC
system shows that the failure rate is
still zero (see Figure 12).
Table III summarizes the chromato-
graphic parameters and tolerances of
the final method.
Conclusions
A quality-by-design–based method
development strategy for a method
to test the purity of omeprazole has
been presented here. The scientif ic
and risk-based multifactorial method
development strategy uses visua l
chromatographic modeling as a fast
and easy to use development tool.
To speed up the method develop-
ment process, all experiments were
performed on a UHPLC system. The
final method was successfully trans-
ferred to HPLC conditions. Verifica-
tion studies between predicted and
experimental retention times confirm
the accuracy of the chromatographic
modeling process.
All experiments, from the plan-
ning, performing on the UHPLC
system, verif ication and transfer to
HPLC, to the reporting, were made
within one week.
References
(1) J.M. Juran, Juran on Quality by Design:
The New Steps for Planning Quality into
Goods and Services (The Free Press, New
York, 1992).
(2) http://www.fda.gov/downloads/Drugs/
Development Approva lProcess/Manu-
facturing/QuestionsandAnswersonCur-
rent Good Ma nu f ac tu r ingPr ac t ic e s c -
GMPforDrugs/UCM176374.pdf.
(3) http://www.ich.org/f i leadmin/Public_
Web_ Site/ICH_Products/Guidel ines/
Quality/Q8_R1/Step4/Q8_R2_Guide-
line.pdf.
Table III: Description of the final analytical procedure including the tolerance limits
Chromatographic
Parameter
UHPLC Condition HPLC Condition
Column50 mm × 2.1 mm, 1.7-μm dp Acquity BEH C18 (Waters)
50 mm × 4.6 mm, 2.5-μm dp
XBridge BEH C18 (Waters)
Eluent A10 mM ammonium bicarbonate buffer, pH 8.75 (±0.1 pH units)
10 mM ammonium bicarbonate buffer, pH 8.75 (±0.1 pH units)
Eluent B Acetonitrile Acetonitrile
Gradient
Linear increase from 10% (±1%) to 60% (±1%) of eluent B in 4.0 min (±0.05 min), followed by reequilibration
Linear increase from 10% (±1%) to 60% (±1%) of eluent B in 7.0 min (±0.5 min), followed by re-equilibration
Stop time 5 min 8 min
Flow rate 0.70 mL/min (±0.05 mL/min) 1.90 mL/min (±0.05 mL/min)
Column temp. 35 °C (±2 °C) 35 °C (±2 °C)
Injection volume 2 μL 20 μL
Detection UV absorbance at 303 nm UV absorbance at 303 nm
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146 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
(4) A.H. Schmidt and I. Molnár, J. Pharm.
Biomed. Anal. 78–79, 65–74 (2013).
(5) L.R. Snyder and J.L. Glajch, Computer-
assisted Method Development for High
Performance Liquid Chromatography,
(Elsevier, Amsterdam, 1990).
(6) L.R. Snyder and J.L. Glajch, J. Chro-
matogr. A 485, 1–675 (1989).
(7) I. Molnár, J. Chromatogr. A 965, 175–
194 (2002).
(8) I. Molnár, H.-J. Rieger, and K.E. Monks,
J. Chromatogr. A 1217, 3193–3200 (2010).
(9) I. Molnár and K.E. Monks, Chromato-
graphia 73(Suppl.1), 5–14 (2011).
(10) K. Jayaraman, A.J. Alexander, Y. Hu,
and F.P. Tomasella, Anal . Chim. Acta
696, 116–124 (2011).
(11) K. Monks, I. Molnár, H.-J. Rieger, B.
Bogáti, and E. Szabó, J. Chromatogr. A
1232, 218–230 (2012).
(12) A.H. Schmidt and I. Molnár, J. Chromatogr.
948, 51–63 (2002).
(13) A.H. Schmidt, J. Liq. Chromatogr. Relat.
Technol. 28, 871–881 (2005).
(14) A.H. Schmidt, M. Stanic, and I. Molnár, J.
