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Volume 34, Number s4 April 2016

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Recent Developments in LC Column Technology: Impact on a World of Disciplines . . . . . . . . . . . . . . . 8David S. BellA brief introduction of the articles presented in this supplement.

The Impact of Superficially Porous Particles and New Stationary-Phase Chemistries on the LC–MS Determination of Mycotoxins in Food and Feed . . . . . . . . . . . . . . . . . . . 10Andreas BreidbachThis fit-for-purpose LC–MS-based method provides fast analysis of four mycotoxins using

standard HPLC equipment with a pentafluorophenyl SPP column.

The Synthetic Cannabinoid Chemical Arms Race and Its Effect on Pain Medication Monitoring . . . . . 15Sheng Feng, Brandi Bridgewater, Gregory L. McIntire, and Jeffrey R. EndersAn investigation of C18 and phenyl-hexyl column chemistries for definitive identification

of 13 synthetic cannabinoid metabolites in patient samples.

HPLC Column Technology in a Bioanalytical Contract Research Organization . . . . . . . . . . . . . . . . . . 24Ryan Collins and Shane NeedhamWhen 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.

Characterizing SEC Columns for the Investigation of Higher-Order Monoclonal Antibody Aggregates . . . 28Ronald E. Majors and Linda L. LloydWhen selecting the optimum phase for SEC separations, several key column parameters must be considered carefully.

Positive Impacts of HPLC Innovations on Clinical Diagnostic Analysis . . . . . . . . . . . . . . . . . . . . . . . 37Michael 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.

Latest Advances in Environmental Chiral Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42Denise 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.

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Articles

Apr i l 2016

Volume 34 Number s4

6 RECENT DEVELOPMENTS IN LC COLUMN TECHNOLOGY APRIL 2016

Recent Developments in

LC Column

Technology

Recent Developments in

LC Column

Technology

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FROM the GUEST EDITOR

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

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 archi-

tectures 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 mod-

ern 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 col-

leagues 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 devel-

opments 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 imple-

mentation of many modes of chromatography to fully characterize these complex

systems. The authors point out the importance of particle pore size (and distribu-

tion), pore volume, and surface chemistry treatments as it pertains to modern SEC

requirements. From the world of clinical diagnostics and testing, Wright and Hep-

burn 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 toward 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 dis-

ciplines. As exemplified by the articles within this supplement, developments in our

craft are improving the quality of life around the world. Enjoy!

David S. Bell

LCGC “Column Watch” editor

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Andreas Breidbach

The Impact of Superficially Porous Particles and New Stationary-Phase Chemistries on the LC–MS Determination of Mycotoxins in Food and Feed

Superficially porous particles with their favorable 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.

In 2006, high performance liquid

chromatography (HPLC) columns

packed with superficially porous

particles (SPP) (also known as porous-

shell, core–shell, and solid-core parti-

cles) were introduced to the market. In

performance rivaling sub-2-μm technol-

ogy, SPP packed columns have enabled

highly efficient separations to be car-

ried out with standard HPLC systems

because of the much lower back pres-

sure they generate (1). This favorable

characteristic has also been exploited

for the determination of mycotoxins in

food and feed.

Mycotoxins are secondary metabo-

lites of certain fungi whose occurrence

in food and feed is difficult to avoid.

Therefore, many countries have regu-

lated this occurrence of mycotoxins

(2,3). A wealth of methods of analysis

to enforce these regulations exist (4)

and among them liquid chromatog-

raphy–mass spectrometry (LC–MS)-

based detection is gaining momentum.

LC–MS is primarily gaining momen-

tum 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 prepara-

tion and run approaches with extensive

cleanup. This higher throughput has

been shown for traditional HPLC equip-

ment 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 f low, 18 mycotoxins could

be detected during a 15-min analytical

run. With those settings, deoxyniva-

lenol (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 eff luent was split 1:5. Using a

sub-2-μm fully porous particle packed

column of 100 mm × 2.1 mm dimen-

sions, Varga and colleagues (6) were able

to show a multimycotoxin separation

APRIL 2016 RECENT DEVELOPMENTS IN LC COLUMN TECHNOLOGY 11www.chromatographyonline.com

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 chromatog-

raphy (UHPLC) system capable of deliv-

ering flows at pressures as high as 1200

bar was used.

With the desire to determine mul-

tiple 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-acetyl-

deoxynivalenol (AcDON). Although

DON can be separated from the two

AcDONs on a C18 column, the two

AcDONs are coeluted. Because of dif-

ferent fragmentation behavior it is still

possible to obtain individual quanti-

tative data using MS-MS detection,

but with lesser confidence than with a

full chromatographic separation (5). A

more recent stationary phase chemis-

try capable of separating such isomers

is the so-called pentaf luorophenyl

(PFP, F5) modified silica. The pentaf-

luorphenyl 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, struc-

tural isomers can often be separated.

