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May 2016

Volume 29 Number s5

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5 Recent Developments in LC Column Technology: Impact on a World

of Disciplines

David S. BellA brief introduction of the articles presented in this supplement.

6 The Impact of Superfi cially Porous Particles and New

Stationary-Phase Chemistries on the LC–MS Determination of

Mycotoxins in Food and Feed

Andreas BreidbachThis fi t-for-purpose LC–MS-based method provides fast analysis of four mycotoxins using standard HPLC equipment with a pentafl uorophenyl SPP column.

12 The Synthetic Cannabinoid Chemical Arms Race and Its Effect on

Pain Medication Monitoring

Sheng Feng, Brandi Bridgewater, Gregory L. McIntire, and Jeffrey R. EndersAn investigation of C18 and phenyl-hexyl column chemistries for defi nitive identifi cation of 13 synthetic cannabinoid metabolites in patient samples.

20 HPLC Column Technology in a Bioanalytical Contract Research

Organization

Ryan Collins and Shane Needham

When presented with a new analyte, a bioanalytical CRO must quickly

develop a robust method with good chromatographic resolution, repeatable

results, and a quick run time. Recent developments in LC column

technology make that possible.

24 Characterizing SEC Columns for the Investigation of Higher-Order

Monoclonal Antibody Aggregates

Ronald E. Majors and Linda L. LloydWhen selecting the optimum phase for SEC separations, several key column parameters must be considered carefully.

34 Positive Impacts of HPLC Innovations on Clinical Diagnostic Analysis

Michael J.P. Wright and Sophie HepburnAs clinical diagnostic assays move to LC–MS–MS, the emphasis has turned to emerging stationary phases that use alternative mechanisms of retention to separate the analyte–interference critical pairs.

39 Latest Advances in Environmental Chiral Applications

Denise WallworthRecent advances in chiral stationary phases have enabled higher efficiency and faster separations in studies of the differing enantiomeric activity of pesticides, their environmental transformation, and the degradation of pollutants in general.

Recent Developments in

LC Column Technology

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4 Recent Developments in LC Column Technology May 2016

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Kevin Altria

GlaxoSmithKline, Harlow, Essex, UK

Daniel W. Armstrong

University of Texas, Arlington, Texas, USA

Michael P. Balogh

Waters Corp., Milford, Massachusetts, USA

Brian A. Bidlingmeyer

Agilent Technologies, Wilmington,

Delaware, USA

Günther K. Bonn

Institute of Analytical Chemistry and

Radiochemistry, University of Innsbruck,

Austria

Peter Carr

Department of Chemistry, University

of Minnesota, Minneapolis, Minnesota, USA

Jean-Pierre Chervet

Antec Leyden, Zoeterwoude, The

Netherlands

Jan H. Christensen

Department of Plant and Environmental

Sciences, University of Copenhagen,

Copenhagen, Denmark

Danilo Corradini

Istituto di Cromatografia del CNR, Rome,

Italy

Hernan J. Cortes

H.J. Cortes Consulting,

Midland, Michigan, USA

Gert Desmet

Transport Modelling and Analytical

Separation Science, Vrije Universiteit,

Brussels, Belgium

John W. Dolan

LC Resources, Walnut Creek, California,

USA

Roy Eksteen

Sigma-Aldrich/Supelco, Bellefonte,

Pennsylvania, USA

Anthony F. Fell

Pharmaceutical Chemistry,

University of Bradford, Bradford, UK

Attila Felinger

Professor of Chemistry, Department of

Analytical and Environmental Chemistry,

University of Pécs, Pécs, Hungary

Francesco Gasparrini

Dipartimento di Studi di Chimica e

Tecnologia delle Sostanze Biologica-

mente Attive, Università “La Sapienza”,

Rome, Italy

Joseph L. Glajch

Momenta Pharmaceuticals, Cambridge,

Massachusetts, USA

Jun Haginaka

School of Pharmacy and Pharmaceutical

Sciences, Mukogawa Women’s

University, Nishinomiya, Japan

Javier Hernández-Borges

Department of Analytical Chemistry,

Nutrition and Food Science University of

Laguna, Canary Islands, Spain

John V. Hinshaw

Serveron Corp., Hillsboro, Oregon, USA

Tuulia Hyötyläinen

VVT Technical Research of Finland,

Finland

Hans-Gerd Janssen

Van’t Hoff Institute for the Molecular

Sciences, Amsterdam, The Netherlands

Kiyokatsu Jinno

School of Materials Sciences, Toyohasi

University of Technology, Japan

Huba Kalász

Semmelweis University of Medicine,

Budapest, Hungary

Hian Kee Lee

National University of Singapore,

Singapore

Wolfgang Lindner

Institute of Analytical Chemistry,

University of Vienna, Austria

Henk Lingeman

Faculteit der Scheikunde, Free University,

Amsterdam, The Netherlands

Tom Lynch

BP Technology Centre, Pangbourne, UK

Ronald E. Majors

Analytical consultant, West Chester,

Pennsylvania, USA

Phillip Marriot

Monash University, School of Chemistry,

Victoria, Australia

David McCalley

Department of Applied Sciences,

University of West of England, Bristol, UK

Robert D. McDowall

McDowall Consulting, Bromley, Kent, UK

Mary Ellen McNally

DuPont Crop Protection,Newark,

Delaware, USA

Imre Molnár

Molnar Research Institute, Berlin, Germany

Luigi Mondello

Dipartimento Farmaco-chimico, Facoltà

di Farmacia, Università di Messina,

Messina, Italy

Peter Myers

Department of Chemistry,

University of Liverpool, Liverpool, UK

Janusz Pawliszyn

Department of Chemistry, University of

Waterloo, Ontario, Canada

Colin Poole

Wayne State University, Detroit,

Michigan, USA

Fred E. Regnier

Department of Biochemistry, Purdue

University, West Lafayette, Indiana, USA

Harald Ritchie

Trajan Scientific and Medical, Milton

Keynes, UK

Koen Sandra

Research Institute for Chromatography,

Kortrijk, Belgium

Pat Sandra

Research Institute for Chromatography,

Kortrijk, Belgium

Peter Schoenmakers

Department of Chemical Engineering,

Universiteit van Amsterdam, Amsterdam,

The Netherlands

Robert Shellie

Australian Centre for Research on

Separation Science (ACROSS), University

of Tasmania, Hobart, Australia

Yvan Vander Heyden

Vrije Universiteit Brussel,

Brussels, Belgium

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Waste

There have been many advances in

liquid chromatography (LC) during

the past decade. Much attention has

been paid to the development of new

and improved particle designs to

achieve higher efficiency and there

have been many new developments

in the surface treatments of these

particles that impact retention and

selectivity. Novel particle designs

such as sub-2-μm and superficially

porous media have vastly improved

the speed and efficiency of

separation tasks. Newly developed

chemical modifications and their

implementation using these modern

particle architectures have greatly

expanded their utility. The underlying

theme for this special supplement

edition was to bring together articles

that discuss how these innovations

have impacted analysis across a

wide variety of disciplines.

Andreas Breidbach from the

European Commission, Joint

Research Center at the Institute

for Reference Materials and

Measurements provides insight

on how modern technologies

have impacted the liquid

chromatography–mass spectrometry

(LC–MS) analysis of mycotoxins

in food and feed. The work

demonstrates the increased

efficiency garnered from the use

of superficially porous particles

as well as added selectivity

through modern surface chemistry

modifications. Sheng Feng and

colleagues from Ameritox provide

examples of similar achievements

for the analysis of an ever-growing

number of synthetic cannabinoids

for toxicology and forensic

analyses. Again, superficially

porous particles combined with

alternative surface chemistries

has enabled rapid, selective, and

sensitive LC–MS–MS identification

of 13 synthetic cannabinoids in

patient urine samples. Collins and

Needham from Alturas Analytics

discuss the impact of recent

column technology advancements

and emerging developments in

microflow LC technologies with

respect to improving productivity

in the bioanalytical contract

research realm. The authors note

that these technologies facilitate

the development of robust and

reliable methods, which may lead

to lowering the cost of complex

biotherapeutics. Continuing with

the theme of bioanalysis, Lloyd

and Majors discuss the importance

of particle architecture and

surface treatments with respect

to current needs in size-exclusion

chromatography (SEC). The growing

attention of the pharmaceutical

market on biotherapeutics has

necessitated the implementation

of many modes of chromatography

to fully characterize these complex

systems. The authors point out the

importance of particle pore size

(and distribution), pore volume,

and surface chemistry treatments

as it pertains to modern SEC

requirements. From the world of

clinical diagnostics and testing,

Wright and Hepburn provide

examples of how modern particle

technologies, surface modifications,

and multiple-channel high

performance liquid chromatography

(HPLC) instruments have enabled

faster analyses for various disease

states and patient types. This is

a crucial step towards providing

high-quality health care. Lastly,

Wallworth highlights some of the

recent advances in chiral stationary

phases (CSP) and how they impact

important environmental concerns.

Chirality plays a significant role in

the study of pollutants, agrochemical

usage, and pharmaceutical waste

on our environment. The author

anticipates that recent applications

of CSPs on modern particle designs

will positively impact research in

this arena.

In applications ranging from food

to pharma and biotherapeutics

to biomes, advances in liquid

chromatography are playing a

critical role. Modern particle designs

and surface chemistry treatments

are continually being adopted

in a variety of disciplines. As

exemplified by the articles within this

supplement, developments in our

craft are improving the quality of life

around the world. Enjoy!

Recent Developments in LC Column Technology: Impact on a World of

Disciplines

David S. Bell

LCGC “Column Watch” editor


Novel particle designs

such as sub-2-μm and

superficially porous

media have vastly

improved the speed and

efficiency of separation

tasks.

In 2006, high performance liquid

chromatography (HPLC) columns

packed with superficially porous

particles (SPP) (also known as

porous-shell, core–shell, and

solid-core particles) were introduced

to the market. In performance rivaling

sub-2-μm technology, SPP packed

columns have enabled highly efficient

separations to be carried out with

standard HPLC systems because

of the much lower back pressure

they generate (1). This favourable

characteristic has also been exploited

for the determination of mycotoxins in

food and feed.

Mycotoxins are secondary

metabolites of certain fungi whose

occurrence in food and feed is difficult

to avoid. Therefore, many countries

have regulated this occurrence of

mycotoxins (2,3). A wealth of methods

of analysis to enforce these regulations

exist (4) and among them liquid


(LC–MS)-based detection is gaining

momentum. LC–MS is primarily gaining

momentum for two reasons: sample

preparation requirements can be

relaxed because of the high specificity

and sensitivity of MS detection, and

multiple mycotoxins can be determined

in one go. Both of these reasons are

of particular interest to official control

laboratories since they will lead to

higher throughput compared to

traditional one analyte per preparation

and run approaches with extensive

cleanup. This higher throughput has

been shown for traditional HPLC

equipment with an analytical column

packed with fully porous particles

by Biselli and colleagues (5). Using

a 150 mm × 2.1 mm column with

3-μm particles at 1-mL/min flow,

18 mycotoxins could be detected

during a 15-min analytical run. With

those settings, deoxynivalenol (DON)

eluted at 3.80 min and zearalenone

(ZON) at 7.38 min. To stay within

the operational envelope of their

electrospray ionization (ESI) source

the column effluent was split 1:5.

Using a sub-2-μm fully porous particle

packed column of 100 mm × 2.1 mm

dimensions, Varga and colleagues (6)

were able to show a multimycotoxin

separation in which DON eluted at

1.45 min and ZON at 6.44 min with a

total run time of 11.5 min. To perform

this separation, an ultrahigh-pressure

liquid chromatography (UHPLC) system

capable of delivering flows at pressures

as high as 1200 bar was used.

With the desire to determine

multiple mycotoxins in one run, the

necessity arose to be able to separate

closely related mycotoxins. One

such example would be DON and

its two acetylated relatives, 3- and

15-acetyldeoxynivalenol (AcDON).

Although DON can be separated from

the two AcDONs on a C18 column, the

two AcDONs are coeluted. Because

of different fragmentation behaviour

it is still possible to obtain individual

quantitative data using MS–MS

detection, but with lesser confidence

than with a full chromatographic

separation (5). A more recent

stationary phase chemistry capable

of separating such isomers is the

so-called pentafluorophenyl (PFP, F5)

modified silica. The pentafluorphenyl

system is electron deficient and can

interact with the analyte in multiple

ways: π-π, dipole-dipole, and

charge-transfer interactions. Because

of these multiple interactions, structural

isomers can often be separated.

The Impact of Superficially Porous Particles and New Stationary-Phase Chemistries on the LC–MS

Determination of Mycotoxins in

Food and FeedAndreas Breidbach, European Commission, Joint Research Centre, Institute for Reference

Materials and Measurements, Geel, Belgium.

Superficially porous particles with their favourable chromatographic properties were a great advance

for liquid chromatography (LC). Analytical LC columns packed with those particles allow for much faster

separations even with standard LC equipment rated at a maximum pressure of 400 bar. This speed is

exemplified by a LC–mass spectrometry (MS) method of analysis for four mycotoxins, spanning log P

values from -0.7 to 3.6, with an analysis time of just over 8 min and excellent performance. Another issue

is the separation of closely related mycotoxins, like 3- and 15-acetyldeoxynivalenol. With the common C18

chemistries, they are coeluted and identification and quantification can only be achieved through differing

MS–MS signals. Now, with the newer pentafluorophenyl chemistries these two mycotoxins can be separated

by LC and MS quantification of them has become much more precise.

Recent Developments in LC Column Technology May 20166

This article presents a

fit-for-purpose LC–MS-based method

of analysis for the four mycotoxins

DON, HT-2 toxin, T-2 toxin, and ZON

utilizing standard HPLC equipment

with an SPP column. Performance

characteristics in unprocessed

cereals, as determined in-house and

verified through a collaborative trial,

were in line with traditional single

analyte methods with a short analysis

time of under 9 min. The article also

shows how the F5 stationary phase

chemistry enables the separation of

the closely related mycotoxins 3- and

15-acetyldeoxynivalenol.

Experimental

Chemicals and Materials: All

chemicals were purchased from either

Sigma-Aldrich or VWR and were of at

least analytical grade. For the mobile

phase LC–MS Chromasolv-grade

(Fluka, Sigma-Aldrich) water and

methanol were used. Deionized

water was generated by a MilliQ

system (Millipore). All tested materials

came from the material pool of

the European Union Reference

Laboratory (EURL) for mycotoxins at

the Institute for Reference Materials

and Measurements (IRMM) of the

Joint Research Centres (JRC) of the

European Commission (EC).

The mycotoxins DON, HT-2, T-2,

ZON, 3-AcDON, and 15-AcDON,

Table 1: MS source and analyzer settings. (The segment run times relate to the Ascentis Express C18 column; for the Kinetex

columns they were adjusted to the respective retention times of the analytes.)

Item Segment 1 Segment 2 Segment 4

Run time (min) 0–2.6 2.6–4.9 4.9–8.7

Analyte DON +

AcDON +

13C15-DON

HT2 +

13C22-HT2,

T2 +

13C24-T2

ZON +

13C18-ZON

Adduct Protonated Sodium Deprotonated

Transitions (collision energy [eV]) 297A231 (16),

297A249 (13),

339A213 (20),

339A261 (20),

312A263 (9),

312A276 (9)

447A285 (22),

447A345 (20),

469A300 (19),

469A362 (18),

489A245 (30),

489A327 (25),

513A260 (26),

513A344 (23)

317A131 (25),

317A175 (22),

335A185 (26),

335A290 (21)

Tube lens (V) 80 110 80

Polarity Pos Pos Neg

Spray voltage (V) 2800 2800 2000

Vaporizer temperature (°C) 350

Sheath gas pressure (arbitrary units) 30

Auxiliary gas pressure (arbitrary units) 10

Transfer capillary temperature (°C) 320


Breidbach

Rela

tive a

bu

nd

an

ce

Rela

tive a

bu

nd

an

ce

Time (min)

100 100

80

60

40

20

0100

80

60

40

20

0100

80

60

40

20

0100

80

60

40

20

0

95

90

85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

00 1 2 3 4

RT: 1.65

RT: 3.62

RT: 4.53 RT: 1.65

RT: 3.63

RT: 4.53

RT: 5.50

0.54

RT: 5.51

5 6 7 8 0 1 2 3 4 5 6 7 8

Time (min)

(b)(a)

Figure 1: (a) A total ion current chromatogram and (b) extracted ion current

chromatograms (top to bottom: DON, HT-2, T-2, ZON) of a QC sample with circa 90-μg/

kg DON (RT 1.65), 30-μg/kg HT-2 toxin (RT 3.62), 10-μg/kg T-2 toxin (RT 4.53), and

10-μg/kg ZON (RT 5.51); the peak areas in (a) are mostly representing the 13C-labelled

isotopologues.

and the isotopologues 13C15-DON, 13C22-HT2, 13C24-T2, and 13C18-ZON

were purchased from Biopure

(Romer Labs) as either solids or

ready-to-use solutions. From these,

a stock solution of 3.2-μg/mL DON,

0.5-μg/mL HT-2 toxin, 0.3-μg/

mL T-2 toxin, and 0.3-μg/mL ZON

in neat acetonitrile was prepared

and stored. This stock solution was

freshly diluted for every calibration

task. An internal standard solution

with the same concentrations of the

respective 13C-isotopologues in neat

acetonitrile was also prepared and

used undiluted. These solutions were

stable for at least three months in the

dark at 2–8 °C.

Equipment: Measurements were

performed on an LC–MS system

consisting of two LC-20AD pumps

(Shimadzu, high-pressure binary

gradient), an Accela autosampler

(Thermo Scientific), and a TSQ

Quantum Ultra triple-quadrupole

mass spectrometer with an IonMax

HESI2 interface (both Thermo

Scientific). For analytical columns

either an Ascentis Express C18

(75 mm × 2.1 mm, 2.7-μm particle

size, Supelco, Sigma-Aldrich), a

Kinetex C18, or a Kinetex PFP (both

100 mm × 2.1 mm, 2.6-μm particle

size, Phenomenex) were used. The

gradient conditions with the Ascentis

Express C18 column were as follows:

0 min, 8% B; 2 min, 57% B; 6 min,

61% B; 6.1 min, 95% B; 7.6 min,

95% B; 7.7 min, 8% B; 8.7 min, 8%

B with mobile-phase A consisting

of 999:1 (v/v) water–formic acid and

mobile-phase B consisting of 999:1

(v/v) methanol–formic acid at a flow

rate of 0.3 mL/min. The column

was maintained at 40 °C during

analysis. This nonintuitive gradient

was designed with optimal resolution

and shortest analysis time for just

the four mycotoxins in mind. For the

two Kinetex columns more-generic

gradient conditions were used:

0 min, 8% B; 8 min, 95% B; 8.1 min,

8% B; 10 min, 8% B at a column

temperature of 50 °C. The mobile

phases and flow rate were as stated

above. The MS system settings

can be found in Table 1. The data

acquisition was segmented to limit

the number of acquired transitions

and enable longer dwell times per

segment.