Pharm. Biomed. Anal., 91, 97–107 (2014).
(15) Commentary of the European Pharmacopoeia
(in German), 38 supplement, Deutscher
Apotheker Verlag, Stuttgart (2011).
(16) “Monograph Omeprazole” in the European
Pharmacopoeia, Seventh ed. (Deutscher
Apotheker Verlag, Stuttgart, 2011).
(17) M. Espinosa Bosch, A.J. Ruiz Sanchez,
F. Sanchez Rojas, and C. Bosch Ojeda, J.
Pharm. Biomed. Anal. 44, 831–844 (2007).
(18) C. Iuga, M. Bojita, and S.E. Leucuta,
Farmacia 57, 534–541 (2009).
(19) K.B. Borges, A.J.M. Sanchez, M.T.
Pupo, P.S. Bonato, and I.G. Collado, J.
AOAC Int. 93, 1811–1820 (2010).
(20) P. Venkata Rao, Ch.K. Sanjeeva Reddy,
M. Ravi Kumar, and Danta Durga Rao,
J. Liq. Chromatogr. Relat. Technol . 35,
2322–2332 (2012).
(21) L .R. Snyder, J.J. Kirk land, and J.L .
Glajch, Practical HPLC Method Develop-
ment, 2nd ed. (Wiley-Interscience, New
York, 1997).
(22) M.R. Euerby, G. Schad, H.-J. Rieger,
and I. Molnár, Chromatogr. Today 3,
13–20 (2010).
(23) K.E. Monks, H.-J. Rieger, and I. Mol-
nár, J. Pharm. Biomed. Anal. 56, 874–
879 (2011).
Time (min)
3.0 4.0 5.0 6.02.01.0
1.6
32 Im
p. A
2.4
90 Im
p. E
2.0
90 Im
p. I
2.9
79 Im
p. D
3.2
60 Im
p. B
4.1
30 Im
p. H
4.5
91 Im
p. C
5.8
40 Im
p. F
6.0
67 Im
p. G
3.401 Omeprazole
Figure 11: Experimental HPLC chromatogram of omeprazole spiked with its relat-ed impurities A–I for conditions after the transfer to the HPLC system (for details see text).
Contact Us if You Want to Try Our Products
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(24) http://www.ich.org/f i leadmin/Public_
Web_ Site/ICH_Products/Guidel ines/
Quality/Q2_R1/Step4/Q2_R1_Guide-
line.pdf.
Alexander H. Schmidt is quality
control director at Steiner Pharmaceuticals
in Berlin, Germany. He is also head of
analytical development of an R&D and
contract analysis lab and supervises 35 lab
assistants and chemists. Over the years,
he has published numerous articles on
HPLC and UHPLC method development
for pharmaceuticals and complex natural
compound mixtures. He is also a guest
lecturer at the Beuth University of Applied
Sciences, in Berlin, Germany. In addition,
he is currently writing his doctoral thesis
at the Institute of Pharmacy at Freie
Universität Berlin in Germany.
Mijo Stanic joined the development
team at Steiner Pharmaceuticals as a lab
assistant and was promoted to deputy
lab manager in early 2013.
Direct correspondence to:
For more information on this topic,
please visit
www.chromatographyonline.com
80
60
N 40
20
02.13 2.18 2.23 2.28
Rs, crit
2.33
Figure 12: Frequency of the distribution of the resolution values Rs,crit for all 729 experiments of the robustness study after the transfer to the HPLC system. The six parameters tG (7 min ± 0.1 min), T (35 °C ± 2 °C), pH (8.75 ± 0.1), flow rate (1.9 mL/min ± 0.1 mL/min), and the %B start (10% ± 1%) and %B end (60% ± 1%) of the gradient were varied at three levels (+1, 0, -1). All experiments still fulfill the requirement for resolution Rs,crit of no less than 2.0. That means that the failure is also 0.
FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 149www.chromatographyonline.com
PITTCON PRODUCT SHOWCASE
Autosampler syringesHamilton’s CTC PAL autos-ampler syringes for gas chromatography and liquid chromatography applications are designed to comple-ment the company’s exist-ing autosampler syringes. According to the company, the design of the plunger and flange of its C-Line Syringe ensures reli-able installation, and its X-Type syringes, developed with CTC Analytics for HPLC applications, have near-zero carryover. Hamilton Company,
Reno, NV. www.hamiltoncompany.com
SPE systemThe EconoTrace automated solid-phase extraction sys-tem from FMS is designed to increase laboratory sam-ple throughput. According to the company, the system is modular and expandable, uses any SPE cartridge format, and can be used to isolate analytes from liquid matrices such as urine, blood, water, milk, and beverages. FMS, Inc.,
Watertown, MA. www.fms-inc.com
GC autosamplerThe Flex Series autosampler from EST Analytical is designed for GC and GC–MS laboratory end users and OEM custom-ers. According to the company, the autosampler has liquid injection capabil-ity with an upgrade path to headspace or SPME analysis. The system reportedly was designed with machine-to-machine industrial wireless technology and is expandable. EST Analytical,
Fairfield, OH. www.estanalytical.com
Ceramic ion source for GC–NPDThe TID-10 ceramic ion source from DETector Engineering is designed to produce catalytic combustion ioniza-tion of compounds containing chains of methylene functional groups. According to the company, the ceramic ion source replaces the ion source used in GC–NPD equipment, and expands the use of that equipment to selective detection of paraffins, isopar-affins, olefins, FAMEs, and triglycerides in complex petroleum and biological samples. DETector Engineering & Technology, Walnut Creek, CA. www.det-gc.com
Report development and generation softwareBruker Dash Reporting soft-ware, from Bruker Chemi-cal and Applied Markets is designed to provide custom-ized reporting that centers on Dash Designer, a purpose-built standalone application that allows users to position and closely format report ele-ments, and preview reports with relevant data. According to the com-pany, individual elements can be sorted, filtered, resized, and formatted with common editing operations and advanced functions. Bruker Corporation, Fremont, CA. www.bruker.com
UHPLC sealThe Enduris UHPLC seal from Bal Seal Engineering is designed to provide con-sistent, long-term performance in liquid chromatography pumps at pressures of 22,000 psi and higher. According to the company, the seal is machined from precision-formulated blends of ultra-high-molecular-weight polyethylene or PTFE and uses a Bal Seal Canted Coil Spring energizer to promote uniform wear and longer service life. Bal Seal Engineering, Inc.,
Foothill Ranch, CA. www.balseal.com
2D-LC systemThe model 1290 2D-LC sys-tem from Agilent Technologies is designed with peak-triggered operation, “shifted gradients,” and valve technology for com-prehensive or heart-cutting 2D-LC analysis. According to the company, the system is beneficial for the analysis of complex samples because it performs a single ultrahigh peak capacity 2D-LC run instead of many conventional separations. Agilent Technologies, Santa Clara, CA. www.agilent.com
Mass detectorThe Acquity QDa mass detector from Waters is designed to provide mass spectral data for chromato-graphic separations. According to the company, the detector is no larger than a photodiode-array detec-tor and, when paired with the company’s UPLC, LC, or SFC system, it generates the mass spectral data expected of a single-quadrupole mass spectrometer. Waters,
Milford, MA.www.waters.com
150 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
GC system optionsNew options for Thermo Scientific’s Trace 1300 Series GC system are designed to conserve helium, permit use of multiple detectors simulta-neously, automate sampling gas workflows, and perform flame photometric detection. According to the company, the options include the Instant-Connect Helium Saver module; the Trace 1310 high-capacity auxiliary oven with multivalve, multicolumn capacity; the Dedicated Instant Con-nect flame photometric detector; and the Instant Connect gas sampling valve module. Thermo Fisher Scientific, Waltham, MA. www.thermoscientific.com/trace1300
SorbentsSupelco’s Supel QuE Z-Sep, Z-Sep/C18, and Z-Sep+ sorbents are designed to provide robust LC–MS and GC–MS methods for a variety of analytes in difficult matrices. According to the company, the Z-Sep family of sorbents is available in 2-mL and 12-mL tub formats for QuEChERS. Supelco/Sigma-Aldrich,