Sample Preparation: In an

appropriately sized tube, 2 g of

unprocessed cereal (comminuted

to <500 μm particle size) was fully

suspended in 8 mL of water. Then

16 mL of ethyl acetate was added

and after a brief, hard shake the

mixture was sonicated for 30 min. After

sonication 8 g of sodium sulphate

was added. The mixture was again

shaken hard and then left for 10 to

20 min to allow the sodium sulphate

to crystallize. To settle particulate

matter and aid phase separation the

tube was centrifuged at a relative

centrifugal force of 3000g for at

least 1 min. Next, 500 μL of clear

supernatant was transferred to a

silylated autosampler vial (2 mL,

Supelco, Sigma-Aldrich), 25 μL of

internal standard mix was added,

and the contents of the vial were

evaporated to dryness with a stream

of dry nitrogen (boil-off) at 60 °C. The

dry residue was reconstituted with

250 μL of mobile-phase B and 250 μL

of mobile-phase A, in that order. Initial

reconstitution with the pure organic

mobile phase significantly improved

the dissolution of the more hydrophobic

analytes. Finally, 5 μL of this solution

was injected without further treatment.

Turbidity of the injection solutions, often

seen in these reconstituted extracts,

did not negatively affect column lifetime

in our experience.

Mycotoxins are

secondary metabolites

of certain fungi whose

occurrence in food and

feed is difficult to avoid.


Breidbach

Rela

tive a

bu

nd

an

ce

Time (min)

RT: 11.92

RT: 10.29

RT: 14.09

18.009.108.385.643.052.69 16.2514.61

RT: 5.97

100

95

90

85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

0

0 2 4 6 8 10 12 14 16 18

Figure 2: Total ion current of the same QC sample as in Figure 1. Run times: DON,

5.97 min; HT-2, 10.29 min; T-2, 11.92 min; ZON, 14.09 min. Column: 150 mm × 2 mm,

4-μm dp Synergi Hydro-RP (Phenomenex).

Method Validation: To validate

the method, the cereals maize,

wheat, oat, and rice but also soy

and a cereal-based compound

feed were investigated. Among the

characteristics determined were

matrix effects, method recovery,

repeatability, and intermediate

precision. For matrix effect and

method recovery determination,

different amounts of the analytes

were spiked into materials free of the

analytes before extraction (set A) and

after extraction of the analyte-free

materials (set B). After regression,

analysis of the slopes of the signals of

the sets A and B were then compared

with the slopes of a calibration done

in neat solvent (set C). Comparing

slopes A and C indicated method

recovery, while comparing slopes

B and C determined the extent of

matrix effects (7). For repeatability

and intermediate precision, naturally

contaminated cereal mixes were

prepared and measured 20 times

on the same day (repeatability) and

once each on a total of eight days by

three different operators (intermediate

precision). A detailed validation report

is available on-line (8). The method

was then further validated through

a collaborative trial (9). Currently,

this method and the results of the

collaborative trial are in the process

of being published by the European

committee for standardization (CEN).

Results and Discussion

The performance characteristics of this

method are very satisfactory. Matrix

effects that can have a significant

influence on results in LC–MS were

found to be negligible for all four

analytes in all six tested materials.

The absence of significant matrix

effects allows for the use of calibration

solutions in neat solvent. This can

be attributed to the use of the stable

isotopologues. To keep the total usage

of isotopologues low, and with that the

expense per test, they were added

after extraction to only an aliquot of the

extract. So instead of having to add

the equivalent of 2 g of test material,

only the equivalent of 0.125 g had to

be spiked. Because this setup does

not account for any loss of analytes

during extraction, method recovery

had to be determined. In this context,

method recovery equals extraction

efficiency, which has shown to be

stable for a given extraction

solvent–analyte system across

different cereal matrices.

The HT-2, T-2, and ZON recoveries

in all six test materials were not

significantly different from 1. Only

DON with an average recovery of

0.83 was different. This is not very

surprising given that the log P of

DON is -0.7 and ethyl acetate is not

the most polar solvent; however,

this method recovery is well within

the commonly accepted ranges.

Compared to more-traditional

acetonitrile–water extracts, the ethyl

acetate extracts seemed to cause, in

general, less of a matrix effect for the

analysis of these four mycotoxins. It

is also less hazardous and expensive

than acetonitrile.

Repeatability was determined with

naturally contaminated materials

at three different contamination

levels. Near the low end of the

calibration range, the relative

repeatability standard deviations

(RSDr) were between 11% and 18%

for the four analytes. Towards higher

contamination levels, which were

smaller than existing (DON and

ZON) or anticipated (HT-2 and T-2)

legislative limits in the European

Union (EU), these values improved

to ≤9%. Two of those materials, the

lowest and the highest contaminated,

were also tested on eight different

days by three different operators to

determine intermediate precision, or

within laboratory reproducibility. For

the low contaminated material, relative

intermediate precisions (RSDi) were

between 13% and 25% for the four

The benefits of short

analysis times are

obvious: higher

throughput and lower

solvent consumption.


Breidbach

Rela

tive a

bu

nd

an

ce

Time (min)

11

2

2,3

3

4

(a) (b)

4

2.477.19 2.31

6.56

3.81

4.18

4.29

100

95

90

85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

0

Rela

tive a

bu

nd

an

ce

100

95

90

85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

00 1 2 3 4 5 6 7 8 9 10

Time (min)

0 1 2 3 4 5 6 7 8 9

Figure 3: Total ion current of a maize sample highly contaminated with DON, AcDONs, and ZON; sample extract was diluted eight

times; separation with (a) Kinetex PFP and (b) Kinetex C18 columns; Peaks: 1 = DON, 2 = 15-AcDON, 3 = 3-AcDON, 4 = ZON.

analytes. For the high contaminated

material they were between 11%

and 17%. All of these findings were

comparable with the results of the

collaborative trial (9).

As already mentioned, these

performance characteristics are

quite satisfactory considering the

analysis time is only 8.7 min. This

is significantly shorter than the

analysis times reported by Biselli

(5) or Varga (6). Figure 1 shows a

typical chromatogram of the four

analytes, which span log P values

from -0.7 (DON) to 3.6 (ZON). The

narrow peaks with a baseline width of

≤0.2 min attest to the high efficiency of

the SPP particles packed in a 75-mm

column. Even though a mobile phase

with methanol–water was used, the

back pressure during analysis never

exceeded 230 bar, which is well below

the maximum pressure of standard

HPLC equipment. Compared to this,

analysis time of the same material

in a different laboratory during the

collaborative trial on a 150-mm

column packed with fully porous

particles takes more than twice as

long (20 min) with larger baseline

peak widths between 0.4 and 0.9 min

(Figure 2). Thus, the SPP column

provides superior resolution at shorter

analysis times.

The benefits of short analysis times

are obvious: higher throughput and

lower solvent consumption. Benefits

of the better resolution might not be

so obvious. Matrix effects in LC–MS

measurements influence ionization

efficiency caused by, amongst

other things, coeluted compounds.

Because of the high specificity of

MS, particularly MS–MS, coeluted

compounds, more likely than not,

will be undetected. Better resolution

will limit possible coelution and,

therefore, minimize influences on

ionization efficiencies and maximize

the ability of unbiased determination.

Furthermore, in our case, the better

resolution comes from narrower and,

hence, taller peaks, which has a

positive effect on limit of detection

and quantification.

To show how a stationary phase

chemistry change helps in obtaining

better and more confident results, a

maize sample highly contaminated

with DON, AcDONs, and ZON

was analyzed with two columns

with identical SPPs but different

chemistries, namely the Kinetex C18

and PFP columns. Figure 3 shows

the two total ion chromatograms

(TICs). Even though the two

AcDONs were not separated with

the C18 chemistry, they were with

the PFP chemistry. Retention for

all analytes was slightly higher on

the PFP column. Because of the

different fragmentation behaviour

of the two AcDONs in MS–MS the

contamination level of the individual

AcDONs can even be estimated from

peaks 2 and 3 in Figure 3(b). But

because of significant overlap of the

product ions, this estimation comes

with an increased uncertainty. It goes

without saying that a separation as

shown in Figure 3(a) is absolutely

preferable.

Conclusions

Through the use of an SPP packed

column, a short method of analysis

for four mycotoxins in cereals was

developed that is fit for the purpose

of official food and feed control. The

total run time was 8.7 min for the

mycotoxins DON, HT-2, T-2, and

ZON spanning log P values from -0.7

to 3.6. Despite the short run time,

excellent resolution was obtained

with very satisfactory performance

characteristics. Method recoveries

were indistinguishable from 1 for HT-2,

T-2, and ZON. For DON a recovery

of 0.83 was determined and results

for DON should be corrected for this

recovery level. Values of RSDr were

18% or smaller for low contamination

levels and improved to 9% or smaller

towards higher levels, which were

still below existing or anticipated

EU legislative limits. Because of the

intelligent use of stable isotopologues,

matrix effects were negligible at a

minimal cost per sample.

Changing the stationary-phase

chemistry from C18 to

pentafluorophenyl enabled the

separation of the structural isomers

3- and 15-acetyldeoxynivalenol as

well as DON and ZON in a naturally

contaminated maize sample. This

stands to show that SPP-packed

columns and new stationary-phase

chemistries have advanced mycotoxin

analysis in food and feed.

Acknowledgements

The author would like to thank Katrien

Bouten, Kati Kröger, and Karsten

Mischke for their excellent technical

support during method validation and

the collaborative study. The highly

contaminated maize was courtesy

of the Austrian National Reference

Laboratory for mycotoxins (AGES,

Linz, Austria).

Disclaimer

Any trade names, trademarks,

product names, and suppliers

named above are only named for

the convenience of the reader of

this publication and their mentioning

does not constitute an endorsement

by IRMM, JRC, or EC of the products

named. Equivalent products may

lead to the same results.

References(1) J.J. Kirkland, S.A. Schuster, W.L.

Johnson, and B.E. Boyes, J. Pharm.

Anal. 3(5), 303–312 (2013).

(2) Food Quality and Standards Service

(ESNS). Worldwide regulations for

mycotoxins in food and feed in 2003.

2004; Available from: http://www.fao.

org/docrep/007/y5499e/y5499e00.

htm.

(3) European Commission, Commission

Regulation (EC) No 1881/2006 of 19

December 2006 setting maximum

levels for certain contaminants in

foodstuffs (Text with EEA relevance).

Official Journal of the European

Union, 2006. L 364: p. 5–24.

(4) F. Berthiller et al., World Mycotoxin J.

8(1), 5–35 (2015).

(5) S. Biselli, L. Hartig, H. Wegner, and

C. Hummert, LCGC Europe Special

Edition: Recent Applications in LC–MS

17(11a), 25–31 (2004).

(6) E. Varga et al., Anal. Bioanal. Chem.

402(9), 2675–2686 (2012).

(7) B.K. Matuszewski, J. Chromatogr. B

830(2), 293–300 (2006).

(8) A. Breidbach, Validation of

an Analytical Method for the

Simultaneous Determination of

Deoxynivalenol, Zearalenone, T-2 and

HT-2 Toxins in Unprocessed Cereals

- Validation Report. 2011; Available

from: http://skp.jrc.cec.eu.int/skp/

download?documentId=51161.

(9) A. Breidbach, K. Bouten, K. Kröger,

J. Stroka, and F. Ulberth, LC–MS

Based Method of Analysis for the

Simultaneous Determination of Four

Mycotoxins in Cereals and Feed:

Results of a Collaborative Study

(Publications Office of the European

Union, 2013). Available at: http://

publications.jrc.ec.europa.eu/

repository/bitstream/JRC80176/la-na-

25853-en-n.pdf

Andreas Breidbach is with the

European Commission, Joint

Research Centre, at the Institute

for Reference Materials and

Measurements in Geel, Belgium.

Direct correspondence to:

[email protected]


Breidbach

Synthetic cannabinoids, commonly

known as “K2”, “spice”, or “synthetic

marijuana”, are often sprayed onto

or mixed with dried plant materials

and sold in convenience stores,

gas stations, smoke shops, and on

the internet. This ready availability

causes confusion about their

safety and legality (1). In recent

years, synthetic cannabinoids have

become increasingly popular among

adolescents and young adults as

one of several frequently abused

substances. These synthetic drugs

mimic delta-9-tetrahydrocannabinol

(THC), but can be much more potent,

which results in psychoactive doses

less than 1 mg (2). In fact, synthetic

cannabinoids, which have a similar

psychoactive effect as cannabis,

have strong addictive properties often

coupled with unknown physiological

impacts on users. A recent study

indicates that the use of synthetic

cannabinoids can be a cause of

death (3).

Because of the high abuse potential

and lack of medical knowledge or

usage, these synthetic cannabinoids

have been added to the Schedule

I list by the United States Drug

Enforcement Administration (DEA), as

“necessary to avoid imminent hazard

to the public safety” (4). In response,

the chemists instigating this illegal

proliferation have synthesized many

new K2 analogues by slightly altering

chemical structures (5). Therefore,

compared with the relatively stagnant

pool of other compounds, such as

opiates, that most pain medication

monitoring laboratories deal with,

the number of agents on the list of

synthetic cannabinoids has been

and continues to be increasing (6).

Testing for synthetic cannabinoids

has become a routine demand among

pain treatment clinics.

There are various types of

synthetic cannabinoids with different

modifications on the core structure.

The first THC analogues, including

HU-210 (7) and CP-47, 497 (8), were

synthesized in the 1980s. Their

inventions allowed the discovery of

G protein-coupled receptors, CB1

and CB2 (9). Later on, a structurally

different analogue, WIN55, 212-2,

was reported. Surprisingly, WIN55,

212-2 has higher affinity towards

CB1 and CB2 than THC does (10).

Subsequently, John W. Huffman

developed a series of “JWH

compounds” by simply replacing the

aminoalkyl group in WIN55, 212-2

with simple alkyl chains (11). JWH-018

has become the prototypical JWH

compound. Synthetic cannabinoids

have also been developed by

generating fluoro-derivatives of

JWH compounds. For example,

AM-2201 and MAM-2201 are

fluoro-derivatives of JWH 018

and JWH 122, respectively (12).

By replacing the ketone in the

3-indole position of JWH-018 with

an ester linkage, PB-22 and BB-22

compounds have been synthesized

(13). Furthermore, another class of

synthetic cannabinoids contains

the tetramethylcyclopropyl ketone

indoles, such as UR-144 and its

fluoro-derivative, XLR-11 (14). Both

UR-144 and XLR-11 have cyclopropyl

rings, and are therefore likely to

exhibit similar retention times in liquid

chromatography (LC).

The increasing number of

sophisticated reversed-phase LC

separations has led to the need

for optimized stationary phases

to offer improved selectivity and

efficiency (15). In the present work,

we investigate C18 and phenyl-hexyl

column chemistries for definitively

identifying 13 synthetic cannabinoid

metabolites in standards and patient

samples.

Materials and Methods

Chemicals: Reference standards of

AKB48 5-hydroxypentyl metabolite,

The Synthetic Cannabinoid Chemical Arms Race and Its Effect on Pain Medication MonitoringSheng Feng, Brandi Bridgewater, Gregory L. McIntire, and Jeffrey R. Enders, Ameritox Ltd.,

Greensboro, North Carolina, USA.

In recent years, synthetic cannabinoids (“K2” or “spice”) have experienced a boom in popularity. The

negative health effects of these drugs coupled with their increasing popularity led to placement onto

Schedule I by the Drug Enforcement Administration (DEA). In response, the chemists behind these

illicit compounds frequently invent new compounds to circumvent the law. Thus, new classes and

new examples within classes of “spice” continue to become available for illicit use. In this paper, we

examine the use of two column chemistries (C18 and phenyl-hexyl) in an effort to definitively identify

synthetic cannabinoid compounds in patient samples. Distinct synthetic cannabinoid compounds

interact differently with specific stationary phases and the hope is that this extra dimension of data will

help to rule out similar interferent compounds that would otherwise cause false-positive results.

In recent years, synthetic

cannabinoids have become

increasingly popular

among adolescents and

young adults as one of

several frequently abused

substances.


AKB48 pentanoic acid metabolite,

AM2201 4-hydroxypentyl metabolite,

BB-22 3-carboxyindole metabolite,

JWH-018 pentanoic acid metabolite,

JWH-073 butanoic acid metabolite,

JWH-122 5-hydroxypentyl metabolite,

MAM-2201 4-hydroxypentyl

metabolite, PB-22 3-carboxyindole

metabolite, PB-22 pentanoic acid

metabolite, UR-144 5-hydroxypentyl

metabolite, UR-144 pentanoic

acid metabolite, and XLR11

4-hydroxypentyl metabolite were

purchased from Cayman Chemical

Company. Reference standards of

11-nor-9-Carboxy-Δ9-THC (THCA),

THCA glucuronide, and THCA-D9

were purchased from Cerilliant

Corporation. Solvents including

methanol (optima grade), acetonitrile

(optima grade), and formic acid

(88%) were purchased from VWR.

Dimethylsulphoxide (DMSO) (HPLC

grade), ethyl acetate (optima

grade), and ammonium hydroxide

(A.C.S. Plus) were purchased from

Fisher Scientific. Recombinant

β-glucuronidase enzyme was

purchased from IMCS. Drug-free

normal human urine (NHU) was

purchased from UTAK Laboratories,

Inc. Deionized (DI) water was

obtained in-house from a Thermo

Scientific Barnstead Nanopure water

purification system.

Sample Preparation: Reference

standards not already in solution

were dissolved in DMSO. Solutions of

reference standards were aliquoted,

dried, and reconstituted with NHU to

make a low calibrator concentration

at 1 ng/mL for all analytes except

BB-22 3-carboxyindole metabolite

and THCA with low calibrator levels at

5 ng/mL and 10 ng/mL, respectively.

A high calibrator concentration of

100 ng/mL in NHU was used for

all analytes. An 18.5-ng/mL THCA

glucuronide hydrolysis–negative

control (HNEG) and a 20-ng/mL

positive control (20CON) were

similarly prepared in NHU. This

protocol uses THCA glucuronide as

a hydrolysis control. Accordingly,

every curve and patient batch has

a hydrolysis control that contains

18.5 ng/mL of THCA glucuronide. For

this control to be considered passing,

it must return the expected THCA

(parent) concentration within 30%.

Into 13 mm × 10 mm borosilicate

glass tubes, 800 μL of calibrators,

controls, and samples were each

aliquoted and combined with 200 μL

of THCA-D9 (2.5 μg/mL)/recombinant

β-glucuronidase (1000 enzyme units/

mL) solution in 25:25:50 methanol–DI

water–pH 7.5 phosphate buffer. All

samples were vortexed, transferred to

SPEware CEREX PSAX 3 mL/35 mg

extraction columns in sample racks

by SPEware, and heated in a VWR

Symphony oven for 15 min at 60 °C.

Samples were cooled for 5 min

and placed on an automated liquid

dispensing-II (ALD-II) system for

extraction. A light positive pressure

was applied to push the samples


Feng et al.

HU-210

JWH-018 AM-2201 JWH-122 MAM-2201

PB-22 BB-22 UR-144 XLR-11

OH OH

OHOHH

O

O

O

O O OO

O

O OO

O

O

O

H

N

N

N

N NN

N

N

N

N N F

F

F

NH3C

H3C H3C

H3CH3C

H3CH3CH3C

CH3CH3

CH3

CH3

CH3

CH3 CH3

CH3

CH3

CH3 CH3

CH3

CH3CH3

CP-47, 497 WIN55, 212-2

Figure 1: Chemical structures of recent synthetic cannabinoids.

XLR11 N-(4-hydroxypentyl) metabolite

UR-144 N-pentanoic acid metabolite

UR-144 N-(5-hydroxypentyl) metabolite

%B solvent

1 2 1 2

100

03 4 5

1 2 1 2 3 4 5

Time (min)Time (min)

C18

Rela

tive in

ten

sity

100

0

%B

%B

Phenylhexyl

Figure 2: Total ion chromatography of 100 ng/mL calibrator in C18 and phenyl-hexyl

columns with 2.5-min or 5-min methods. Red, blue, and green peaks represent XLR11

N-(4-hydroxypentyl), UR-144 N-pentanoic acid, and UR-144 N-(5-hydroxypentyl),

respectively. Blue dashed lines indicate solvent gradients.

onto the solid-phase extraction

(SPE) packing. The ALD-II system

then washed columns with 85:14:1

DI water–acetonitrile–ammonium

hydroxide, washed with 30:70 DI

water–methanol, and finally eluted

samples into 1800-μL amber

autosampler vials using 98:2 ethyl

acetate–formic acid. Samples were

dried under nitrogen for ~35 min at

25 °C in a SPEware Cerex sample

concentrator, then each reconstituted

with 400 μL of 50:50 DI water–

methanol. Samples were capped,

vortexed for 20 s, and spun for 5 min

at 4000 rpm on a Sorvall ST 40

centrifuge.

Patient Sample Collection: Patient

urine specimens were collected

at clinics and shipped to Ameritox

Ltd. These de-identified patient

samples were treated similarly to

standards, that is, they were diluted,

extracted, and subjected to liquid

chromatography–tandem mass

spectrometry (LC–MS–MS). Patient

samples were selected for this study

that were deemed positive by the

current method’s criteria, but were

then deemed negative upon closer

manual inspection.

Instrumentation: All analyses

were conducted by LC–MS–MS on

an Agilent 6490 triple-quadrupole

system run in electrospray ionization

(ESI) positive mode using an Agilent

1290 chromatographic system

(1290 Inifinity binary pump, 1290

TCC, 1290 autosampler, and 1290

thermostat) with a 100 mm × 2.1 mm,

2.7-μm dp Agilent Poroshell 120

EC-C18 or 50 mm × 2.1 mm, 2.6 μm

Phenomenex Kinetex Phenyl-Hexyl

column. Source conditions were

optimized with a 250 °C gas

temperature, gas flow at 19 L/min,

nebulizer set to 45 psi, sheath gas

heater at 300 °C, sheath gas flow at

11 L/min, capillary voltage at 3.5 kV,

and charging voltage at 2 kV. The run

time for this method is 2.21 min with a

cycle time of approximately 2.5 min.

A longer chromatographic method

(roughly 5 min) was also used in this

study to help resolve questionable

interferences. All of these assays

monitor two or three transitions for

each of the following 14 analytes:

AKB48 5-hydroxypentyl metabolite,

AKB48 pentanoic acid metabolite,

AM2201 4-hydroxypentyl metabolite,

BB-22 3-carboxyindole metabolite,

JWH 018 pentanoic acid metabolite,

JWH 073 butanoic acid metabolite,

JWH 122 5-hydroxypentyl metabolite,

MAM2201 4-hydroxypentyl

metabolite, PB-22 3-carboxyindole

metabolite, PB-22 pentanoic acid

metabolite, UR-144 5-hydroxypentyl

metabolite, UR-144 pentanoic acid

metabolite, XLR11 4-hydroxypentyl,

and THCA; and one transition for one

internal standard, THCA-D9. THCA is

analyzed by the mass spectrometer,

but it is not actively monitored

in patient samples. MS method

parameters are shown in Table 1. The

chromatographic starting conditions

are 40% mobile-phase A (0.1% formic

acid in 90:10 water–methanol) and

60% mobile-phase B (0.1% formic

acid in methanol) with a 0.5-mL/min


Feng et al.

Columnchemistry

C18

Co

un

tsC

ou

nts

Co

un

tsC

ou

nts

Pati

en

t 01

Pati

en

t 02

C18

Phenyl-hexyl

Phenyl-hexyl

JWH-018 N-pentanoic acidmetabolite qual372.2 → 126.9

1.8E4

1E4

0

1.6E4

0.8E4

0

1.2E4

0.6

0

9E3

4E3

0

1.8E4

1E4

0

0.4

1 1.2 1.4 1.6 1.8 1 1.2 1.4 1.6 1.8

1 1.2 1.4 1.6 1.8 1 1.2 1.4 1.6 1.8

0.6 0.8 1 1.2 1.4 0.6 0.8 1 1.2 1.4

1.2E4

0.6

0

1.2E4

0.6

0

Time (min) Time (min)

0.4 0.6 0.8 1 1.2 1.4 0.6 0.8 1 1.2 1.4


JWH-018 N-pentanoic acidmetabolite quant

372.2 → 155.1

IR fail5.4 ng/mL

IR pass14.5 ng/mL

IR fail5.4 ng/mL

IR pass14.5 ng/mL

Figure 3: Comparison of suspected JWH-018 pentanoic acid patient samples. The grey

areas are integrated peaks. The dashed lines indicate the expected retention time based

on the calibrators.

Columnchemistry

C18

Co

un

ts

Pati

en

t 02

Phenyl-hexyl


MAM2201 N-(4-hydroxypentyl)metabolite quant

390.1 → 169.0

MAM2201 N-(4-hydroxypentyl)metabolite qual390.1 → 141.0

1E3

5E2

0

Co

un

ts

58

50

42

80

65

50

IR fail1.2 ng/mL

IR fail0 ng/mL

3.5E2

2.0E2

0.5E2

1.2

0.6 0.8 1 1.2 1.4 1.6 0.8 1 1.2 1.4 1.6

1.4 1.6 1.8 2 1.2 1.4 1.6 1.8 2

Figure 4: Comparison of suspected MAM-2201 metabolite patient samples. The grey

areas are integrated peaks. The dashed lines indicate the expected retention time based

on the calibrators.


Feng et al.

Table 1: Mass spectrometry conditions for all methods in this study. The retention times coordinate with the 2.5 min C18 and

phenyl-hexyl method.

Compound NamePrecursor

IonProduct Ion

Fragmentation

(V)

Collision

Energy (V)

Cell Accelerator

(V)

C18 RT

(min)

Phenyl-hexyl

RT (min)

AKB-48 5-

hydroxypentyl382.11

107.00 380 52 2 1.99 1.24

92.90 380 60 2 1.99 1.24

135.10 380 10 5 1.99 1.24

AF4–MALS–dRI 396.1193.00 380 60 3 1.94 1.22

135.10 380 10 5 1.94 1.22

AM-2201

4-hydroxypentyl376.11

143.80 380 40 3 1.3 0.88

127.10 380 56 2 1.3 0.88

155.10 380 25 3 1.3 0.88

BB-22 3-

carboxyindole258.01

118.00 380 24 5 1.8 0.97

54.90 380 36 2 1.8 0.97

175.90 380 10 7 1.8 0.97

JWH-018

N-pentanoic acid372.21

126.90 380 60 2 1.36 0.94

55.00 380 56 2 1.36 0.94

155.10 380 25 3 1.36 0.94

JWH-073

butanoic acid358.21

127.20 380 60 2 1.26 0.84

43.30 380 48 2 1.26 0.84

155.10 380 45 3 1.26 0.84

JWH-122

5-hydroxypentyl372.11

115.10 380 72 4 1.65 1.11

169.10 380 21 4 1.65 1.11

141.00 380 55 4 1.65 1.11

THCA 345.20

327.20 380 18 2 2.1 1.31

299.20 380 18 6 2.1 1.31

193.20 380 18 2 2.1 1.31

MAM-2201 N-

(4-hydroxypentyl)390.11

141.00 380 48 2 1.53 1.04

169.00 380 10 7 1.53 1.04

PB-22 3-

carboxyindole232.01

118.00 380 16 2 1.53 0.75

43.10 380 24 2 1.53 0.75

132.00 380 10 7 1.53 0.75

PB-22 pentanoic

acid389.31

144.00 380 36 3 1.14 0.73

54.90 380 56 4 1.14 0.73

244.00 380 10 3 1.14 0.73

UR-144 5-

hydroxypentyl328.11

55.00 380 44 2 1.74 0.93

125.00 380 10 3 1.74 0.93

UR-144

N-pentanoic acid342.11

125.00 380 20 3 1.68 0.92

54.90 380 48 4 1.68 0.92

244.00 380 10 4 1.68 0.92

XLR-11 4-

hydroxypentyl346.11

143.90 380 44 3 1.49 0.79

248.00 380 20 2 1.49 0.79

THCA-d9 (internal

standard)354.10 336.10 380 13 5 2.09 1.29

flow throughout (Tables 2 and 3). The

2.5-min phenyl-hexyl method was

validated according to a previously

published procedure (16).

Results and Discussion

Various methods including

colorimetric detections (17),

immunochemical assays (18), nuclear

magnetic resonance (NMR) (19), gas


(GC–MS) (20), and LC–MS–MS

(21), have been developed for the

analysis of synthetic cannabinoids.

With those methods, many synthetic

cannabinoids have been successfully

analyzed in different samples such

as plant materials, human hair,

saliva, serum, and urine. Several

analytical reviews have summarized

the identification and quantification

techniques for synthetic cannabinoids

that are currently popular (22,23).

Among those methods, LC–MS–

MS has clear advantages of ease

and speed of sample preparation

and the capability of automation.

However, most of the current methods

only focus on a few synthetic

cannabinoids, or need a very long

chromatographic gradient to affect

resolution of spice compounds of

interest (usually longer than 10 min,

see Table 4). To improve the analysis

of synthetic cannabinoids, we

developed new LC–MS–MS methods

with two different column chemistries

(C18 and phenyl-hexyl), which take

either 2.5 min or 5 min for each

sample to achieve optimal resolution.

These methods were applied to the

analysis of 13 synthetic cannabinoids.

We have analyzed a 100-ng/mL

synthetic cannabinoid calibrator

that includes all the K2 and spice

compounds of interest to this work

with both the 2.5-min or 5-min

methods in two different columns.

Most of the compounds were eluted

in similar order in the different

columns, though the elution time

changed. Overall, the compounds in

the phenyl-hexyl column are eluted

earlier compared with ones in the

C18 column under both the 2.5-min

and 5-min methods, which may

be solely due to the shorter length

of the column or a combination of

length and selectivity. In addition,

the three compounds that share

the tetramethylcyclopropyl ketone

indole structural moiety (that is,

XLR11 N -[4-hydroxypentyl], UR-144

N -pentanoic acid, and UR-144 N -[5-

hydroxypentyl]) exhibit changed

elution order in the two different

columns. In both the 2.5-min

and 5-min methods, those three

compounds were eluted much

Synthetic cannabinoids

have strong addictive

properties often

coupled with unknown

physiological impacts on

users.


Feng et al.

Table 2: Gradient properties of the 2.5-min method.

StepFlow Rate

(mL/min)

Time

(min)

%A (0.1% Formic Acid in

90:10 Water–Methanol)

%B (0.1% Formic

Acid in Methanol)

0 0.5 Initial 40 60

1 0.5 0.80 30 70

2 0.5 1.60 5 95

3 0.5 2.20 5 95

4 0.5 2.21 40 60

5 0.5 2.50 40 60

Table 3: Gradient properties of the 5-min method.

StepFlow Rate

(mL/min)Time (min)

%A (0.1% Formic Acid in

90:10 Water–Methanol)

%B (0.1% Formic

Acid in Methanol)

0 0.5 Initial 65 35

1 0.5 0.90 40 60

2 0.5 1.70 35 65

3 0.5 2.50 32 68

4 0.5 4.00 5 95

5 0.5 4.30 5 95

6 0.5 4.31 65 35

7 0.5 5.00 65 35

Columnchemistry

C18

Pati

en

t 03

Phenyl-hexyl

Time (min)

UR-144 N-pentanoic acidmetabolite quant

342.1 → 125.0

UR-144 N-pentanoic acidmetabolite qual342.1 → 244.0

Co

un

tsC

ou

nts

7E3

3E3

0

5.0E3

2.5E3

0

IR fail5.2 ng/mL

IR fail4.9 ng/mL

4E4

2E4

0

3.0E4

1.5E4

0

1.2 1.4 1.6 1.8 2 1.2 1.4 1.6 1.8 2

0.6 0.8 1 1.2 1.4

Time (min)

0.60.4 0.8 1 1.2 1.4

Figure 5: Comparison of suspected UR-144 N-pentanoic acid patient samples. The

grey areas are integrated peaks. The dashed lines indicate the expected retention time

based on the calibrators. In this particular patient sample (when run on the C18 column),

the actual qualifier peak was visible and chromatographically separated; however, the

integration software (under reasonable integration conditions) incorrectly selected the

interferent for integration.

earlier in order with the phenyl-hexyl

column compared to the C18 column.

This change in elution order is

not because of the change in the

column length. However, it might be

due to their tetramethylcyclopropyl

structure having a higher affinity

towards the C18 column than for

the phenyl-hexyl column. Although

this observation may seem trivial,

it helps illustrate the breadth of

chemical components inherent in a

synthetic cannabinoid method. This

challenge of chemical breadth can

be used as an advantage, however,

if one considers that synthetic

cannabinoids with different chemical

structures will have different elution

behaviours in two distinct column

chemistries. In most cases, newly

invented spice compounds only

slightly change the side chains of the

banned chemicals. It is possible that

evaluating potential patient positives

for this class of compounds using two

different column chemistries might

help better separate compounds with

similar chemical structures, thereby

improving the detection of novel

compounds from existing agents.

These new methods for analyzing

synthetic cannabinoids were applied

to suspected patient positive samples

identified from a production method.

When the urine sample of patient

01, positive for JWH-018 pentanoic

acid metabolite, was analyzed

using both C18 and phenyl-hexyl

columns, both quantifier (quant) and

qualifier (qual) peaks for JWH-018

pentanoic acid metabolite came

out earlier than expected based

on calibrators (Figure 3). However,

the ion ratio failed in the analysis

on the C18 column because of a

missing qual peak, whereas the ion

ratio passed in the analysis with the

phenyl-hexyl column. Regardless of

column chemistry, a human reviewer

would likely review this sample as

negative or “unable to confirm” since

retention times do not perfectly line

up. However, with the phenyl-hexyl

column data the peaks that passed

the ion ratio criteria were not all

that far off with regards to retention

time. On a production floor it is

not unreasonable for peaks to drift

0.3 min (18 s) over a given day or

week, especially if this instrument is

used to run two different methods that

may or may not use different columns

and solvents.

Meanwhile, in the test of patient

02, also potentially positive for

JWH-018 pentanoic acid, all peaks

showed up at the expected retention

times. The ion ratios passed on the

phenyl-hexyl column, but failed on

the C18 column, which is consistent

with the result of patient 01. The

data suggests the phenyl-hexyl

column significantly improved the

detection of JWH-018 pentanoic

acid metabolite in our methods

compared to the C18 column. The

fact that this patient sample fails

ion ratio (IR) on the C18 column

and passes on the phenyl-hexyl

possibly indicates that an interferent

coeluted with one or both of the

C18 peaks, thereby throwing off the

ion ratio. Cannabinoids (synthetic

or otherwise), due to their chemical

makeup, are generally fat soluble

and by extension they also tend to be

chromatographically coeluted with any

lipid content that may be in a sample.

It is possible that this interferent,

which is throwing off the ion ratio in

the C18 sample, is a lipid component

that was able to survive the hydrolysis

and extraction protocol to be coeluted

on the C18 column, but on the

phenyl-hexyl column it is sufficiently

separated. It is also possible that the

compound from the patient sample

is isobaric with JWH-018 pentanoic

acid and possesses the same multiple

reaction monitoring (MRM) transitions

as JWH-018, but at different ratios

than the true calibrator compound.

This is possible if a small change in

side chain configuration is envisioned

(for example, straight chain versus


Feng et al.

Table 4: LC–MS–MS conditions for synthetic cannabinoids in urine samples in selected studies.

Targets Purification Column Time of Gradient LOD (ng/mL) Reference

Metabolites of JWH-018

and JWH-073Dilution (hydrolysis)

Zorbax Eclipse XDB-C18 (150

mm × 4.6 mm, 5-μm)10 min <2.0 (24)


and JWH-073SPE (hydrolysis)


mm × 4.6 mm, 5-μm)10 min <0.1 (25)

Metabolites of 8 synthetic

cannabinoidsLLE (hydrolysis)

AQUASIL C18 (100 mm × 2.1

mm, 5-μm) (Thermo Scientific)14 min 0.1 (26)


and JWH-073LLE (hydrolysis)

Acquity UPLC HSS T3 (100 mm ×

2.1 mm, 1.8-μm) (Waters)

More than

3.2 min(27)

Metabolites of 7 synthetic

cannabinoidsLLE (hydrolysis)

Luna C18 (150 mm × 2 mm,

5-μm) (Phenomenex)15 min (28)

Metabolites of UR-144

and its pyrolysis productLLE (hydrolysis)


mm × 2.1 mm, 3.5-μm) (Agilent)19 min (29)

9 synthetic cannabinoids,

20 metabolitesPP (hydrolysis)

XB-C18 (50 mm × 3.0 mm,

2.6-μm) (Kinetex)10 min 0.5–10 (21)

15 indole derivative

synthetic cannabinoidsLLE (hydrolysis)

Ascentis C18 (150 mm × 2.1 mm,

5-μm) (Supelco)16 min 0.1–0.5 (30)

17 metabolites of

synthetic cannabinoidsLLE (hydrolysis)

Phenomenex Gemini C18 (150

mm × 4.6 mm, 3.0-μm)12 min 0.01–0.5 (31)

SPE = solid-phase extraction; LLE = liquid-liquid extraction; PP = protein precipitation

branched chain). The technical and

ethical issues associated with making

a positive call on such samples are

not trivial.

Next, for a suspected MAM-2201

N-(4-hydroxypentyl) metabolite,

we found that patient sample 02

showed an interfering peak, with

slightly incorrect retention time, on

the C18 column. The chemistry of this

interferent seems to be drastically

different compared to the MAM-2201

N-(4-hydroxypentyl) metabolite, since

it was not observed in the window for

the phenyl-hexyl column. These types

of interferences are rampant among

positive and questionably positive

synthetic cannabinoid patient samples.

Patient 03 had a very strong well

separated quant peak for UR-144

N -pentanoic acid, but the qual peak

showed an interferent just a few

seconds away from the targeted

retention time. This interferent made

detection of the qual peak of interest

very difficult. The qual peak is still

visible in the C18 separation; however,

the software (under reasonable

integration conditions) incorrectly

integrated the interferent. With the

phenyl-hexyl column chemistry, the

qualifier peak has coalesced into the

interferent peak entirely and is not

able to be resolved, even with manual

integration intervention. The fact that

this interferent moved proportionally

with reference to the expected UR-144

N -pentanoic acid retention time

indicates that this interferent might

share some chemical functionality as

discussed above.

Conclusions

A rapid, selective, and sensitive

LC–MS–MS method identifying 13

synthetic cannabinoids in patient

urine samples has been described.

Two different column chemistries (that

is, C18 and phenyl-hexyl) have been

applied using this method. Three

compounds, including XLR-11 N-(4-

hydroxylpentyl), UR-144 N-pentanoic

acid, and UR-144 N-(5-hydroxylpentyl)

metabolites, demonstrate the different

order of elution on a phenyl-hexyl

column compared to the C18 column,

while most of the compounds maintain

their elution order. The fact that newly

invented synthetic cannabinoids often

only slightly change the side chains of

the banned drugs makes the detection

of those compounds more difficult. At

our laboratory, synthetic cannabinoids

are requested in roughly 20% of our

total samples and therefore should

not be written off as a fringe interest in

the pain medication monitoring arena

in spite of the very low positivity rate.

Using a second LC–MS–MS method to

confirm patient positives (as illustrated

here) is potentially useful for large

scale laboratories on a daily basis

because of the low positivity rates

observed.

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Sheng Feng, Brandi Bridgewater,

Gregory L. McIntire, and Jeffrey

R. Enders are with Ameritox Ltd., in

Greensboro, North Carolina, USA.