Bellefonte, PA. www.sigma-aldrich.com/zsep
HPLC columnsThe IC YS-50 polymer-based ion chromatography column from Shodex is designed for cation analysis applicable to both suppressor and non-suppressor methods. According to the company, the column can support the analysis of alkylamines such as adrenaline, dopamine, noradrenaline, ace-tylcholine, and choline. Applica-tions reportedly are available from the company’s database.Showa Denko America, Inc.,
New York, NY. www.shodex.net
Photodiode-array detectorShimadzu’s SPD-M30A photo-diode-array detector is designed for a variety of HPLC and UHPLC conditions and report-edly can be used for a range of analyses without replacing its capillary cell. According to the company, the detector’s capil-lary cell allows the peak from the principal component and a 0.005% infinitesimal peak to be quantified simultaneously. Shimadzu Scientific Instruments,
Columbia, MD. www.ssi.shimadzu.com
M icrochannel platesA long-life, low noise performance (L3N) option is available from Photonis for its microchannel plate (MCP) formats. According to the company, the option provides a 100-fold reduction in background noise when compared to traditional long-life MCPs, and any MCP made by Photonis can be ordered with the low-noise performance option. Photonis USA,
Sturbridge, MA.www.photonis.com
LC–MS nitrogen generatorThe Parker Balston NitroFlow 60 LC–MS membrane nitrogen generator from Parker Hannifin is designed to produce up to 60 slpm of pure LC–MS-grade nitrogen at pressures as high as 110 psig. According to the com-pany, the output flow produced by the generator is equivalent to using one cylinder of com-pressed gas every 2 h. Parker Hannifin
Corporation,
Haverhill, MA. www.parker.com
Ion chromatography systemMetrohm’s 940 Professional IC Vario modular, self-monitoring ion chromatography system is designed with options that include sequen-tial, chemical, or no suppression; conductivity, UV–vis, or ampero-metric detection; high-pressure, low-pressure, and dose-in gradients; and columns of any base material, selectivity, capacity, and dimen-sion. According to the company, the instruments have a three-year warranty, a 10-year suppressor warranty, and a 10-year spare parts guarantee.Metrohm, Riverview, FL. www.metrohmuse.com
L C columnsACE UltraCore solid-core LC columns from Advanced Chromatography Technologies are designed to provide a low column back pressure and are available in SuperC18 and Super-PhenyHexyl bonding. According to the company, both phases feature proprietary encapsulated bonding technology for peak shape and phase stability across a pH range of 1.5 to 11.0. Advanced Chromatography
Technologies Ltd, Aberdeen, Scotland. www.ace-hplc.com
FEBRUARY 2014 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 151www.chromatographyonline.com
High-temperature GPC instrumentThe EcoSEC High Tempera-ture GPC system from Tosoh Bioscience is designed to provide researchers with an all-in-one temperature-controlled system that has a comprehensive temperature range of 40 °C to 220 °C. According to the company, the system comes equipped with a dual-flow refractive index detector. Tosoh Bioscience, LLC,
King of Prussia, PA. www.tosohbioscience.com
PEEK fittingsVICI Valco’s Cheminert high-pressure PEEK fittings are designed to permit direct connection of 360-μm o.d. fused silica, PEEK, stainless, or electroformed nickel tubing without hav-ing to use liners. According to the company, the 360-μm fittings in PEEK can be used safely at pressures as high as 10,000 psi. Valco Instruments Co.,
Inc., Houston, TX. www.vici.com
96-well plateUCT’s FASt 96-well plate is designed to pair with the company’s 96-well positive pressure manifold. Accord-ing to the company, the well material uses a simple “filter and shoot” prepara-tion and is effective at cleaning up urine samples for more than 50 different drugs and metabolites. UCT, Inc.,
Bristol, PA. www.unitedchem.com
Irregular silica gelsSiliaFlash irregular silica gels from SiliCycle are designed for use in flash and gravity chro-matography columns and for analytical and preparative chro-matography columns. According to the company, the gels have a narrow pore-size distribution, the absence of fines, and a long shelf life.SiliCycle,
Quebec City, Canada. www.SiliCycle.com
2nd Annual
CHROMATOGRAPHY
COMMUNITY MIXER
Buddy Guy’s
Legends Chicago
Tuesday March 4
5:30 – 8:30 p.m., 700 South Wabash Ave.Buffet, open bar, music and chromatographers galore.