Direct correspondence to: Jeffrey.

[email protected]

The fact that newly invented

synthetic cannabinoids

often only slightly change

the side chains of the

banned drugs makes

the detection of those

compounds more difficult.


Feng et al.

Over the course of the last several

decades, high performance liquid

chromatography–tandem mass

spectrometry (HPLC–MS–MS)

has become the method of choice

for high-throughput analysis of

small-molecule therapeutics,

metabolites, and biomarkers. This is

due, in large part, to the selectivity

and sensitivity provided by

HPLC–MS–MS, combined with the

ability to rapidly develop an assay

consisting of quick extractions and

short run times for a vast majority of

small molecules.

When presented with a new analyte

at a bioanalytical contract research

organization (CRO), the goal is

to develop a robust method with

good chromatographic resolution,

repeatable results, and a quick run

time. However, after these scientific

criteria have been met, the ultimate

end goal for any bioanalytical CRO

is productivity and efficiency —

analyzing the most samples possible

while using the minimum amount of

solvent, supplies, and resources, and

still remaining scientifically sound. In

short, the goal at a CRO is to create

the most productive method in the

most efficient manner possible, all

while using sound science. This

approach benefits not only the CRO,

but also its bioanalytical clients, and

most importantly, the end users;

patients that can receive care from

these novel therapeutics provided by

the industry.

There is an increasing trend in the

industry to monitor (possibly multiple)

metabolites, as well as a push

towards using HPLC–MS–MS for the

analysis of large molecules, including

peptides and proteins. As the

industry shifts towards the analysis

of more-complicated therapeutics,

there is a need to increase efficiency

and productivity wherever possible.

With that in mind, when developing

a new HPLC–MS–MS method for

a novel molecule, every tool in the

chromatographic arsenal should

be used to grant the best chance

of success. Perhaps the strongest,

most versatile tool in the bioanalytical

setting is the LC column. A large

reason that method development

can be performed with the amount

of efficiency necessary to function

as a CRO in today’s bioanalytical

world is the development of column

technology over the past few

decades. The reliable repeatability

of columns on the market today,

combined with the plethora of

unique column types that can be

implemented, allow for the efficient

development of an HPLC–MS–MS

method for high-throughput analysis.

Because all bioanalytical work

depends on high-throughput

analysis, many of the trends in

emerging technologies in the

bioanalytical market are directly

related to increasing on-instrument

productivity and reducing costs.

This includes smaller particle size

in columns coupled with ultrahigh

pressure liquid chromatography

(UHPLC), superficially porous shell

column technology, and microflow

HPLC. This article presents a

quick background into the details

of developing an HPLC–MS–MS

method from the perspective of a

CRO in relation to column choice.

It also focuses on recent column

technologies, the instrumentation

surrounding them, and their benefits

in a CRO environment.

Method Development

High-throughput bioanalysis CROs

are usually a fast-paced environment,

where it is necessary to create a

productive, rugged method from the

ground up for what is often times an

unknown novel therapeutic. A large

part of a CRO’s efficiency stems

from its ability to quickly develop a

rugged method that will repeatedly

hold up to rigorous industry and

regulatory standards. As efficiency

can often be derived from simplicity,

when developing a new method the

simplest solution is always the first

approach. This is why, despite the

HPLC Column Technology in a Bioanalytical Contract Research

OrganizationRyan Collins and Shane Needham, Alturus Analytics, Inc., Moscow, Idaho, USA.

High performance liquid chromatography–tandem mass spectrometry (HPLC–MS–MS) is the go-to technique

for high-throughput analysis of small-molecule therapeutics, metabolites, and biomarkers. Through

technological advancements in the last decade, developing quality methods for a novel analyte in the

contract research environment has become easier and faster than ever. Increasingly shorter run times, higher

sensitivity, and greater separation have all become possible in a standard method. This is, in part, because

of column technologies that have enabled the standardization of the method development process. Method

efficiency and productivity are also improving because of emerging column technologies such as sub-2-μm

particles coupled with ultrahigh-pressure liquid chromatography (UHPLC)–MS–MS, superficially porous

particle columns, and microflow HPLC–MS–MS. Increasing efficiency and productivity in high-throughput

bioanalysis is becoming more important as the applications for HPLC–MS–MS expand to large molecules

such as peptides, proteins, and oligonucleotides.


plethora of columns available for use,

it is almost always best to start with

a C18 or C8 column. One of the most

versatile and widely used columns,

the C18 column has been in use in

one form or another for decades.

Comprising a simple octadecyl

carbon chain bonded silica-based

stationary phase, the C18 column is

the go-to column of choice for a large

majority of molecules analyzed by

HPLC–MS–MS. C18 columns have

proven to provide good retention and

resolution for a vast array of small

molecules.

With a proven track record

of negligible lot-to-lot and

column-to-column variability, there

is minimal concern of anomalous

behaviour throughout the life of a

method on a C18. C18 columns

also tend to be very rugged, with

the average lifespan lasting for

upwards of thousands of injections.

This is a very important point in

the development of any method;

if a seemingly scientifically sound

method has been developed, but

the column only lasts a few hundred

injections before peak deterioration,

then the method probably isn’t

rugged or productive enough to

be feasible. A large benefit in the

flexibility of the C18 is that it allows

for the standardization of many

HPLC–MS–MS methods, which

greatly increases the productivity

of high-throughput analysis. With

multiple standardized methods

relying on one type of column and

identical mobile phases for an array

of molecules, it is possible to keep

instruments running continuously

without interruption. This is crucial to

the high-volume requirement in the

bioanalytical CRO world.

However, there are always going

to be analytes that do not work on a

C18 column. For multiple analytes,

resolution (Rs) and chromatographic

selectivity (α) will play a role.

However, here we focus on method

development of one analyte. Whether

due to poor retention (tR), poor

asymmetry factor (AF), or poor

repeatability, decisions can then

be made on what type of specialty

column to look at. This process can

quickly become overwhelming given

the plethora of columns and column

types on the market today. Having

an approach to address the most

common column-based issues during

method development, as seen in the

flowchart in Figure 1, is an important

aspect in maintaining efficiency

during method development. Once it

has become apparent that a method

will not be adequately developed

on a C18 column, the next step

is typically to evaluate the polar

moieties and functional groups

exhibited by the molecule. For a polar

molecule, some of the more common

approaches available are to choose

a polar endcapped column or to

implement an ion-pairing reagent

(where an ion-pairing reagent such

as heptafluorobutyric acid [HFBA]

is added to the mobile phases or

extraction solvents). When presented

with a particularly small, polar

molecule, another option available

is to choose a column such as an F5

column (a pentafluorophenylpropyl

stationary phase) or to use

The goal is to develop

a robust method with

good chromatographic

resolution, repeatable

results, and a quick

run time.


Collins and Needham

Is it a chiral molecule?

Is it a mobile phasemismatch?

Polarendcapped

column

Look at the functional groups andselect specialty column

Is it a mobile phasemismatch?

Chiral column

No

C18

Yes

No No

F5

C18

Ion pairing HILIC

Yes Yes

NonpolarPolar

Good tR

and good AF Good tR

and poor AFPoor tR

and good AF

Key

tR

= Retention time

AF = Asymmetry Factor

Poor tR

and poor AF

Figure 1: Representative column method development flowchart.

2-μm solid core

0.5-μm shell (3 μm total) 3-μm fully porous particle

Figure 2: Representative structure of SPP and fully porous particles.

a hydrophilic-interaction

chromatography (HILIC) method.

HILIC methods use gradients with a

high percentage of organic content

coupled with either an unmodified

silica column, an amino column, a

zwitterionic column, or any one of a

number of columns made specifically

for HILIC methods.

Recent Column Advancements

Although efficiency in method

development is paramount to being

cost effective in a bioanalytical

CRO environment, this efficiency

would amount to nothing if the

actual methods themselves were

not productive in the long run. Even

if all the scientific benchmarks may

have been met during development,

the overall costs of performing the

method determine whether it will

actually be feasible. The costs of a

method are largely determined based

on two factors: the overall costs of

disposable supplies (for example,

extraction supplies, solvents, and

columns) and time. With this in mind,

it is no surprise that many of the

emerging technologies in the industry

seek to minimize both of these

aspects of HPLC–MS–MS.

One such way to increase

HPLC–MS–MS productivity that has

been developed and implemented

in the past decade is the decrease

in column packing particle size.

Traditionally, the packing in LC

columns has been made up of

fully porous particles ranging in

size from 3 to 10 μm. However, by

decreasing the particle size below

the previous standards to sub-2-μm

particles, there is an increase in

chromatographic efficiency leading

to an increase in theoretical plate

counts and, thus, greater resolution

(1). However, one of the side effects

of decreasing the particle size is

a fairly large increase in pressure,

which limited the widespread use

and commercial viability of sub-2-μm

columns until fairly recently. To

withstand the back pressures involved

with using sub-2-μm columns, new

instrumentation was devised; thus,

UHPLC was born (2,3). Using an

UHPLC system available from various

vendors, it is possible to successfully

implement smaller particle size

columns and run at pressures as

high as ~20,000 psi (4). These

UHPLC systems have proven to be

robust enough for high-throughput

bioanalysis work and have been

implemented throughout the industry.

However, since cost effectiveness

is an overall goal of a bioanalytical

CRO, it may not be the most

practical option to purchase an

entirely new HPLC system to attain

what may amount to only a slight

increase in method productivity

and decrease in run time. For

laboratories already in existence

and set up with traditional HPLC

instruments rather than UHPLC, it

is much more desirable to find a

smaller-scale solution to increase

method productivity. Another recent

advent to the column market in the

last decade, superficially porous

particle (SPP) columns take the idea

of smaller column particles to the

next, albeit somewhat divergent,

step. Rather than decreasing the

size of fully porous particles in the

columns, the idea behind SPP is

a small, solid inner core (which

generally range from 1.3 to 5 μm)

surrounded by a permeable shell of

porous silica. While the outer shell of

the particles are similar in materials

and function as a conventional


Collins and Needham

2-μm solid core

0.5-μm shell (3 μm total) 3-μm fully porous particle

Path of analyte

Path of analyte

Figure 3: Representation of possible analyte paths between SPP and fully porous

particles.

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8

Time (min)

0.0

1.0e4

2.0e4

3.0e4

4.0e4

5.0e4

6.0e4

7.0e4

8.0e4

9.0e4

1.0e5

1.1e5

1.2e5

1.3e5

1.4e5

1.5e5

1.6e5

1.7e5

1.8e5

1.9e5

2.0e5

Inte

nsi

ty (

cps)

7 μL/min, 0.2 mm i.d.

44 μL/min, 0.5 mm i.d.

700 μL/min, 2.0 mm i.d.

Figure 4: Comparative chromatogram between HPLC–MS–MS (red trace), microflow

LC–MS–MS (blue trace), and in-source column PicoFuze (green trace) from the analysis

of a surrogate peptide from MAOB from human plasma using a gradient of acetonitrile

and water with 1% formic acid on C18 columns. Stationary phase for all analyses:

Prontosil, 3 μm.

fully porous column particle, the

inner core is impermeable (hence

the term superficially porous), as

can be seen in Figure 2. Although

the idea of shell-based stationary

phases have been around since the

late 1960s, with the use of larger

(~50 μm) pellicular particles (5),

it is only recently that the particle

sizes have been reduced down to

conventional standards. With the

combination of the small diameter

of the inner core and the porous

nature of the shell, SPPs provide the

benefits of sub-2-μm fully porous

particles while eliminating many

of the back pressure issues (6,7).

Although the theory behind the

increase in efficiency attributed to

SPP columns is not discussed in

detail here, Figure 3 shows a rough

representation of how the rate of

diffusion is increased throughout an

SPP column as opposed to a column

containing fully porous particles of

comparable size. This increased

rate of diffusion relates to quicker,

more efficient separations than were

previously possible with fully porous

columns, and results in a tighter peak

shape as the shorter path reduces

the diffusion of the analytes (8).

Emerging Technologies

Yet another approach of reducing

costs and increasing efficiency

in bioanalytical analysis is the

implementation of microflow LC

coupled with a mass spectrometer.

As compared to the standard

high flow of HPLC–MS–MS, which

generally uses around a 700-μL/

min flow rate, microflow LC–MS–MS

employs the use of pumps that can

accurately deliver a flow rate of well

below 100 μL/min, greatly reducing

the consumption of solvents. This

reduction in solvent use directly

translates to a cost savings in the

purchasing of solvents, disposal

of solvent waste, and the labour

of solvent preparation — none of

which are insignificant expenses in

a high-throughput laboratory that

is virtually running continuously.

The drastically lower flow rates

associated with microflow LC–MS–

MS also translate to less solvent

flowing through the electrospray

ionization (ESI) source. This means a

cleaner MS system and a lower cost

associated with MS maintenance.

Microflow LC–MS–MS employs

columns with drastically decreased

internal column diameter. While

standard HPLC–MS–MS may use

columns with internal diameters

ranging from 2 to 4.6 mm, microflow

LC–MS–MS uses columns with

internal diameters ranging from

0.2 to 0.3 mm (micro) down to

<0.2 mm (nano), which can be

used with flow rates of 10 and

0.3 μL/min, respectively. Solvent

consumption and savings aside,

microflow LC–MS–MS has also

been documented to increase ESI

response (9) while reducing matrix

effects (10) and increasing ionization

efficiency (11). Early works on ESI

response demonstrated that as

the mobile-phase flow rate of ESI

is reduced, there is an increase in

proportional MS signal-to-noise ratio

(12).

Some of the challenges in the

integration of microflow LC–MS–MS

into the high-throughput bioanalysis

world are longer run times, dead

volumes in fittings and connections

having a greater impact on

chromatography, and a perceived

lack of robustness of microflow

instrumentation. To address some

of these challenges, work has been

performed by multiple vendors

on implementing an integrated,

in-source column. By integrating a

column directly into the source, many

of the dead volume issues related to

microflow LC–MS–MS are resolved.

The idea behind the application

is to simplify instrument setup by

minimizing connections and reducing

the length of tubing required between

the LC injector and the MS, and thus

minimizing the impact of pre-column

and post-column volumes. As shown

in the corresponding chromatogram

in Figure 4, the combination of a

micro internal diameter column

integrated into the source coupled

with microflow LC–MS–MS provides a

greatly increased signal as compared

to HPLC–MS–MS; in addition, the

system maintains a run time of less

than 5 min. With the possibility

of a system that is generating

higher sensitivity (among other

chromatographic benefits) coupled

with lower flow rates leading to lower

solvent consumption, microflow

LC–MS–MS combined with

integrated, in-source columns seems

to be a highly promising direction for

high-throughput bioanalysis.

Conclusion

With the advancements in column

and other LC technology in recent

years, developing robust methods

for novel therapeutics has become

a more reliable process than ever.

It is possible to efficiently create

productive methods for molecules

of ever-increasing complexity. This

will become more important in

years to come as HPLC–MS–MS is

increasingly looked to as the solution

for analysis of large molecules

including peptides, proteins, and

biomarkers. Increasing efficiency

and productivity on both the front

end (method development) and

back end (sample analysis) will be

made continuously possible with

further advancements such as SPP

columns and microflow LC–MS–MS.

Looking to the future, the expectation

for the pharmaceutical and biotech

industries will be to supply the

global community with therapeutics

at a reasonable cost. Thus, the

highest levels of productivity and

efficiency will be paramount to meet

this goal.

References(1) J.E. MacNair, K.C. Lewis, and J.W.

Jorgenson, Anal. Chem. 69, 983–989

(1997).

(2) J.E. MacNair, K.D. Patel, and J.W.

Jorgenson, Anal. Chem. 71, 700–708

(1999).

(3) N. Wu, J.A. Lippert, and M.L. Lee, J.

Chromatogr. A 911, 1–12 (2001).

(4) “In the News”, Trends Anal. Chem. 61,

iv–x (2014).

(5) C. Horváth, B.A. Preiss, and S.R.

Lipsky, Anal. Chem. 39, 1422 (1967).

(6) J.J. DeStefano, T.J. Langlois, and J.J

Kirkland, J. Chrom. Sci. 46, 254–260

(2008).

(7) D.V. McCalley, J. Chromatogr. A 1218,

2887−2897 (2011).

(8) G. Guiochon and F. Gritti, J.

Chromatogr. A 1218, 1915–1938 (2011).

(9) G. Valaskovic and N. Kelleher, Curr.

Top. Med. Chem. 2(1), 1–12 (2002).

(10) E. Gang, M. Annan, N. Spooner, and P.

Vouros, Anal. Chem. 73(23), 5635–5644

(2001).

(11) R. Juraschek, T. Dulcks, and M. Karas,

J. Am. Soc. Mass Spectrom. 10,

300–308 (1999).

(12) P. Kebarle and L. Tang, Anal. Chem. 65,

972A–986A (1993).

Ryan Collins and Shane Needham

are with Alturus Analytics, Inc.,

in Moscow, Idaho, USA. Direct

correspondence to: sneedham@

alturasanalytics.com


Collins and Needham

The development of biological-based

pharmaceuticals is growing. In

2012, of the top selling 200 drug

products in the United States 25%

were based on a biological entity (1).

It is anticipated that by 2020 52%

of all top selling drugs will fit into

this category (2). These continuing

trends will have strong implications

for the analytical techniques used to

characterize these large-molecule

products. Chromatographic

separations will still play a key

role not only in the purification of

these biologics, but also in the

analysis from the early phases of

product development to the final

quality control of formulations.

Continued improvements in

liquid chromatography (LC)

column materials to cope

with higher-molecular-weight

biopharmaceuticals will be needed.

Many of the attributes for optimized

chromatographic packings that have

been developed for small-molecule

drugs will not always directly

extrapolate to those needed for

these biological-based drugs. For

example, LC separations requiring

nondenaturing conditions will not

tolerate high concentrations of

organic mobile phases or, when LC

coupled to mass spectrometry (MS)

is used, high amounts of nonvolatile

salt buffers. New workflows may be

required to ensure that the analysis

conditions do not cause degradation

of sensitive biomolecules. The

complexity of new biological drugs

may require much greater levels

of resolution than was required for

well characterized small-molecule

drugs. Two-dimensional (2D)

chromatographic separations may

become the norm for some of these

drugs, especially when biosimilars

are undergoing characterization.

Monoclonal Antibodies and

Aggregation

Monoclonal antibodies (mAbs)

are in favour since they are highly

specific and often bind to a

single antigen target. The cellular

processes to produce mAbs are

complex, however, and multistep

purification procedures subject

the protein to numerous changes

in their environment. Like many

recombinant proteins that are

inherently unstable, the increased

degree of handling of the mAbs may

cause conformational changes and

increased levels of aggregation with

the possibility of visible precipitation

and invisible soluble aggregates. At

the molecular level, the process of

mAb aggregation is complex with a

possible loss of its three-dimensional

(3D) structure by interacting with

other protein molecules. Aggregation

can be reversible or irreversible

and, in some cases, the protein

can become irreversibly denatured

thereby losing its bioactivity. There

are many mechanical stress and

chemical conditions that can cause

or change aggregation including

storage, interactions with surfaces

or solids, flow or agitation, and

temperature changes. An earlier

paper (3) provided more details

of the upstream and downstream

processes that can affect mAb

aggregation including the method of

analysis.

The impact of aggregation on the

process economics (product yield),

efficacy (decreased bioactivity),

and immunogenicity (recipient

immune system response) are

considerable, thus, reliable and

accurate methods of analysis and

quantitation are required. Although

there are a number of traditional

methods commonly used to

measure aggregation (see Figure 1),

the technique of size-exclusion

chromatography (SEC) is a required

technique for soluble aggregation

analysis and quantitation.