Tickets required for entry
Register for tickets through your regional chromatography discussion group or chromatography vendor.
For further inquiry contact:Jonathan Edelman, PresidentWashington DC Chromatography DG(215) 850-8748 [email protected]
! Buddy Guy’s invites attendees to stay
for the evening show.
!"Help us revive the Chicago
Chromatography Discussion Group.
Join colleagues from around the world
Conversation, community, collaboration
152 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
HPLC columnsFlare HPLC columns from Diamond Analytics are designed as diamond-based columns that allow for the exploration of novel chemistries. According to the company, the columns are pH stable, can run at elevated temperatures, and can be regenerated for repeat use. Diamond Analytics,
Orem, UT. www.diamond-analytics.com
Capillary tubingPolymicro’s flexible fused-silica capillary tubing is designed with an outer diameter of 1/32 in. According to the company, the tubing mates with existing 1/32-in. fittings and is available in a range of internal diameters from 50 μm to 500 μm.Polymicro
Technologies,
Phoenix, AZ.www.polymicro.com
Sample cleanup workstationThe Freestyle workstation from Pickering Laboratories is designed for automated sample cleanup work flow. The instrument is based on a suspended rack design, with an XY robot arm for liquid handling. The workstation reportedly is able to handle multiple flask shapes with volumes ranging from 1 mL to 1 L, and the instrument’s software enables users to program multiple sample parameters and to pre-pare graphical reports and audit logs. SPE, GPC, and evaporation and solvent exchange modules are available. Pickering Laboratories, Inc.,
Mountain View, CA. www.pickeringlabs.com
Quick-connect systemThe Opti-Lynx II system from Opti-mize Technologies is designed as a combination of quick-connect hold-ers with a selection of packed-bed cartridges. According to the com-pany, accessing and changing the insert takes a quarter turn and the connection is rated up to 6000 psi. Optimize Technologies,
Oregon City, OR.www.optimizetech.com
Olfactory portThe GC SNFR olfactory port from PerkinElmer is designed to perform aroma characterization in the food, beverage, and fragrance applications. Users reportedly can capture a comprehensive sensory evaluation and correlate it with analytical data from a GC–MS system.PerkinElmer,
Waltham, MA. www.perkinelmer.com
SEC–MALS detectorThe Dawn Heleos-II multiangle light scat-tering (MALS) detector from Wyatt Technology is designed for absolute molecular weight and size determinations of poly-mers and biopolymers in solution. According to the company, the detector may be connected in series to any chromatographic system to determine absolute molar masses with-out the use of reference standards or column calibration. Wyatt Technology Corp., Santa Barbara, CA.www.wyatt.com
Water and soil sample processorOI Analytical’s model 4100 water and soil sample proces-sor is designed to automate the handling and processing of samples in 40-mL VOA vials for purge-and-trap analy-sis of volatile organic com-pounds in accordance with US EPA methods. According to the company, the instru-ment processes up to 100 drinking water, wastewater, or soil samples and operates with the company’s Eclipse 4660 purge-and-trap instruments. OI Analytical, College Station, TX. www.oico.com
S ample preparation automation systemThe AutoMate-Q40 system from Teledyne Tekmar is designed to automate the QuEChERS sample prepara-tion workflow. According to the company, the system is configured “out of the box” to conduct two QuEChERS sample preparation meth-ods: AOAC2007.01 and EN 15662.2008.Teledyne Tekmar,
Mason, OH.www.teledynetekmar.com/AutoMateQ40
EDITORS’ SERIES
PART I: Key Learning Objectives
■ What new chromatographic advances are available for the characterization of biopharmaceuticals?
■ What type of mobile phases and stationary phases should be used in reversed-phase LC for biopharmaceutical characterization?
■ What are the constraints when working with large proteins under very high pressure or temperature?
PART II: Key Learning Objectives
■ What is the classical MS-based workflow for biopharmaceutical characterization?
■ What are the benefits of using emerging approaches like native MS or ion mobility for biopharmaceutical characterization?
■ What can high resolution MS bring for biopharmaceutical characterization?
EVENT OVERVIEW:
Proteins, monoclonal antibodies (mAbs) and antibody-drug
conjugates (ADCs) are powerful therapeutic agents. Because of
their high molecular complexity, a panel of separation techniques
based on both liquid chromatography and electrophoresis has
been used for their characterization and comparability studies. In
terms of detection, mass spectrometry (MS) plays a pivotal role in
the structural elucidation of biopharmaceuticals, because it offers
an additional degree of separation by mass/charge ratio, greatly
facilitating the characterization of variants. This two-part web
seminar will discuss possibilities and limitations of chromatographic
techniques and mass spectrometry detection for the physico-
chemical characterization of biopharmaceutical compounds. Part I
will focus on chromatographic techniques, with some discussion of
ion exchange and size-exclusion methods, but primarily focusing
on reversed-phase LC, which is more compatible with MS. Part II
will focus on mass spectrometry techniques, including classical MS
analysis (intact mAb mass measurements, LC-MS analyses in reducing
conditions or after deglycosylation treatment, and peptide mapping),
enzymatic treatments for the analysis of mAb fragments, and newer
trends such as native MS, ion mobility–MS, and high resolution native
MS analysis.
Who Should Attend:
Analysts from industry, government
and academic laboratories who:■ Currently carry out the physico-chemical
characterization of biopharmaceuticals
■ Plan to work in the field of biopharmaceuticals in the near future
■ Want to learn more about recent trends in LC and MS for the analysis of biomolecules
Presenter Part I
Davy Guillarme, PhD
School of Pharmaceutical Sciences
University of Geneva
University of Lausanne
Switzerland HTMLH
Presenter Part II
Sarah Cianférani
BioOrganic Mass Spectrometry Laboratory,
Hubert Curien Pluridisciplinary Institute
University of Strasbourg,
Strasbourg, France
Moderator
Laura Bush
Editorial Director,
LCGC
Analytical Tools for the Characterization of Biopharmaceuticals
For questions, contact Kristen Moore at [email protected]
Sponsored by
Presented by
Part I: Chromatographic Methods Register free at:
www.chromatographyonline.com/methods_1
Part II: Mass Spectrometry Detection Register free at:
www.chromatographyonline.com/detection_1
ON-DEMAND WEBCASTS
154 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
Literature
CHANGING THE WAY YOU THINK ABOUT HPLC
HILIC application notesThe COSMOSIL HILIC Application Notebook from Nacalai reportedly contains close to 200 chromato-grams for the separation of polar compounds using the company’s HILIC column. According to the company, the publication also describes how mobile-phase condi-tions such as buffer pH and salt concentration influence separation in HILIC mode. Nacalai USA, San Diego, CA. www.nacalaiusa.com
Chemical ionization sourceFour application notes from LECO discuss the use of a chemical ion-ization (HR-CI) source for the com-pany’s Pegasus GC-high resolution time-of-flight mass spectrometer. According to the company, applica-tion note topics include jet fuel analysis, metabolite profiling, poly-mer extracts, and drug residues. LECO Corporation, St. Joseph, MN. www.leco.com/registration
GC postersFree GC poster packages from Restek provide wall charts paired with companion guides. According to the company, one package focuses on GC columns and includes two posters, one with tips on simplifying GC column selection, the other with solutions for GC troubleshooting. Another package offers information about GC liner selection including packing options, geometries, and dimensions, plus types of injections and how they relate to liner choice. Restek Corporation, Bellefonte, PA. www.restek.com/posters