Size-Exclusion

Chromatography

Unlike all other modes of high


(HPLC), pure SEC involves absolutely

no interaction between the analyte

Characterizing SEC Columns for the Investigation of Higher-Order

Monoclonal Antibody Aggregates

Ronald E. Majors1 and Linda L. Lloyd2, 1Column Editor Emeritus for LCGC, 2Agilent Technologies,

Church Stretton, Shropshire, UK.

With many new biopharmaceuticals now being developed, robust analytical methods are needed to

ensure that these protein-based drugs are of high purity and safe with a minimum amount of side effects.

Size-exclusion chromatography (SEC) is an important technique for investigating purity and is useful to

identify and monitor protein aggregation, which can have economic and immunogenicity effects. This

article discusses those column parameters that are most important in the selection of the optimum phase

for SEC separations.

Chromatographic

separations will still play

a key role not only in the

purification of biologics,

but also in the analysis

from the early phases of

product development to

the final quality control of

formulations.


and the packing material. The

molecules are separated based on

differences of size in solution, their

hydrodynamic volumes. Figure 2

shows a schematic of the differential

flow paths as a function of molecular

size along with the associated

chromatogram. The SEC packing

material consists of neutral, porous,

spherical particles with a defined

pore size. The “fit” of the molecule

into the porous structure will

determine its residence time inside of

the packing. The largest molecule,

depicted in green in Figure 2, will not

permeate very far into the pore, if at

all, and it will move down the packed

bed virtually unretained and will be

eluted first from the column. The

blue molecule, being smaller in size,

will permeate further into the pore,

spend more time inside the packing,

and will be eluted from the column

after the largest green molecule. The

red molecule, being the smallest

in size, will permeate well into the

porous packing and spend the most

residence time there and will be

eluted after the blue molecule. Thus,

as depicted in the chromatogram of

the right hand side of Figure 2, the

order of elution is green (large), blue

(intermediate), and red (small).

The pore size of an SEC column

will define the molecular sizes that

can be resolved — anything that

is bigger than the pore opening

will be excluded and all molecules

equal to or larger than the pore will

be eluted at the exclusion volume

(Ve), sometimes referred to as the

interstitial volume (Vi), of the column

and the smallest molecules that

permeate all of the pore volume will

be eluted at the total permeation

volume (V0). These two volumes

define the elution volume–resolving

range of the column and all

separation must take place within

these two volumes. Thus, SEC is

quite different from the other LC

modes that can have the separation

take place over many column

volumes. Also, for SEC, the elution

order is unlike other LC modes such

as reversed phase chromatography

where the larger, more-hydrophobic

molecules are eluted last and the

smaller, more-hydrophilic molecules

are eluted first.

How is the SEC data used? Most

frequently, a calibration curve is

first generated (see Figure 3). In

this plot, the log of the molecular

weight (MW) of known protein–

peptide standards are plotted versus

retention time (or elution volume).

In Figure 3, a protein–peptide

standard mix consisting of various

known molecular weight compounds

was used to make up this plot.

The proteins, peptides, and their

respective MWs are identified in the

figure caption. The calibration plots

are generally-fitted to a polynomial.

Because the SEC separation is

based on the hydrodynamic volume

of a molecule in solution and not

solely on MW, any extrapolated MW

is referred to as apparent MW. In

this example, an unknown sample

solution of protein containing a small

amount of its dimer was injected onto

a modern SEC column containing

a packing with a 300-Å pore size.

By noting the retention time on the

calibration curve of 8.6 min, the

apparent MW of the main compound


Majors and Lloyd

Dynamic light scattering

Static light scattering

Aggregates Particles

AUC

SEC Microscope

Counter principle

Flow imaging microscopy

Light microscopy

Monomersoligomers

Visible particlesSubvisible particles

10 100 10 100 10 100mmnm μm cm

Visual inspection

FFF-MALS

Figure 1: Classical techniques for aggregate determination — SEC is used for the

quantitation of the soluble aggregates that are typically less than 80 nm in size.

Figure 2: Mechanism of SEC in the separation of different sizes of molecules. Molecules

can permeate the pores of the stationary phase to different extents depending on their

size in solution. The largest molecules (green circles) cannot permeate the pores and are

eluted first, the small molecules (red circles) can permeate all of the pore structure and

are eluted last. Molecules that have a size between these two (blue circles) will partially

permeate the pores and will be eluted between these two limits.

was determined to be 18.4 kDa,

which coincides with the MW of

β-lactoglobulin. The small peak

eluted just before the major peak

has a retention time of 8.3 min,

which from the calibration curve is

determined to have an apparent MW

of 37 kD and thus was estimated

to be the β-lactoglobulin dimer. By

measuring the relative peak areas

one could estimate the level of

dimer in the original solution. For

an absolute MW, another method

beyond ultraviolet (UV) or refractive

index detection must be used. Most

often a light scattering (LS) detector

is used to provide absolute MW and

also provides an increased sensitivity

for the higher MW aggregates. A

mass spectrometer can also be used

to measure an absolute MW and

provide structural identification for

unknown impurity peaks.

Characterization of SEC

Columns for mAb Analysis

Now that we have introduced

the concept of SEC and how the

separation mode can be used

to separate biomacromolecles

and higher order earlier eluted

aggregates, we would like to look

at those characteristics of packed

SEC columns that can be used to

optimize their ability to provide the

best resolution of mAb monomers

from higher order aggregates in the

shortest possible time. The overall

desire is for the SEC column to

deliver accurate separation and

precise quantitation. A typical SEC

column has notable parameters that

define its separation characteristics,

some unique to the SEC mode

and some that are well known

chromatographic principles. Table 1

provides typical column parameters

that are useful for comparison with

advantages and disadvantages

The impact of

aggregation on the

process economics

(product yield), efficacy

(decreased bioactivity),

and immunogenicity

(recipient immune

system response) are

considerable.


Majors and Lloyd

Retention time (min)

Log

(M

W)

4.002.00

2.50

3.00

3.50

4.00

4.50

5.00

5.50

6.00

6.50

5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00

Unknown is β-lactoglobulinMW 18.4 kD

β-Lactoglobulin dimer, apparentMW 37 kD

Ovalbumin, 44.3 kD

8.2

41

7.8

42

10.0

25

Myoglobin, 17 kD

Figure 3: Determination of equivalent molecular weight of an unknown protein. A

calibration curve is constructed using proteins and peptides of known molecular weight

and as small molecule, uracil. By plotting the retention time against molecular weight the

polynominal fit equation can be used to calculate the equivalent molecular weight from

the retention time of the unknown. Column: 300 mm × 7.8 mm, 2.7-μm dp AdvanceBio

SEC, 300 Å (Agilent Technologies); eluent: 150 mM sodium phosphate, pH 7.0; flow

rate: 1.0 mL/min. Molecules for calibration, left to right: thyroglobulin dimer (Ve marker),

1340 kDa; thyroglobulin, 670 kDa; IgG dimer, 300 kDa; IgG, 150 kDa; ovalbumin dimer,

88.6 kDa; ovalbumin, 44.3 kDa; myoglobin, 17 kDa; aprotinin, 6.5 kDa; neurotensin,

1.7 kDa; angiotensin II, 1.05 kDa; uridine (V0 marker) 0.24 kDa.

Figure 4: Example calibration curves for 130-Å and 300-Å pore size SEC columns: (a)

300 mm × 7.8 mm, 2.7-μm dp AdvanceBio SEC 130 Å; (b) 300 mm × 7.8 mm, 2.7-μm

dp AdvanceBio SEC 300 Å. Eluent: 150 mM sodium phosphate, pH 7.0; flow rate: 1.0 mL/

min. Compounds used to construct calibration curve are the same as in Figure 3.


4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00

Thyroglobulin

lgG dimer

dimer

Ovalbumin

Ovalbumin

Myoglobin

Aprotinin

Neurotensin

Angiotensin II

Uridine

lgG

Thyroglobulindimer

Log

(M

W)

2.00

2.50

3.00

3.50

4.00

4.50

5.00

5.50

6.00

6.50(a)


4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00

Thyroglobulin

lgG dimer

dimerOvalbumin

Ovalbumin

Myoglobin

Aprotinin

NeurotensinAngiotensin II

Uridine

lgG

Thyroglobulindimer

(b)

Log

(M

W)

2.00

2.50

3.00

3.50

4.00

4.50

5.00

5.50

6.00

6.50


Majors and Lloyd

Table 1: Important parameters in the characterization of an SEC column.

Column Parameter

Influences Advantages Disadvantages Comments

Particle

pore size

Defines molecular

sizes that can

be resolved

(separation range)

Large pore sizes allow

separation of larger

macromolecules; small pore

sizes for smaller biomolecules

One pore size column may not

resolve both large and small

biomolecules in same sample;

may require columns in series

with different pore sizes

Calibration curves provide

guidance for separation

range of SEC column; typical

pore sizes for SEC are 100,

200, 300, 450, and 500 Å

Pore size

distribution

(PSD)

Separating range

Narrow PSD columns will

provide higher resolution over

a narrow range of molecular

sizes

Narrow PSD will provide lower

resolution over a wide range

of molecular sizes

The alternative wider PSD will

provide wider fractionation

range but calibration curve

will have a steeper slow

Pore volume

of packingResolution

Larger pore volume extends

useful range of calibration

curve giving higher resolution

and accuracy

Small pore volume may not

allow resolution of close

molecular sizes

Difficult to make stable

silica-based particles with

large pore volume

Pore volume

of columnResolution

Longer columns or multiple

columns extend separation

range by increasing total pore

volume

Additional columns slow

down separation and

increase the cost

Multipore columns have

been developed but single

multipore columns have

limited resolution

Particle size Column efficiency

Smaller particles provide

narrower peaks and therefore

better resolution and better

sensitivity than larger

particles

Smaller particles give rise

to higher back pressure,

may generate frictional

heating; may require lower

band dispersion and higher

pressure rated instrument to

get full efficiency gains

Small particles used with

high flow rates may induce

shear degradation of large

biomolecules and are more

likely to clog with large

molecules; typical particle

sizes are 1.7, 2.7, 5, and 10 μm

Column length ResolutionLonger or multiple columns

give better resolution

Longer or multiple columns

give longer analysis times,

greater pressure drop, and

cost more

Typical modern SEC

columns are 150 or 300 mm

in length

Column

internal

diameter

Speed and

sensitivity

Narrow internal diameter

columns have greater

sensitivity and are suitable for

use with MS detection

Wide internal diameter

columns are more robust and

less impacted by instrument

dispersion; larger sample

capacity for LS detectors

Typical modern column

internal diameters are 4.6

and 7.8 mm

Nonspecific

interactions

Resolution,

sensitivity

No significant advantages for

pure SEC size separations

May cause peak tailing, peak

loss, low recovery, peak

elution outside of operating

range of SEC column, and

loss of sensitivity

Overall quantitation,

accuracy, and reproducibility

is affected; surface

deactivation procedure with

hydrophilic properties is

paramount

Flow rateSpeed and

efficiency

High flow rates decrease

analysis time, may affect

efficiency and raise pressure

Low flow rates increase

analysis time, increase

efficiency, and lower pressure

Compromise must be made

just like any chromatographic

experiment

Particle stabilityColumn lifetime

and performance

Robust silica-based

particles stand up to UHPLC

conditions and allow higher

pressure operation

Unstable particles create

voids, give higher back

pressure as they break down,

and create problems with LS

and MS detectors.

Modern particles are

generally engineered to

withstand UHPLC conditions;

older particles may not

handle as well

Column

stabilityReplacement costs

Longer lifetime and higher

number of injections result in

overall savings; allow higher

flow rates and pressures

Long lifetimes present no

disadvantages as long as

separation persists

Modern HPLC and UHPLC

columns should provide a

minimum of 1000 injections,

often more with good

laboratory practice

Batch-to-batch

and column-

to-column

reproducibility

Data

reproducibility and

quantitation

Reproducible batches

of packings and packed

columns provide data

integrity and eliminate

unnecessary revalidation

Nonreproducibility of packing

and columns provides

nonrugged methods and lots

of rework

Manufacturers should ensure

that their products meet the

performance needs of their

customers.

listed. Out of this large number of

parameters, we shall now look at the

more important ones and see if these

parameters can be tested to meet

the separation requirements.

Effect of Pore Size on SEC

Resolution: One must select the

proper pore size to allow adequate

resolution for molecules of interest.

Figure 4 shows the results of a

calibration curve of the standard

protein mixture on two different

columns with the same dimensions

but with different pore sizes, 130 Å

and 300 Å. The molecular weights

of the compounds in the protein–

peptide test mixture goes from the

thyroglobulin dimer (MW 1340 kDa) to

the V0 marker uridine (MW 0.24 kDa).

For the smaller-pore-size column,

the largest molecules IgG dimer,

thyroglobulin, and the thyroglobulin

dimer are totally excluded from all the

pores of the packing and are eluted

in a single volume (Figure 4[a]).

Other more moderate sized proteins

and dimers are separated nicely on

this column. For the larger-pore-size

column (300 Å), the entire range

of proteins and peptides can be

adequately resolved and it would

be the column of choice if a large

range of proteins and peptides

were encountered (Figure 4[b]).

In addition, the larger-pore-size

column also possesses a larger

pore volume, which allows for

better resolution throughout the

chromatogram. Sometimes one can

achieve improvements in resolving

range by coupling two columns with

different pore sizes in series — say a

200-Å column and a 450-Å column

— but run times are increased as is

added expense in purchasing two

columns instead of one. For increased

resolving power, one can also add

additional columns of the same pore

size to increase the total pore volume

and hence resolution between peaks.

Effect of Column Dimensions and

Flow Rate on SEC Separations:

In recent years, faster separations

became the name of the game. As

the number of samples increase and

laboratory personnel are pushed for

higher productivity, everybody wants

to do things faster. In the past, SEC

columns were considered somewhat

fragile, especially when the soft gels

were used in low-pressure columns.

Most laboratories practising HPLC

and ultrahigh-pressure liquid

chromatography (UHPLC) have

high-pressure systems available

that can achieve fast separations

in a matter of minutes. Although

SEC has some limitations of column

dimensions (smaller column lengths

and volumes mean lower resolution

because of decreased pore volume

availability), there has been a

tendency to shift from the standard

7.8-mm i.d. SEC columns to those

diameters more popular in HPLC,

such as 4.6 mm. Figure 5 shows a

separation of protein standards on

300-Å columns 300 mm in length,

but with 7.8-mm and 4.6-mm internal

diameters. The 7.8-mm column run

at 1.0 mL/min gave a separation

time of just under 12 min as did the

4.6-mm column run at same linear

velocity (0.35 mL/min). Compared

to the 7.8-mm i.d. column, the

overall resolution for the 4.6-mm

i.d. column was barely impacted

for these proteins. However, the

One must select the

proper pore size to allow

adequate resolution for

molecules of interest.


Majors and Lloyd

Figure 5: Separation of protein standards on 7.8-mm and 4.6-mm i.d. columns. Upper

chromatogram: 300 mm × 4.6 mm, 2.7-μm dp AdvanceBio SEC 300 Å, 0.35 mL/min.

Lower chromatogram: 300 mm × 7.8 mm, 2.7-μm dp AdvanceBio SEC 300 Å, 1.0 mL/

min. Eluent: 150 mM sodium phosphate, pH 7.0.

300 mm x 4.6 mm

Time (min)

Ab

sorb

an

ce (

mA

U)

Flow rate: 0.35 mL/min

Injection volume: 2 μL

300 mm x 7.8 mm

Flow rate: 1.0 mL/min

Injection volume: 6 μL

200

175

150

125

100

75

50

25

0

Ab

sorb

an

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mA

U) 200

175

150

125

100

75

50

25

2 4 6 8 10 12 14

2 4 6 8 10 12 14

0

Rs 1.82

Rs 2.12

Rs 1.91

Rs 2.23

Figure 6: Further increasing the speed of analysis by increasing flow rate when using a

150-mm-long column. Inset shows all three chromatograms overlaid indicating no or little

loss in resolution with flow rate.

Time (min)

Time (min)Ab

sorb

an

ce (

mA

U)

Ab

sorb

an

ce (

mA

U)

Monomer

DimerTrimerHigher orderaggregates

Mobile phase: 150 mM sodium phosphate, pH 7.0

Flow rate: 0.5mL/min

Sample: lgG 19640

; 1.0mL/min ; 1.5mL/min

140

120

100

80

60

40

20

0

140

120

100

80

60

40

20

0

0 2 4 6 8 10 12 14

2 4 6 8 10 12 14

amount of injected sample required

for a 4.6-mm i.d. column is smaller

so in sample-limited situations,

a 4.6-mm i.d. column would be

preferred. The injected volume is

adjusted downwards based on

the inverse square of the column

radii. In addition, a lower flow rate

for the 4.6-mm i.d. column saves

mobile phase. For applications

requiring the use of less-sensitive

detectors including light scattering

and refractive index detectors and

longer UV detector wavelengths

(when using mobile-phase eluents

that have a high background at

lower wavelengths, for example),

then 7.8-mm i.d. columns offer the

capability to handle much larger

sample volumes.

Newer SEC packings that are

more rigid and robust can withstand

higher operating pressures. Thus,

separation times can be shortened

even further by using higher flow

rates. Figure 6 shows results using

a 4.6-mm i.d. column with an even

shorter column length of 150 mm,

which in itself allows for a decrease

of 50% of the run time observed

with the popular 300 mm columns. A

series of chromatograms of an IgG

sample containing dimers, trimers,

and higher order aggregates was

generated at three flow rates: 0.5,

1.0, and 1.5 mL/min; the total run

times were determined to be 12, 6,

and 3 min, respectively. The inset

chromatogram included in Figure 6

shows that all three chromatograms

— when normalized for time and

aligned — gave virtually complete

overlap without any sacrifice in

resolution. Thus, an increase in

sample throughput of a factor

of three was achieved while the

chromatographic resolution was

maintained.

Particle Size of SEC Packing: As

with any form of chromatography,

the particle size is an important

parameter. In aqueous SEC,

sometimes referred to as gel filtration

chromatography, original particles

were quite large (in the tens of

micrometres) and quite soft (for

example, polydextran and agarose).

Modern SEC packings are closer to

the range of other HPLC packings,

with 5 μm having been the standard

diameter for many years. More

recently, particles in the 3-μm range

have become more popular and

even a few sub-2-μm packings have

been introduced. The larger-pore

silica-based SEC packings (>300 Å)

become more fragile and sub-2-μm

particles generate too high of a

pressure drop for long-term stability,

so most manufacturers have settled

on particle diameters of 2.5–3 μm for

these products.

Of course, in SEC, particle size is

only part of the equation. The pore


Majors and Lloyd

Figure 7: Comparison of various commercial SEC columns of varying particle size and

pore size. The sample consists of the same standards used in Figure 5.

1

1

1

1

2

2

2

2

2

2

2

2

1

1

1

1

3

3

3

3

3

3

3

3

4

4

4

4

4

4

4

4

5

5

5

5

5

5

5

5

6

6

6

6

6

6

6

6

750

500

250

0

5 10 15

750

500

250

0

Vendor A, 5 μm, 250 A

Time (min)

5 10 15

Time (min)

5 10 15

Time (min)

5 10 15

Time (min)

5 10 15

Time (min)

5 10 15

Time (min)

4 62 8 10 12 14

Time (min)

4 62 8 10 12 14

Time (min)


Vendor B, 3.5 μm, 200 A



Vendor C, 2.7 μm, 300 A



Ab

sorb

an

ce (

mA

U)

Ab

sorb

an

ce (

mA

U)

750

500

250

0Ab

sorb

an

ce (

mA

U)

750

500

250

0Ab

sorb

an

ce (

mA

U)

750

500

250

0Ab

sorb

an

ce (

mA

U)

750

500

250

0Ab

sorb

an

ce (

mA

U)

750

500

250

0Ab

sorb

an

ce (

mA

U)

750

500

250

0Ab

sorb

an

ce (

mA

U)

size comes into play to a greater

extent than in other LC modes. This

can be clearly seen in Figure 7 where

several popular commercial products

of different particle sizes and pore

sizes are compared. The sample was

a standard protein mixture. Figure 7

is organized by the largest particle

size at the top and the smallest

currently available particle size

at the bottom. The pore sizes are

shown next to each chromatogram.

The column dimensions were

300 mm × 7.8 mm, except for the

two bottom chromatograms that

were obtained using columns with

smaller internal diameters, 4.6 mm,

which are especially designed for

more-sensitive methods. Although,

the particle size of the smallest

SEC packing is 1.7 μm, the pore

size (200 Å) is not sufficiently large

enough to resolve the thyroglobulin

dimer from thyroglobulin and thus

for the purposes of this study, a

larger-pore-size column would be

required. To resolve the monomer

and dimer, one would have to resort

to a larger-pore-size packing (300 Å

or 450 Å) with a larger particle size.

It is readily apparent, as one scans

down the figure for the various

columns, particle size appears to

have a minimal influence of resolution

for this test mix while pore size is

more influential.

Batch-to-Batch and

Column-to-Column

Reproducibility: For validated

methods, it is imperative that each

batch of column packing behave

like its predecessors. As part of

any ruggedness test protocol, most

biochromatographers are required

to investigate multiple batches (at

least three) and multiple columns

to ensure that the method can be

reproduced over a long period of

time. Figures 8 and 9 show four

chromatograms indicating the

reproducibility of four batches of

manufactured material. Batches were

tested with a standard protein mix

(Figure 8) as well as a test of the

target analytes that are higher-order

aggregates from the monomeric

mAb (Figure 9). The resolution of

the myoglobin–ovalbumin pair was

used for batch-to-batch comparison

(Figure 8), while the resolution of

the mAb dimer and mAb monomer

was used for the target analyte test


Majors and Lloyd

Figure 8: Batch-to-batch reproducibility of SEC columns for protein standards. Column:

300 mm × 7.8 mm, 2.7-μm dp AdvanceBio SEC 300 Å; mobile phase: 150 mM sodium

phosphate, pH 7.0; flow rate: 1.0 mL/min. Protein standards: 1 = thyroglobulin dimer,

2 = thyroglobulin, 3 = IgA, 4 = IgG, 5 = ovalbumin dimer, 6 = ovalbumin,

7 = myoglobin, and 8 = vitamin B12 (marker).

Ab

sorb

an

ce (

mA

U)

150

Batch 6273369

Rs = 2.12

Batch 6273380

Rs = 2.17

Batch 6279525

Rs = 2.12

Batch 6277528

Rs = 2.12

Ovalbumin Myoglobin

100

50

0

Ab

sorb

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mA

U)

150

100

50

0

Ab

sorb

an

ce (

mA

U)

150

100

50

0

Ab

sorb

an

ce (

mA

U)

150

100

50

0

2 4

4.6

30

5.1

07

4.6

04

4.5

76

4.9

81

5.4

63

6.3

02

7.0

29

7.9

13

8.5

62

11

.16

51

1.3

228

.87

8

8.2

50

6.6

64

7.3

78

5.7

84

5.2

60

4.7

38

5.0

82

5.5

74

6.4

33

7.1

53

8.0

34

8.6

72

11.2

12

5.6

23

6.4

98

7.2

28

8.4

16

8.7

62

11.3

23

6 8 10 12 14Time (min)

2 4 6 8 10 12 14Time (min)

2 4 6 8 10 12 14Time (min)

2 4 6 8 10 12 14Time (min)

Figure 9: Batch-to-batch reproducibility of SEC columns for target analytes. Column:

300 mm × 7.8 mm, 2.7-μm dp AdvanceBio SEC 300 Å; mobile phase: 150 mM sodium

phosphate, pH 7; flow rate: 1.0 mL/min; sample: mAb and its dimer.

Ab

sorb

an

ce (

mA

U) 80

60

40

20

0

Ab

sorb

an

ce (

mA

U) 80

60

40

20

0

Ab

sorb

an

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mA

U) 80

60

40

20

0

Ab

sorb

an

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mA

U) 80

60

40

20

0

4.5

89

4.5

56

5.1

51

5.5

82

6.4

36

7.7

72

11

.80

91

1.8

34

11

.85

3

7.9

97

6.6

66

5.7

98

5.3

50

4.6

98

7.6

41

6.3

04

5.4

74

5.0

62

4.5

43

5.1

98

5.6

29

6.4

92

7.8

47

11

.90

8

Batch 6273369

Rs = 1.92

Batch 6273380

Rs = 1.99

Batch 6279525

Rs = 1.90

Batch 6277528

Rs = 1.96

mAb dimer mAb monomer

2 4 6 8 10 12 14

Time (min)

2 4 6 8 10 12 14

Time (min)

2 4 6 8 10 12 14

Time (min)

2 4 6 8 10 12 14

Time (min)

(Figure 9). Rather than testing each

column with a series of proteins

and mAb aggregate samples, for

quality control purposes, an inert

small molecule is used to ensure that

the column is packed according to

specification. Therefore, users can

be assured that the column that is

received has not seen any protein

sample. In addition, to prevent any

possibility of bacterial growth during

shipping or storage, most SEC

columns are shipped and stored in

a solvent such as a 0.02% sodium

azide or a solvent rich in organic

solvent. Before use, columns from

any vendor should be thoroughly

rinsed with the mobile phase that will

be used for SEC.

Particle, Phase, and Column

Stability: SEC columns are

expensive, and all precautions taken

with any HPLC or UHPLC column

should also be observed with SEC

columns. Most of the aqueous SEC

columns used for protein–peptide

size separations are based on

spherical silica gel, which has

been produced by any number of

synthesis procedures. Silica gel is a

more rugged packing than the soft

gels of yesteryear, but nevertheless

does require some care in its use.

SEC columns do have defined pH

limits, upper pressure limits, upper

temperature limits, and so on —

the biochromatographer should

be familiar with these attributes

before use. To cut down or eliminate

nonspecific surface interactions,

silica gel SEC columns require some

surface deactivation by bonding,

coating, or building into the phase

strong hydrophilic characteristics.

The bonding of the diol functionality

appears to be the favoured approach

to provide a hydrophilic surface, but

newer approaches such as bonding

with a hydrophilic polymer may prove

to be more successful. If proteins

are allowed to interact with the silica

surface, sample integrity may be

compromised. Tailing, irreversible

For validated methods,

it is imperative that

each batch of column

packing behave like its

predecessors.


Majors and Lloyd

Figure 10: Column lifetime study of mAb and its dimer and higher order aggregates. In

this study, a use-case scenario was simulated by running a series of mAb samples with a

protein standard mix and a small molecule before and after each mAbs sequence. After

each sequence was completed the flow was stopped before starting the next sequence.

Column: 300 mm × 4.6 mm, 2.7-μm dp AdvanceBio SEC 300 Å; mobile phase: 150 mM

sodium phosphate, pH 7; flow rate: 0.35 mL/min.

Mo

no

mer

are

a %

Ag

gs

an

d d

imer

are

a %

100.0 30.0

25.0

20.0

15.0

10.0

5.0

0.0

95.0

90.0

85.0

80.0

75.0

70.0

65.0

60.0200 400 600 800 1000 12000

Injection number

Sample changed

Monomer% Aggs% Dimer%

Figure 11: Application of SEC to characterize a commercial mAb and its biosimilar:

intact and stressed conditions. SEC chromatograms of (a) intact ribuximab innovator (red

trace) overlaid with pH and heat-stressed sample (blue trace) and (b) intact rituximab

biosimilar (red trace) overlaid with stressed sample (blue trace). Chromatographic

conditions: Column: 300 mm × 7.8 mm, 2.7-μm dp AdvanceBio SEC 300 Å; mobile

phase: phosphate buffered saline (PBS), 50 mM sodium phosphate containing 150 mM

sodium chloride, pH: 7.4; temperature: ambient; injection volume: 10 μL; flow rate: 0.8 mL/

min; detection: UV absorbance at 220 and 280 nm.

Ab

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mA

U)

Ab

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mA

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(a)

(b)

160

140

120

100

80

60

40

20

04 6 8 10 12 14

160

140

120

100

80

60

40

20

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Monomer8.286

Aggregates

Fragments

10.293 14.494

14.494

14.494

11.985

8.401

8.292

Fragments

Monomer

5.668 6.945

11.990

12.760

Time (min)

42 6 8 10 12 14

Time (min)

adsorption with subsequent low

recovery, and nonreproducible

separations are signs of possible

nonspecific interactions. Repetitive

injections of a test protein sample

should be performed. Peak areas

should be reproducible with less than

a 1% relative standard deviation.

Column lifetime is another

parameter of great interest. Besides

the expense of replacing a dead

column, the time to re-equilibrate

and recalibrate the column and

running necessary blanks should

also be taken into account. Modern

SEC columns, if properly treated,

should provide at least 1000

injections. Lifetimes can be even

further extended by the use of

guard columns, which are a lot less

expensive to replace and, as long

as connections are minimized to

prevent band broadening, should

have no effect on the separation.

To test an SEC column, a series of

1200 injections of a mAb containing

dimers and higher order aggregates

(depicted as aggs in the figure)

was made over a period of 10 days.

Although not shown, the peaks were

well resolved and the resolution of

the monomer–dimer changed about

3% over the time period. Figure 10

shows that the quantitation for

monomer, dimer, and aggregates

was still reproducible after 1200

injections, and the quantitation is

consistent over the lifetime of the

column.

Application of Optimized SEC

Column to a Stressed Monoclonal

Antibody and Biosimilar — A

Typical Biopharma Application:

To test an SEC column on a real

sample, the innovator drug rituximab,

a medication to treat non-Hodgkin’s

lymphoma or chronic lymphocytic

leukemia and the first monoclonal

approved by the United States

Food and Drug Administration

(FDA) in 1997, and a biosimilar were

subjected to forced degradation

studies. The resulting breakdown

products were separated by SEC.

Samples of the mAbs were prepared

by first diluting them in mobile

phase and then a pH stress test was

performed by adding hydrochloric

acid to the sample solutions to adjust

the pH to 1.0, then adding sodium

hydroxide to adjust the pH to 10.0,

and finally getting the pH back to

6.0 by the addition of hydrochloric

acid (4). The resulting solution

was incubated at 60 °C for 60 min.

Figures 11(a) (innovator drug, red

trace) and 11(b) (biosimilar drug,

red trace) show the initial profile of

each drug determined by SEC and

both were found to give a single,

fairly symmetrical peak showing

no indication of aggregation or

degradation.

After the pH and heat-stressed

experiments were performed, the

SEC profiles were dramatically

changed. The innovator drug

(Figure 11[a], blue trace) showed

evidence of aggregate formation as

can be seen by the small higher-MW

aggregate peaks eluted before the

monomer. Additional lower-MW

degradation peaks were observed

after the elution of the monomer. For

the rituximab biosimilar (Figure 11[b],

blue trace) no evidence of

higher-order aggregates was found

but lower-MW fragments could

be observed in the SEC profile. In

both cases, a relative decrease in

the main mAb peak was observed,

indicating a molecular breakdown

caused by the stress experiments.

More information about these drugs

and quantitative results can be

found in reference 5. This series of

experiments shows that SEC can

be very helpful in the process of

mAb-based product development

especially for the quantitation of

dimer and higher-order aggregates.

Conclusion

As the shift in pharmaceutical

drug development towards

biological-based entities continues,

HPLC and UHPLC column technology

will have to shift with the market

demands. Columns that were suited

for small molecules will not necessarily

be useful for the larger biomolecules,

and older biocolumns that have

been used for years may not have

the proper characteristics to meet

the demands required for treatment

of newer biopharmaceuticals. In this

article, we have tried to show the

important characteristics that impact

the performance of an aqueous SEC

column, particularly one that is suited

for the separation and quantitation

of a monoclonal antibody and higher

aggregates such as dimers, trimers,

and other high-molecular-weight

species. Some of the characteristics

are familiar chromatographic

principles (such as column length,

particle size, and flow rate) but others

are unique to SEC (for example, pore

size, pore volume, and nonspecific

interactions). It is anticipated that

further developments in SEC columns

for biomolecules will come about in

future years with further research and

development for smaller particles and

tuned inert porous surfaces underway.

It should be noted that, because of the

fixed retention mechanism of SEC, a

single column and mobile phase can

be used for multiple types of samples

requiring a size separation including

fragment analysis, separation of

antibody-drug conjugates, PEGylated

proteins, and general protein and

peptide separations.

References(1) http://cbc.arizona.edu/njardarson/

group/top-pharmaceuticals-poster.

(2) World Preview Outlook to 2020,

EvaluatePharma (2014).

(3) L. Lloyd, LCGC Europe 27(s11), 25–29

(2014).

(4) B. Basak Kukrer, V. Filipe, E. van Duijn,

P.T. Klasper, R.J. Vreeken, A.J.R. Heck,

and W. Jiskoot, Pharm. Res. 27,

2197–2204 (2010).

(5) M.S. Palaniswamy, “Separate and

Quantify Rituximab Aggregates and

Fragments with High-Resolution SEC,”

Agilent Technologies, Application Note

5991-6304EN, October, 2015.

Disclaimer

For research use only. Not for

diagnostic purposes. This information

is subject to change without notice.

Ronald E. Majors is Column

Editor Emeritus for LCGC, and

an analytical consultant in West

Chester, Pennsylvania, USA. Linda

L. Lloyd is with Agilent Technologies

in Church Stretton, Shropshire,

UK. Direct correspondence to:

[email protected]

As the shift in

pharmaceutical drug

development towards

biological-based entities

continues, HPLC and

UHPLC column technology

will have to shift with the

market demands.


Majors and Lloyd


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Chromatographic techniques

(including liquid, gas, and thin-layer

chromatography), have been used

for decades in specialist clinical

laboratories for the separation and

(semi-) quantitation of established

biomarkers. High performance liquid

chromatography (HPLC) emerged as

the most useful technique in the clinical

field and has been commonplace

for biospecimen analysis since the

1970s (1). Over the last 20 years

there has been a shift towards mass

spectrometry (MS) detection rather

than conventional detection methods

(ultraviolet [UV], fluorescence,

and electrochemical) (2). This shift

was driven by the uptake of liquid

chromatography coupled to tandem

MS (LC–MS–MS) in newborn screening

and therapeutic drug monitoring

laboratories where the advantages

of reduced turnaround times and a

simplified workflow were paramount.

In recent years, LC–MS–MS has also

started to replace gas chromatography

(GC)–MS and immunoassay

methods for vitamins, hormones, and

metabolites. This trend is mainly due to

the superior selectivity and adequate

sensitivity of LC–MS–MS compared

to immunoassays (3) and the higher

throughput and capacity compared

to GC–MS. The result is that, today,

many specialist clinical laboratories

continue to use a dwindling number of

well-established GC, GC–MS,

HPLC–UV, HPLC–electrochemical

detection (ECD), and HPLC–

fluorescence detection (FD) methods

and an ever-increasing number of

LC–MS–MS methods.

Diagnostic clinical chemistry

departments, particularly those

within the public health system,

usually receive budgetary funding

on a reimbursement per result basis.

In these laboratories, the majority

of sample analysis is performed on

large, fully automated colorimetric,

nephelometric–turbidimetric, or ligand

binding assay instruments, which

are often acquired from vendors

via reagent rental or cost-per-assay

agreements. This means that the

vendor provides the instrument in

exchange for a guaranteed purchase

of reagents per year, or alternatively,

the clinical laboratory must pay the

vendor a specified amount per test

processed. These arrangements

work well because they are suitable

for the budget model and remove

the considerable capital outlay of

purchasing equipment. In addition,

because the average contract

expires after five years, laboratories

can keep up with technological

advances via the tendering process.

This remuneration scenario is not

the norm for chromatography and

MS equipment vendors supplying

instrumentation to specialist clinical

chemistry laboratories. As a result,

obtaining the capital funds to

purchase LC–MS–MS instrumentation

often requires detailed business cases

demonstrating cost-effectiveness to

accompany the predicted clinical

benefit of using this technology.

Despite a history spanning more

than 40 years, chromatographic

challenges are commonplace in

clinical diagnostic analysis, even

with the improved selectivity offered

by MS detection. Interferences that

prevent result reporting can arise

from specific patient groups because

of age, sex, diet, disease states,

and drug regimens. The complexity

of samples from various patient

populations can necessitate more

than one chromatographic method

for the analysis of a target biomarker

to enable measurement across all

patient subgroups and allow for

confirmatory testing when unusual

interferents are present. This need

places a great deal of emphasis on

stationary-phase options that

explore different retention

mechanisms, and emerging phases

on the market are met with great

enthusiasm.

Rapid and Robust Analysis

without the Back Pressure

Many HPLC services provided in

specialist centres employ established

assays using older instrumentation

with back-pressure limits of 5000 psi

or less. In the past, the relatively

long chromatographic run times

were not of concern because sample

numbers were low. However, the

ever-increasing workload (typically

≥10% expansion year on year)

has meant that chromatographic

run time has become a limiting

factor. Unfortunately, the costs

Positive Impacts of HPLC Innovations on Clinical Diagnostic Analysis

Michael J.P. Wright and Sophie Hepburn, Department of Clinical Chemistry and Endocrinology, Prince of

Wales Hospital, Sydney, Australia.

The last decade has seen a series of advances in the field of liquid chromatography that have resulted

in improvements for many clinical diagnostic services. These innovations have included the expansion

of superficially porous particle columns, new or improved stationary phase options, and user-friendly

multiple-channel high performance liquid chromatography (HPLC) instrument options that allow sequential

analysis — a boon for low- and moderate-throughput laboratories with limited hardware. As a result,

diagnostic services are able to offer faster turnaround times and measure analytes in patient types and

disease states that were previously problematic. This article presents examples of the impact these

innovations have had in a number of hospital settings.


of replacing instrumentation

with ultrahigh-pressure liquid

chromatography (UHPLC) equipment

capable of recognizing the gains

of sub-2-μm dp columns can be

prohibitive.

An important development

in column technology was the

emergence of >2-μm superficially

porous silica particles (SPPs) that

can provide increased efficiency

without the same back-pressure

gains as those seen with sub-2-μm

fully porous particle columns. For

established clinical HPLC assays,

for example, serum vitamins A

and E (HPLC–UV) and urine

catecholamines, metanephrines, and

5-hydroxyindoleacetic acid (HPLC–

ECD), the introduction of higher

efficiency SPPs enabled the use of

shorter columns to produce very

similar chromatographic separation

with greatly reduced run times and

minimal changes in back pressure

(Figure 1). In many cases, this

increased the capacity of existing

HPLC instrumentation 3–4-fold.

Interestingly, the main limitation in

accelerating the chromatography

further is no longer the back pressure,

but rather a combination of other

factors including autosampler

operating speed, detector cell volume,

and the data collection rate limit of the

detector.

Accelerated chromatography can

certainly aid in improving patient

sample turn-around times; however,

ideally it should not come at the

expense of robustness of the method.