HPLC columns product bulletinA 12-page product bulletin from Advanced Materials Technology describes its HALO-5 HPLC col-umns. According to the company, the bulletin includes charts and figures that describe the per-formance of the columns, and provides descriptions of the seven available phases (C18, C8, Phenyl-Hexyl, PFP, ES-CN, Penta-HILIC, HILIC). Advanced Materials Technology, Wilmington, DE. www.advanced-materials-tech.com
SPE cartridgesSupelMIP SPE – Patulin SPE cartridges from Supelco are designed with a molecu-larly imprinted polymer to provide sample prepara-tion for the analysis of the mycotoxin patulin in fruit matrices. According to the company, the cartridges consist of highly cross-linked polymers that are engineered to extract a single analyte of interest or a class of structurally related analytes of interest with an extremely high degree of selectivity. Supelco/Sigma-Aldrich, Bellefonte, PA. www.sigma-aldrich.com
Analytical reference materials websiteChem Service has updated its website. According to the company, on-line ordering of its analytical reference materials is now available, and customers who place an order will receive an e-mail message or a phone call from one of its sales representatives to confirm the order.Chem Service,
West Chester, PA.www.chemservice.com
Peptide mapping columnsAdvanceBio peptide map-ping columns from Neta Scientific are designed for resolution and iden-tification of amino acid modifications in primary structure. According to the company, the columns fea-ture a 120-Å pore size with superficially porous 2.7-μm particles. Neta Scientific,
Hainesport, NJ.www.netascientific.com
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Multi-Analyte Analysis of 390 Pesticide Residues, Mycotoxins, and Pyrrolizidine Alkaloids in Phytopharmaceuticals, and Herbal Food Supplements with UHPLC–HRAM–MS/MS
EVENT OVERVIEW:
Herbal food supplements and phytopharmaceuticals have
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residues, 56 mycotoxins, and 11 pyrrolizidine alkaloids using
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■ An advanced data-dependent MS/MS algorithm used for
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■ The method performance characteristics and validation
■ Analytical and economical improvements resulting from
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Who Should Attend:
■ Laboratory technicians, managers,
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Presenter
Zbynek Dzuman
Mass Spectrometry Specialist
Institute of Chemical Technology
Prague, Czech Republic (MSc.)
Moderator
Laura Bush
Editorial Director
LC/GC
For questions, contact Kristen Moore at [email protected]
156 LCGC NORTH AMERICA VOLUME 32 NUMBER 2 FEBRUARY 2014 www.chromatographyonline.com
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THE ESSENTIALS Excerpts from LCGC’s professional development platform, CHROMacademy.com
More Online:
There are only a few topics in gas chro-
matography (GC) that are responsible
for a large number of problems posed
to the “Ask the Expert” function in Chrom
Academy (www.ChromAcademy.com).
This month’s installment presents a sum-
mary of some of these topics relating to
poor peak shape and rising baselines, to act
as a guide when setting up or troubleshoot-
ing a method.
Problems with split and shouldered peaks
are typically caused by a disruption to the
way the sample band is introduced into
the GC column. Check that the column
is correctly installed into the instrument
— usually the depth of insertion into the
inlet is critical in this respect. The column
cut is absolutely critical in determining peak
shape, and one should ensure that the cut is
at 90° to the column wall and that it is clean
(not jagged or rough). The exposure of high
numbers of silanol groups and the formation
of turbulent eddies at the head of a roughly
cut column can cause major peak shape
issues. Always inspect the column cut with
a magnifier or lower-power microscope —
we cannot overemphasize the importance
of good quality column cuts at both the
inlet and detector ends of the column. The
homogeneity of the analyte band can also
be disturbed by problems with the internal
column surface at the head of the GC col-
umn. If stationary phase has been stripped,
exposing silanol groups, or if nonvolatile
sample matrix has been deposited on the
surface, the analyte band will interact differ-
ently with these areas than with the bonded
phase, causing peak splitting or shouldering.