System blockages cause delays

in patient result reporting while the

instrument undergoes troubleshooting

and repairs. One trade-off seen with

UHPLC systems fitted with sub-2-μm

dp columns, when compared to a

HPLC system fitted with a larger dp

column, is the requirement for cleaner,

particulate-free mobile phases and

more exhaustive sample preparations

before injection to prevent blockages.

In a high-throughput clinical laboratory

these extra sample preparation

requirements can be an additional

burden on staffing and workflow. SPP

columns with >2-μm particles provide

an intermediate solution.

To assess robustness we performed

the following experiment: 100 μL

of serum samples were protein

precipitated by the addition of 25 μL

of 0.2 mol/L zinc sulphate followed

by 200 μL of methanol. The resulting

solution was passed through a

0.45-μm 96-well Multiscreen Solvinert

filter plate (Millipore) before being

loaded onto a Nexera series UHPLC


Wright and Hepburn

2.5Time (min)

4.0

Resp

on

se (

nA

)R

esp

on

se (

nA

)

10Time (min)

2.5

0

0

3.23

3.87 5.60

9.01

0.93

1.071.48

2.28

(b)

(a)1

2 3

4

1

2 3

4

BP = 1810 psi

BP = 1880 psi

Figure 1: Accelerated chromatography with superficially porous particles provides

faster patient sample turn-around times without requiring UHPLC instrumentation: (a)

Urine catecholamine screen performed by HPLC–ECD with a 20-μL injection onto a

150 mm × 4.6 mm, 5-μm dp fully porous particle C18 column at a flow rate of 1.2 mL/

min; (b) 5 μL of the same sample injected onto a 50 mm × 4.6 mm, 2.7-μm dp SPP C18

column at a flow rate of 1.5 mL/min. Peaks: 1 = noradrenaline, 2 = adrenaline,

3 = DHBA (internal standard), 4 = dopamine.

50 mm x 2.1 mm, 1.6-μm dp SPP C18

Back

pre

ssu

re (

psi

)

8000

N = 1700

Injection count

N = 2257

N = 1720

7000

6000

5000

4000

3000

2000

1000

00 201 401 601 801 1001 1201 1401 1601 1801 2001 2201 2401 2601 2801 3001

50 mm x 2.1 mm, 1.8-μm dp C18

50 mm x 2.1 mm, 2.7-μm dp SPP C18

Back pressure limit of HPLC instruments in the laboratory

Figure 2: Back-pressure and robustness advantages of 2.7-μm particle columns

versus sub-2-μm columns. Protein precipitated serum samples were injected onto three

columns fitted into a column oven. After each batch of 200 sample injections the column

was switched to the next in line and the same samples were re-injected. The back

pressure was recorded at the beginning of each batch. The red dotted line indicates the

back-pressure limit of the standard HPLC systems in the laboratory.

system (Shimadzu) coupled to an

API 6500QTRAP mass spectrometer

(Sciex). The three columns under

evaluation were fitted into the column

oven using multiport selection valves.

Next, 20 μL of each prepared sample

was injected onto the column and

after each batch of 200 sample

injections the column was switched

to the next in line and the process

was repeated. Mobile-phase A was

0.1% formic acid in water and B was

0.1% formic acid in methanol. A rapid

gradient of 50–100% B was performed

over 1 min at 0.4 mL/min, followed by

100% B at 1 mL/min for 1 min, and

then 50% B at 1 mL/min for 0.5 min.

The back pressure was recorded

at the beginning of each batch and

column efficiency was determined

by an injection of a system suitability

test solution containing testosterone.

As expected, the sub-2-μm dp

columns initially generated a higher

back pressure than the 2.7 μm dp

column; however, the efficiency (N)

was dependent on column type

rather than purely the particle size

(Figure 2). Back pressure increased

for all columns as the injection number

increased, but this elevation was more

marked in those with sub-2-μm dp

particles. Unlike the UHPLC system

used in this study, a number of the

HPLC systems in the laboratory have

a back-pressure limit of 5000 psi,

so for this example only the 2.7-μm

dp column would be suitable for all

instruments over a large number of

injections.

Innovations in Stationary

Phases

The move towards LC–MS–MS

analysis in clinical chemistry has

provided many benefits; however,

challenges involving chromatographic

separation of similar compounds

remain. With the number of solvents

and additives now limited to those that

are considered “MS friendly” (that is,

volatile, proton donating, or accepting,

do not form unwanted adducts), the

selection of stationary phase has

taken on increased importance (4).

Chromatography is required not only

for the removal of interferents causing

ion suppression, particularly salts and

phospholipids present in blood and

urine, but also for the separation of

isobaric compounds that share the

mass transitions used for quantitation.

Alkyl-bonded stationary phases have

been the traditional mainstay of clinical

HPLC separations with mobile-phase

buffers and ion-pair reagents providing

the additional selectivity required.

As assays move to LC–MS–MS, the

emphasis has turned to emerging

stationary phases that use alternative

mechanisms of retention to separate

the analyte–interference critical pairs.

Serum 25OH vitamin D3

measurement has seen substantial

growth in clinical chemistry

laboratories over the past 10 years;


Wright and Hepburn

6.0Time (min)

Inte

nsi

ty (

cps)

Time (min)

1.9e5

Inte

nsi

ty (

cps)

2.52

(b)

5.3e4

(a)

25OHD3 3epi -25OHD3

3epi -25OHD3

4.594.84

25OHD3 and

4.0

HO

OH

HO

OH

Figure 3: Serum 25OH vitamin D3 analysis in adults and infants: (a) A rapid on-line

solid-phase extraction (SPE) method for 25OH vitamin D3 measurement in serum

from adult patients. Serum is protein precipitated and filtered before injection onto

a 20 mm × 2 mm, 20-μm dp C8 extraction cartridge followed by elution (reverse

elution time point indicated by the dotted line) onto a 50 mm × 2.1 mm, 2.7-μm dp

C8 column. This phase does not separate the 3-epi-25OH vitamin D3 form sometimes

found in infants. (b) The same on-line SPE method as above but eluted onto a 100

mm × 2.1 mm, 2.7-μm dp pentafluorophenyl phase column resolves the 3-epimers.

1.65

1.37

Time (min)

Inte

nsi

ty (

cps)

3.0

1.37

1.01 3.71

3.58

3.71

4.41

2.75

2.352.26

Time (min)

Inte

nsi

ty (

cps)

6.0

(b)(a)

1

2

3

4

5 6 7

8

9

10 11

Figure 4: Separation of target analytes from isobaric interferences for clinical

diagnostic LC–MS analysis using embedded polar group and biphenyl phases:

(a) MRM transitions of hydrophilic Kreb cycle metabolites on a 100 mm × 2.1 mm,

2.7-μm dp reversed-phase amide column with isocratic 100% aqueous mobile phase

containing 0.4% formic acid; (b) separation of glucocorticoids and sex steroids on a

50 mm × 2.1 mm, 1.7-μm dp biphenyl column with mobile-phase A consisting of 0.1%

formic acid in water and B consisting of 0.1% formic acid in methanol; a 40–100%

B gradient over 4.5 min was used. Peaks: 1 = isocitrate, 2 = citrate, 3 = succinate,

4 = methylmalonic acid, 5 = predniolone, 6 = cortisol, 7 = cortisone, 8 = epi-

testosterone, 9 = testosterone, 10 = 17OH-hydroxyprogesterone,

11 = 11-deoxycorticosterone. Note: The MRM transition for peaks 5

and 7 in (b) is detecting the naturally occurring M+2 isotope.

with test requests having increased

approximately twofold per year, every

year. One of the challenges presented

by the measurement of this biomarker

with LC–MS–MS is separating the

C3-epimeric forms often found in

samples from infants. The 3-epi-25OH

form of vitamin D3 is thought to be an

inactive or possibly a suppressing

form of 25OH vitamin D3 with the

general consensus that it should be

separated for measurement of 25OH

vitamin D3 in infant patient samples

(5). Because the C3-epimeric forms

share the same precursor–product

ion mass spectra they need to be

separated before arrival at the mass

spectrometer ion source. Many

LC–MS–MS methods in the literature

were designed for older patients and

used C8 or C18 stationary phases

that were unable to resolve this critical

pair. In the past, chromatography

using cyano stationary phases were

utilized but limited selectivity of

the phase resulted in run times of

18–45 min, which were too long to

be feasible for the volume of test

requests (6). The development of

pentafluorophenyl (PFP) phases has

shown improved selectivity for 25OH

vitamin D3 and 3-epi-25OH vitamin

D3, enabling quantitation of the target

analyte in this patient group (Figure 3),

either as a secondary method for

infant samples or, if time permits, as a

front-line analysis for all samples (7).

Issues with isobaric

interferences in clinical LC–MS–

MS can be exacerbated when the

compounds are extremely polar

and difficult to separate by most

hydrophilic-interaction chromatography

(HILIC) phases. The measurement

of Kreb cycle compounds

demonstrates this scenario where

the critical pairs of isocitrate–citrate

and succinate–methylmalonic acid

need to be resolved. The evolution

and diversification of phases that

incorporate an embedded polar

group (EPG) with an alkyl ligand has

produced stationary phases with

a wide range of chromatographic

properties that are capable of

operating at 100% aqueous mobile

phases (8). In this example, an

EPG stationary phase, operated

under aqueous conditions, enabled

resolution of these critical pairs

(Figure 4[a]).

For the measurement

of serum steroids such as

cortisol, testosterone, or

17-hydroxyprogesterone, the target

analyte is part of a large group

of closely related endogenous

compounds that share a fused

ring system of three cyclohexanes

and one cyclopentane and

where isobaric interferences are

common. To further complicate

matters, because of their structural

similarity, steroids often have similar

fragmentation patterns and can also

be present at supraphysiological

concentrations, for example, when

used for treatment. Thus, even

for compounds that have slightly

different precursor mass-to-charge

ratios (m/z), the possibility of

interference from naturally occurring

isotopes of steroids with smaller

m/z values have to be taken into

consideration. This is particularly

true when developing LC–MS–MS

methods for the analysis of samples

from certain patient groups, such as

those with steroidogenesis defects.

The emergence of biphenyl phases

introduces separation mechanisms

such as shape selectivity and π-π

interactions while providing a greater

amount of hydrophobic retention than

seen with traditional phenyl phases.

The use of a biphenyl phase enables

the separation of common isobaric

steroid interferences, such as those

outlined in Figure 4(b).

Leveraging the Most Out of

Instrumentation

For small to moderate-sized specialist

clinical laboratories (500–5000

patient samples/week) the LC–MS–

MS workflow consists of numerous

applications where small batches of

patient samples are run on a regular

basis (daily or weekly). Often these

applications rely on different mobile

and stationary phases to achieve the

chromatographic selectivity required.

To leverage the capacity of the

LC–MS–MS instruments to achieve

favourable cost-effectiveness, the

systems should run continuously with

an automated process for changing

from one method to another without

intervention by staff.

HPLC systems that incorporate

selection-valve configurations

allowing multiple mobile phase

and column combinations to be

run simultaneously have existed for

some time in research and assay

development laboratories. However,

because of reliability issues,

complicated software, concerns

regarding service-support, and a

lack of experienced operators in

the laboratories themselves, these

instruments were not regularly

promoted to clinical diagnostic

laboratories. This situation has

changed in recent years with a

number of LC–MS–MS vendors

providing simpler instrument set-ups

with numerous on-board mobile

phases and columns easily controlled

via instrument software.


Wright and Hepburn

(b)

(a)

Mass

spectrometer

Mass

spectrometer

Columnoven

Autosampler

Solventselection valve

On-line SPE cartridge Two-position divert valve

Six-position selection valve

Analytical column

Autosampler

Pumps 2Waste

Pumps 1

Pumps 1

Columnoven

Figure 5: LC–MS systems designed for automated sequential method transfer:

(a) System containing solvent selector valves, allowing multiple solvents to the pumps,

and six-position high-pressure selection valves allowing multiple column selection;

(b) system with a second binary pump, two-position high-pressure divert valves, and

another six-position high-pressure selection valve, enabling on-line-SPE to be added to

the automated sequential method transfer system.

Figure 5(a) illustrates a system where

binary pumps have solvent-selection

valves attached allowing multiple

mobile phases (typically, four or six)

to each pump. In our laboratory, one

of the lines running to each pump

is reserved for a “cleaning solvent”

of 50% methanol. The column oven

houses two seven-port, six-position

selection valves allowing availability

of up to six columns without system

reconfiguration. In this setup, one

column option is sacrificed for a direct

line for use during conditioning steps.

For sequential analysis of multiple

assays, all sample preparation is

completed during normal working

hours and the prepared samples

are loaded into the autosampler by

the end of the day. The batches of

samples are submitted together with

conditioning batches introduced

between different assays to run

overnight as follows:

t� The first batch is run using Method

1: column 1 and mobile-phase A1

and B1.

t� A “conditioning batch” is run using

blank samples injected utilizing

General Conditioning Method*:

direct line (no column) and

mobile-phase A4 and B4 (cleaning

solvent) — this step purges

the system with 50% methanol,

removing the mobile phases from

Method 1 and thus preventing the

possibility of incompatible mobile

phases mixing from two different

methods.

t� A second conditioning batch is run

with blank samples injected utilizing

Method 2 Conditioning Method*:


mobile-phase A2 and B2 (Method

2 mobile phases) — This primes

the system with the correct mobile

phases for Method 2 in preparation

for the next column to be switched

on-line.

t� The second batch is run using

Method 2: column 2 and

mobile-phase A2 and B2.

t� The “conditioning batch” is run

again with blank samples injected

using General Conditioning

Method*: direct line (no column)

and mobile-phase A4 and B4

(cleaning solvent).

t� A third conditioning batch is run

with blank samples injected using

Method 3 Conditioning Method*:


mobile-phase A3 and B3 . . . and so

on, with up to five different clinical

assay methods running without user

intervention.

t� *The liquid flow during the various

conditioning batches is diverted to

waste immediately before the mass

spectrometer to prevent fouling of

the ion source.

On-line solid-phase extraction (SPE)

is a popular technique in clinical

diagnostic laboratories because of the

labour and cost savings it represents

compared to off-line SPE. Adding

multiple on-line SPE stations to a

system (Figure 5[b]) can be achieved

by the introduction of a second set of

pumps, fitted with solvent selection

valves, and a high-pressure selection

valve to direct the flow from these

pumps to the switching valve fitted

with the on-line SPE cartridge. Again,

one mobile-phase channel for each

pump is reserved for a “cleaning

solvent” of 50% methanol and one

option from the selection valve is sent

to waste for use during conditioning

steps. As with the example described

previously, general conditioning

and method-specific conditioning

batches are submitted between

batches to prepare the system with

the correct mobile phases, column

oven temperatures, and mass

spectrometer ion source conditions for

the subsequent sample batch.

A clear advantage in running assays

sequentially on a single system (or

even parallelism in larger laboratories)

is that of operation time (uptime)

allowing laboratories to provide a

24-h service to users. Priority is

obviously given to urgent tests, which

can be run during the daytime with

rapid reporting of results. However,

routine batch tests can run throughout

the night to minimize sample

congestion during working hours

where instruments would be better

used for assay development and

improvement processes. It also allows

LC–MS–MS methods to compete with

routine immunoassay analyzers that

are common to core testing facilities

that often perform 50+ reactions

concurrently.

Conclusion

HPLC continues to have widespread

applications in clinical laboratories,

and, when coupled to MS, it is the

preferred method for the measurement

of many low-concentration

endogenous biomarkers. The advent

of SPP introduced higher efficiencies

on existing HPLC equipment, enabling

the faster run-times required to match

the growing sample numbers without

the need to purchase expensive

UHPLC equipment. In addition,

the introduction and expansion

of a greater variety of stationary

phases to the market has helped to

solve many of the chromatographic

challenges facing clinical laboratories

moving to LC–MS–MS technology.

Throughput limitations for LC–MS–

MS platforms have been resolved

by multiple-channel systems that

enable programming of sequential

analyses over a 24-h period. Adding

on-line SPE to these platforms

further streamlines the workflow and

introduces cost-savings in a busy

clinical setting. These innovations

allow several assays to run back to

back with a variety of stationary and

mobile phases without the need for

expensive, and often unfavourable,

night-shift schedules for highly skilled

staff while also delivering value for

money from expensive LC–MS–MS

platforms.

References(1) C.A. Burtis, J. Chromatogr. 52, 97–106

(1970).

(2) S.K.G. Grebe and R.J. Singh, Clin.

Biochem. Rev. 32, 5–31 (2011).

(3) V.M. Carvalho, J. Chromatogr. B

883–884, 50–58 (2012).

(4) S.R. Needham, P.R. Brown, K. Duff, and

D. Bell, J. Chromatogr. A 869, 159–170

(2000).

(5) A. De La Hunty, A.M. Wallace,

S. Gibson, H. Viljakainen,

C. Lamberg-Allardt, and M. Ashwell, Br.

J. Nutr. 104(4), 612–619 (2010).

(6) K.W. Phinney, M. Bedner, S.S. Tai,

V.V. Vamathevan, L.C. Sander, K.E.

Sharpless, S.A. Wise, J.H. Yen, R.L.

Schleicher, M. Chaudhary-Webb, C.M.

Pfeiffer, J.M. Betz, P.M. Coates, and M.F.

Picciano, Anal. Chem. 84(2), 956–962

(2012).

(7) C.R. Aurand, D.S. Bell, and M. Wright,

Bioanalysis 4(22), 2681–2691 (2012).

(8) M.R. Euerby and P. Petersson, J.

Chromatogr. A 1088, 1–15 (2005).

Michael J.P. Wright and Sophie

Hepburn are with the SEALS

Department of Clinical Chemistry and

Endocrinology at the Prince of Wales

Hospital in Sydney, Australia. Direct

correspondence to: mike.wright333@

gmail.com or shepburn_au@yahoo.

com


Wright and Hepburn

While in earlier years environmental

applications concentrated mainly

on agrochemicals in use, it is now a

much broader field covering not just

preferential enantioselective activity,

but also the influence of microbial

population on selective degradation.

The impact of excess and metabolized

pharmaceuticals is also widely studied

along with persistent organic pollutants

(POPs), that includes a range of both

pesticides and fluorinated organics.

There is increasing alarm about

these POPs potentially not being

fully extracted in waste-treatment

plants, affecting both human and fish

populations. Monitoring for banned

pesticides is also a key activity.

Recent developments in chiral

stationary-phase (CSP) technology

have principally concerned major

advances in smaller particle technology

to support these needs. The result is

vastly improved chiral column efficiency

and selectivity enabling many new

applications along with the potential for

more comprehensive multicomponent

screening. A significant number of

applications have used 3-μm particle

size versions of both the immobilized

and coated polysaccharide CSPs to

enable much faster separations. There

has been much interest in the utilization

of sub-2-μm ultrahigh-pressure liquid

chromatography (UHPLC) particles for

chiral separations, mostly on brush type

and cellulosic CSPs. A recent paper by

Gasparrini (1) demonstrated the benefits

of both UHPLC and supercritical fluid

chromatography (SFC) and the high

efficiencies obtained by bonding onto

Whelk-O-1 both 1.7-μm porous silica and

superficially porous particle (SPP, core–

shell) silica. The next phase of new CSP

development for this year, however, is

very likely to use the recent introduction

of a 1.9-μm monodisperse totally porous

particle (TPP) (2) that appears to provide

new opportunities to increase CSP

efficiencies even further. These particles,

when bonded with C18, exhibited an

extremely low reduced plate height,

h, of 1.7 in narrow-bore (2.1 mm i.d.)

columns, extremely low when compared

to classical porous particles. Gasparrini

(3) demonstrated extremely high

efficiencies obtained by bonding

teicoplanin to TPPs and performed

extensive fundamental studies of the

CSP, reporting efficiencies of 200,000–

250,000 plates/m at the optimum

flow rate. Additionally, Armstrong and

coworkers (4,5) reported ultrafast

separations by bonding cyclofructan,

cyclodextrin, and all the macrocyclic

chiral selectors to TPPs. Separations

in seconds were demonstrated that

could, for instance, provide on-line chiral

monitoring of asymmetric synthesis. The

very significant increase in efficiency

should enable the separation of far more

complex mixes in addition to being

used for two dimensional (2D)-UHPLC

for the separation of multichiral centre

pesticides in the near future (4).