Typically, these issues can be solved by trim-
ming a few centimeters from the head of the
column. Occasionally it may be necessary
to trim the column by up to 10% of the
total column length to solve the problem;
however, note that peak retention times will
decrease and peak identification windows
may need to be altered in your data system.
Further peak shape issues are more spe-
cific to splitless injection modes, but again
all relate to the homogeneity (contiguous
nature) of the sample band as it enters the
GC column. One should ensure, especially
in splitless injection, that the polarity of the
sample diluent solvent matches that of the
stationary-phase chemistry. Further, the
initial oven temperature should be at least
10 °C (preferably 20 °C) below the boiling
point of the sample solvent, which will act
to condense the analyte as it slowly evolves
from the inlet and focus each analyte band to
give sharp peaks within the chromatogram.
These factors combined, ensure that the
sample vapors condense as contiguous bands
within the GC column before they revolatil-
ize as the oven temperature is raised.
We are often asked about the causes of
rising baselines within GC separations —
and these typically fall into three categories.
If operating a temperature programmed
separation, with constant carrier gas head
pressure, the flow rate (and linear velocity)
of the carrier gas will decrease because gas
viscosity increases as a function of tempera-
ture. If one is using a mass- or flow-sensi-
tive detector (a flame ionization detector,
for example), which responds not only to
the amount of analyte but also the rate at
which analyte passes through the detector,
then the baseline position will naturally
rise. The solution to this issue is to oper-
ate in a constant flow mode in which the
instrument increases the carrier gas head
pressure to maintain a constant flow (or
linear velocity with some instruments) dur-
ing the whole of the temperature program.
Note that in switching operating modes,
retention times, especially of later-eluted
compounds, will change.
Baseline rise can also be caused by an
increase in column bleed with temperature.
Ensure that columns are properly condi-
tioned before use, which will involve a short
time at room temperature with carrier gas
flowing (this step is very important), fol-
lowed by no more than 30 min at 10 °C
higher than the upper operating tempera-
ture of the analytical method. Remember
that more-polar and thicker-film GC col-
umns will show greater bleed and to set a
bleed specification beyond which the col-
umn will not be used.
The third common cause of rising base-
lines is an improperly optimized splitless
injection. Although the initial phase of a
splitless injection should be carried out with
the split valve closed, the split should then
be initiated to remove excess solvent and
sample vapors from the inlet. This “split-
less” or “purge” time needs to be carefully
optimized; too short and sample will be lost
resulting in poor quantitation, too long and
a large tailing solvent peak with rising base-
line will result. Typically, the purge time is
optimized by choosing a time value (usually
in seconds) at which repeated injection of
the sample gives reproducible analyte peak
areas, but which results in the narrowest
solvent peak width.
Finally, we are very often asked about
peaks that tail badly in capillary GC, that
is, peaks whose asymmetry or United States
Pharmacopeia (USP) tailing factor is greater
than one. Most often, peak tailing occurs
because a certain proportion of the analyte
molecules are being subjected to a second-
ary mechanism of retention compared to the
rest and this is usually some type of silanol
interaction with analyte polar functional
groups. The silanol groups are present on
the surface of your quartz glass inlet sleeve or
liner, glass wool used for liner packing, and
in the silica from which the wall coated cap-
illary columns are manufactured. To avoid
peak tailing one should use only profession-
ally deactivated inlet liners and glass wool
packing, ensure good column cuts, trim the
inlet end of the column to remove exposed
silanol groups because of phase stripping,
and, lastly, consider derivatizing analytes to
“cap” or “mask” polar functional groups.
Get the full tutorial at www.CHROMacademy.com/Essentials
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Troubleshooting Real GC Problems
Valves, fittings, and much more for chromatography and liquid handling
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