Environmental Applications

The fast growth in agrochemicals

has fueled much research into their

environmental impact. It is estimated

that 28% of agrochemicals are currently

chiral (6), a growth in part because of

advances in asymmetric synthesis and

process scale simulated moving bed

chromatography that has significantly

reduced the commercial cost for

multitonnage agricultural requirements.

Despite this, some 24% of these are

applied as a racemate (7), resulting in

the potential release of inactive products

into the environment. Of the $223 billion

global pesticide industry, more than

40% of the products are used in China

and the largest proportion of papers

published in the last two years reflects

this, especially where related to their

impact on the important tea production

industry.

The fate of pesticides in the

environment is expected to be subject

to enantioselective biodegradation

by microorganisms, possibly in

quite a different way compared to

microorganisms present in water

because of residue matrix binding

effects. The differing enantiomeric

activities of chiral pesticides, the effect of

various microorganisms giving differing

modes of degradation, and the resulting

unbalancing of the microbiological

makeup of the environment are all of

great interest. Pharmacologically active

compounds — drugs, their metabolites,

and illicit drugs — are routinely tested in

wastewater, but could also be present

in solid waste and sludge providing an

additional source of bioavailable uptake.

Overall, there are many reasons for

increased environmental testing.

Chiral Method Development for

Environmental Applications

While chiral separations in environmental

applications have generally not kept

pace with those for pharmaceutical

products, the number of publications

has grown considerably in recent

years due, in part, to these increasing

environmental concerns. CSPs used

for environmental separations need

to be capable of separating relatively

polar molecules. Fortunately, high


(HPLC), gas chromatography (GC), and

SFC have all proven to be useful. SFC

was used for the enantiomeric analysis

of the triazole fungicide flutriafol in

vegetables, fruits, and soils in 3.5 min

Latest Advances in Environmental

Chiral ApplicationsDenise Wallworth, Sigma-Aldrich UK, a subsidiary of Merck, Poole, Dorset, UK.

This article provides a brief overview of some of the chiral environmental studies carried out recently

that cover the differing enantiomeric activity of pesticides, their environmental transformation, and

the degradation of pollutants in general. It highlights some of the recent advances in chiral stationary

phases that have enabled higher efficiency and faster separations than previously seen in this area.


using a 3-μm bonded amylose tris(3,5-

dimethylphenylcarbamate) CSP in

carbon dioxide–methanol. Formic acid

in methanol was added post column

to enhance mass spectrometry (MS)

ionization. Using QuEChERS (quick,

easy, cheap, effective, rugged, and safe)

for sample preparation, this method

provided a limit of quantitation (LOQ)

down to 0.41 μg/kg, making it useful for

both environmental and food analysis

(8). This separation has also been

performed by LC–MS using a cellulosic

tris(3-chloro-4-methyl phenyl carbamate)

phase in 40:60 (v/v) acetonitrile–water

giving a limit of detection (LOD) of 15 μg/

kg (9). This was found to be a much faster

method than using a cellulosic phase

under normal-phase conditions. Elution

order and configuration were assigned

using electronic circular dichroism

(ECD) and found to be (R)-(-) for the

first eluting enantiomer and (S)-(+) for

the second. Linearity and precision was

checked in seven different matrices,

in preparation for future environmental

and food studies. Chiral GC was used

for a haloxyfop study (10,11), separating

these herbicides as their methyl esters

using a custom-made OV170 GC column

coated with 15% w/w permethylated

beta cyclodextrin (0.1-μm film thickness).

The levels of organochlorine pesticides

in air and surface water in the Indian

Ocean were measured using chiral

GC–MS (12) employing EI detection

in multiple reaction monitoring (MRM)

mode and a 20% tert-butyldimethylsilyl-

beta-cyclodextrin CSP dissolved in

15% phenyl-, 85% methylpolysiloxane.

Significant decreases in α-HCH and

γ-HCH but increases in p,p′-DDT,

o,p′-DDT and cis- and trans-chlordane

were observed. An example separation of

chlordane and HCH is shown in Figure 1.

For the monitoring of active

pharmaceuticals in wastewater, a method

for the simultaneous enantioselective

determination of ibuprofen, naproxen,

and ketoprofen was developed using

LC–MS–MS. The method used a

single-step sample treatment based on

microextraction with a supramolecular

solvent that provided low method

detection limits of 0.5–1.2 ng/L. This

was optimized and the analytical

method validated on a vancomycin

bonded 5-μm CSP (13). The method

was reported as suitable for using

the enantiomeric fraction of ibuprofen

as an indicator of the discharge of

untreated or poorly treated wastewaters.

In contrast, a (nonchromatographic) 14C isotope tracing MS–MS method

was used to investigate the fate of the

four isomers of IPP, a novel, broad

spectrum neonicotinoid insecticide (7).

Stereoselective soil binding and the

microbial influence on epimer-selective

degradation were reported.

Enantioselective Activity

As is well known for chiral

pharmaceutical products in biological

systems, if a pesticide is a chiral

molecule, it is common that one

enantiomer carries greater activity

than its pair. A great example is

deltamethrin, where only one of the

eight enantiomers (αS,1R,3R′-) has the

desired insecticidal activity, the other

seven being nonactive or less active.

Only one of the enantiomers of the

herbicides dichlorprop and mecoprop

is responsible for their activity — the

(S)-isomer is completely inactive in

each case. Another in this class is

haloxyfop-methyl, a chiral herbicide

that was first introduced as racemate

but later replaced by its R-enantiomer,

responsible for the herbicidal action (10).

The first study of the enantioselective

biodegradation and activity of

difenoconazole was carried out using

a coated 5-μm tris(4-methylbenzoate)

cellulosic CSP. It was used to conclude

that the (2R,4S)- enantiomer would

be the better choice rather than the

stereoisomers to maximize bioactivity

and reduce environmental damage

(14). Although there have been health

concerns for acute exposure to acephate

related to its more toxic metabolite,

methamidophos (which was banned

in the European Union [EU] in 2015,

although at the time of writing this article

it was still in use in the US), the effect

of chirality had not previously been

studied. Recently, it was found that

enantioselective enrichment depended

on soil type and was shown to be

microbially activated (15). GC–MS–MS

was used, employing a heptakis(2,3-di-

O-methyl-6-O-tert-butyldimethylsilyl)-

β-cyclodextrin chiral GC capillary

column. Sample preparation used a

modified QuEChERS method, followed

by drying with anhydrous magnesium

sulphate to protect the chiral GC column.

Relative enantioselective bioactivity

of the enantiomers of acephate and

methamphos is in this case, however,

not so clear as it appears to depend on

the species it is applied to. This study

investigated the different enantioselective

degradation rates under various soil


Wallworth

0 2 4 6 8 10 12 14

Cl Cl

Cl

Cl

Cl

Cl

ClCl

Cl

ClCl

Cl

Mirror

α-HCH (peaks 1 and 2)

CCl2

Cl Cl

Cl

Cl

Cl

Cl

cis-Chlordane (peaks 3 and 4)

Time (min)

Figure 1: An example of chiral GC separations of organochlorine pesticides: chlordane

and α-HCH on Chiraldex G-BP, 10 m × 0.25 mm, at 170 °C with helium as carrier gas.

(Taken from G005050, SiAL source.)

conditions as a possible cause and

concluded that differing microbial

populations could play a significant role.

Enantiomeric Degradation

Environmental biodegradation of chiral

pesticides and herbicides is frequently

enantioselective. As in any guest-host

interaction in biological systems, the

interaction of such molecules with

microorganisms in the environment

is chiral and can result in differing

metabolism (microbial transformation),

causing possible selective accumulation

of one isomer over the other. Many

recent studies provide evidence of

such microbial transformation by

comparing transformation profiles in

sterile and nonsterile soils. In the case of

haloxyfop and haloxyfop methyl, a study

was carried out using chiral GC–MS

employing a custom made permethylated

beta cyclodextrin phase (OV 1701 with

15% (w/w) permethyl-β-cyclodextrin

and a film thickness of 0.1 μm) (10).

Haloxyfop was derivatized as the ethyl

ester to enable simultaneous separation

of haloxyfop and haloxyfop methyl, and

the derivatization procedure was shown

to be nonenantioselective. It was shown

that rapid degradation by cleavage

of the ester group occurred in three

different types of soils studied, but was

not observed in sterile soils, possibly

explained by the presence of microbial

carboxy esterases. Further, chiral

inversion occurred, with rapid conversion

of the S-enantiomer to the R-enantiomer

in nonsterile soils (Figure 2), reaching

a steady state when the R-enantiomer

level was about 10 times that of the

S-enantiomer. Interestingly, faster

inversion was observed for the acid when

originally applied as haloxyfop methyl.

Individual enantiomers were

isolated for the study using a cellulose

tricinnamate CSP in 95:5:0.1 heptane–

isopropanol–acetic acid, purifiying 2 mg

from a total of 10 injections (20 min per

injection) and confirmed with >99%

enantiomeric purity by chiral GC–MS

as the methyl ester. Analytically, 85:5:10

heptane–isopropanol–methanol

provided a separation in under 10 min

with the same column. If the herbicide

is applied to the soil for root update,

then this rapid interconversion to

the active R-enantiomer results in

independence of herbicidal activity from

the enantiomeric composition applied.

Any difference because of the mode

of application to the growing plant was

also studied, using the same GC–MS

method, and found that, when applied

to the leaves, no interconversion takes

place such that the effect of applying

individual enantiomers directly to the

plant will be very different and only the

R-enantiomer of haloxyfop effective (11).

A newly developed antiviral agent,

dufulin, used widely in China to

prevent disease in rice, tobacco, and

vegetables, was found to degrade

6–8 times faster in nonsterile soils

(16,17), providing confirmation of its

degradation by soil microbial action

but in this case without any chiral

inversion. After extraction of the soil

samples with acetonitrile, the chiral

separation was carried out in normal

phase on immobilized amylosic

tris(3,5-dimethylphenylcarbamate).

ECD was used to determine the

absolute configurations of the two

dufulin enantiomers, confirmed as the

S-(+)-enantiomer for the first eluting

enantiomer, and R-(−)-enantiomer as

the second one.

It is also now established that there

is enantioselective toxicity from many

pharmaceutically active compounds

and illicit drugs to freshwater species,

especially through adsorption on

sediments and suspended solids.

For example, S-(+)-fluoxetine and

S-(-)-atenolol significantly inhibit the

growth of a freshwater protozoan,

Tetrahymena thermophilia, compared to

the opposite enantiomer (18). This study

aimed to develop a comprehensive

screening protocol for multiresidue

identification. After microwave assisted

extraction and solid-phase extraction

(SPE), separations were performed

on a 5-μm cellobiohydrolase CSP

in reversed-phase mode for the

amphetamines and, for all other

analytes, on a vancomycin bonded

5-μm silica CSP (in the polar ionic

mode, using methanol, 4 mM

ammonium acetate and 0.005% formic

acid) (see, for example, Figure 3).

This method was used to investigate

stereoselective effects in sludge

treatment processes. In another

study, microbial degradation of the

chiral fungicide, benalaxyl (BX), was

investigated in water, sediment, and

water–sediment environments (19).

A separation of the enantiomers of

both the parent compound and its

acid metabolite was achieved using

a tris(3,5-dimethylphenylcarbamate)

coated cellulosic CSP in a mobile


Wallworth

0

20

40

60

80

100

120

0 1 2 3 4

Re

lati

ve

co

nce

ntr

ati

on

(%

)

Incubation time (d)

Sum of enantiomers

R-Ha-acid

S-Ha-acid

Figure 2: Microbial chiral inversion of S-haloxyfop through incubation of rac-haloxyfop

acid in soil. (Reproduced with permission reference 10.)

phase of n-hexane and 2-propanol

(91:9, v/v). Elution order, determined

using a polarimetric detector at

426 nm, was (-)-BX, (+)-BX, (-)-BX

acid, and (+)-BX acid. Sediment

microbial populations were found to

be responsible for enrichment of the

more toxic (+)-enantiomer, causing

higher risk in aquatic environments.

Additionally, the (-)-enantiomer was

preferentially degraded, enriching the

presence of the persistent (up to 70

days) benalaxyl acid, of concern to the

aquatic environment.

Enantioselective Transformation

A study of indoxacarb on

immobilized amylosic tris(3,5-

dimethylphenylcarbamate) in normal

phase reported no interconversion but

degradation of each isomer depended

on soil pH and its microbial activity

(20). Many studies have been carried

out over the years on polychlorinated

biphenyls (PCBs) and a recent study

looked at the transfer of PCBs 95,

132, 135, and 149 into chickens

via soil and chicken feed (21). The

results indicated enantioselective

metabolism, but nonselective maternal

transfer to chicks and it was found that

enantiomeric enrichment of PCBs 95,

132, and 149 and interconversion of

PCB 135 later occurred in the chick

resulting in different toxicity compared

to the adult.

Interestingly, the unexpected

appearance of the banned antibiotic

chloramphenicol in animal feed has,

for the first time, been traced back to

its production naturally by bacterial

activity in soils. Uptake into animal

feed crops was studied by chiral

LC–MS using an α1-acid glycoprotein

CSP and found to be related to its

bioavailability (22).

Summary

Stereoselective investigations need

to continue to play a significant role

in the study of the environmental

impact of agrochemicals, POPs, and

pharmaceutical products. Apart from

their impact on living organisms, a

critical outcome of their presence is

the disruption of the natural microbial

status resulting from stereospecific

transformation of these molecules,

as well as the potential for their

enantioselective persistence in

the environment. The majority of

applications reported used either

polysaccharide CSPs or derivatized

cyclodextrin-based capillary GC

columns. Although there have not

been any new developments for the

latter, or for protein-based CSPs, these

phases retain their usefulness in this

area. The advent of smaller particle

CSPs for the polysaccharide CSPs has

increased both speed and selectivity,

enabling more complex and difficult

separations to be developed, while the

future of ultraefficient TPP-based CSPs

bonded with a wide range of chiral

selectors is set to transform chiral

HPLC separations yet again.

References

(1) A. Cavazzini, N. Marchetti, R. Guzzinati

M. Pierini, A. Ciogli, D. Kotoni, I.

D’Acquarica, C. Villani, and F. Gasparrini,

TrAC, Trends Anal. Chem. 63, 95–103

(2014).

(2) F. Gritti, D.S. Bell, and G. Guiochon, J.

Chromatogr. A 1355, 179–192 (2014).

(3) O. Ismali, C. Allessia, C. Villani, and F.

Gasparrini, J. Chrom. A 1427, 55–68

(2016).

(4) D.C. Patel, Z.S. Breitbach, M.F. Wahab,

C.L. Barhate, and D.W. Armstrong, Anal.

Chem. 87, 9137–9148 (2015).

(5) C.L. Barhate, M.F. Wahab, Z.S. Breitbach,

D.S. Bell, and D.W. Armstrong, Anal.

Chim. Acta 898, 128–137 (2015).

(6) X. Zhang, F. Luo, Z. Loum, and M. Lu, J.

Chrom. A 1359, 212–223 (2014).

(7) Q. Fu, Y. Wang, J. Zhang, H. Zhang,

C. Bai, J. Li, W. Wang, H. Wang, Q. Ye,

and Z. Li, J. Agric. Food Chem. 61(32),

7689–7695 (2013).

(8) Y. Tao, F. Dong, J. Xu, X. Liu, Y. Cheng,

N. Liu, Z. Chen, and Y. Zheng, J. Agric.

Food Chem. 62(47), 11457–11464 (2014).

(9) Q. Zhang, M. Tian, M. Wang, H. Shi, and

M. Wang, J. Agric. Food Chem. 62(13),

2809–2815 (2014).

(10) T. Poiger, M.D. Müller, H.-R. Buser, and

I.J. Buerge, J. Agric. Food Chem. 63(10),

2583–2590 (2015).

(11) I.J. Buerge, A. Bächli, W.E. Heller, M.

Keller, and T. Poiger, J. Agric. Food

Chem. 63(10), 2591–2596 (2015).

(12) Y. Huang, Y. Xu, J. Li, W. Xu, G. Zhang,

Z. Cheng, J. Liu, Y. Wang, and C. Tian,

Environ. Sci. Technol. 47(23),

13395–13403 (2013).

(13) C. Caballo, M.D. Sicilia, and S. Rubio,

Talanta 134, 325–332 (2015).

(14) F. Dong, J. Li, B. Chankvetadze, Y.

Cheng, J. Xu, X. Liu, Y. Li, X. Chen, C.

Bertucci, D. Tedesco, R. Zanasi, and

Y. Zheng, Environ. Sci. Technol. 47(7),

3386–3394 (2013).

(15) X. Wang, Z. Li, H. Zhang, J. Xu, P. Qi, H.

Xu, Q. Wang, and X. Wang, Environ. Sci.

Technol. 47(16), 9233–9240 (2013).

(16) H.Z. Wang, H.G. Zuo, Y.J. Ding, C. Jiang,

and H. Zang, Environ. Sci. Pollut. Res. Int.

6, 4331–42 (2014).

(17) K.-K. Zhang, D.-Y. Hu, H.-J. Zhu, J.-C.

Yang, and B.-A. Song, J. Agric. Food

Chem. 62(8), 1771–1776 (2014).

(18) S.E. Evans, P. Davies, A. Lubben, and B.

Kasprzyk-Hordern, Anal. Chim. Acta 882,

112–126 (2015).

(19) M. Liu, D. Liu, Y. Xu, X. Jing, Z. Zhou, and

P. Wang, J. Agric. Food Chem. 63(21),

5205–5211 (2015).

(20) Y.-P. Zhang, D.-Y. Hu, H.-R. Ling, L.

Zhong, A.-X. Huang, K.-K. Zhang, and

B.-A. Song, J. Agric. Food Chem. 62(37),

9066–907 (2014).

(21) X.-B. Zheng, X.-J. Luo, Y.-H. Zeng, J.-P.

Wu, and B.-X. Mai, Environ. Sci. Technol.

49(2), 785–791 (2015).

(22) B. Berendsen, M. Pikkemaat, P. Römkens,

R. Wegh, M. van Sisseren, L. Stolker, and

M. Nielen, J. Agric. Food Chem. 61(17),

4004–4010 (2013).

Denise Wallworth is with

Sigma-Aldrich UK, a subsidiary of

Merck, in Poole, Dorset, UK. Direct

correspondence to:

[email protected]


Wallworth

0 2 4Time (min)

O

F

F

F

NHCH3

Figure 3: Separation of fluoxetine enantiomers on Chirobiotic V2, 10 mm × 2.1 mm, in

the polar ionic mode, 13 mM ammonium acetate in methanol. (Adapted with permission

from Sigma-Aldrich.) (Taken from G004476, SiAL source.)

Absolute Molecular Weights andSizes with your UHPLC…

and our ģDAWN™ MALS Detector

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RMS radii (rg):

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