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 unpro-

cessed 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 gener-

ated 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,

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 pre-

pared and stored. This stock solution

was freshly diluted for every calibration

task. An internal standard solution with

the same concentrations of the respec-

tive 13C-isotopologues in neat acetoni-

trile was also prepared and used undi-

luted. 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-quadru-

pole mass spectrometer with an Ion-

Max HESI2 interface (both Thermo

Scientif ic). 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, Phe-

nomenex) were used. The gradient con-

ditions 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 f low rate of 0.3 mL/min. The col-

umn 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 gradi-

ent 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 f low

Table I: MS source and analyzer settings. (The segment run times relate to

the Ascentis Express C18 column; for the Kinetex columns they were adjust-

ed 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


rate were as stated above. The MS sys-

tem settings can be found in Table I.

The data acquisition was segmented to

limit the number of acquired transi-

tions 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 sus-

pended in 8 mL of water. Then 16 mL

of ethyl acetate was added and after a

brief, hard shake the mixture was soni-

cated for 30 min. After sonication 8 g of

sodium sulphate was added. The mix-

ture was again shaken hard and then left

for 10 to 20 min to allow the sodium

sulfate to crystallize. To settle particu-

late matter and aid phase separation the

tube was centrifuged at a relative cen-

trifugal 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 evapo-

rated 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 recon-

stitution with the pure organic mobile

phase significantly improved the dis-

solution of the more hydrophobic ana-

lytes. Finally, 5 μL of this solution was

injected without further treatment. Tur-

bidity of the injection solutions, often

seen in these reconstituted extracts, did

not negatively affect column lifetime in

our experience.

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 char-

acteristics determined were matrix

effects, method recovery, repeatabil-

ity, and intermediate precision. For

matrix effect and method recovery

determination, different amounts of

the analytes were spiked into materi-

als free of the analytes before extrac-

tion (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 cali-

bration 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 repeatabil-

ity and intermediate precision, natu-

rally 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 pre-

cision). 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 collab-

orative 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 inf lu-

ence 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 sol-

vent. 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 sol-

vent–analyte system across different

cereal matrices.

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

in all six test materials were not signifi-

cantly 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.

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100 100

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0100

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0100

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0100

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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 chromato-grams (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-labeled isotopologues.


Repeatability was determined with

naturally contaminated materials at

three different contamination levels.

Near the low end of the calibration

range, the relative repeatability stan-

dard deviations (RSDr) were between

11% and 18% for the four analytes.

Toward higher contamination lev-

els, which were smaller than exist-

ing (DON and ZON) or anticipated

(HT-2 and T-2) legislative limits in

the European Union (EU), these val-

ues improved to ≤9%. Two of those

materials, the lowest and the high-

est contaminated, were also tested on

eight different days by three different

operators to determine intermediate

precision, or within laboratory repro-

ducibility. For the low contaminated

material relative intermediate preci-

sions (RSDi) were between 13% and

25% for the four analytes. For the

high contaminated material they were

between 11% and 17%. All of these

f indings were comparable with the

results of the collaborative trial (9).

As already mentioned, these per-

formance characteristics are quite

satisfactory considering the analysis

time is only 8.7 min. This is signifi-

cantly shorter than the analysis times

reported by Biselli (5) or Varga (6).

Figure 1 shows a typical chromato-

gram 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 parti-

cles packed in a 75-mm column. Even

though a mobile phase with metha-

nol–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 labora-

tory 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 inf luence ionization

eff iciency caused by, amongst other

things, coeluted compounds. Because

of the high specificity of MS, particu-

larly MS-MS, coeluted compounds,

more likely than not, will be unde-

tected. Better resolution will limit

possible coelution and, therefore, min-

imize inf luences on ionization eff i-

ciencies 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 chem-

istry 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 Kine-

tex C18 and PFP columns. Figure 3

shows the two total ion chromatograms

(TICs). Even though the two AcDONs

were not separated with the C18 chem-

istry, they were with the PFP chemistry.

Retention for all analytes was slightly

higher on the PFP column. Because of

the different fragmentation behavior

of the two AcDONs in MS-MS the

contamination level of the individual

AcDONs can be estimated even from

peaks 2 and 3 in Figure 3b. 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 3a is

absolutely preferable.

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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

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85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

00 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).


Conclusions

Through the use of an SPP packed col-

umn, 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 char-

acteristics. Method recoveries were indis-

tinguishable 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. Val-

ues of RSDr were 18% or smaller for

low contamination levels and improved

to 9% or smaller toward higher levels,

which were still below existing or antici-

pated EU legislative limits. Because of

the intelligent use of stable isotopologues,

matrix effects were negligible at a mini-

mal cost per sample.

Changing the stationary-phase chem-

istry from C18 to pentaf luorophenyl

enabled the separation of the structural

isomers 3- and 15-acetyldeoxynivalenol

as well as DON and ZON in a natu-

rally contaminated maize sample. This

stands to show that SPP-packed col-

umns and new stationary-phase chemis-

tries have advanced mycotoxin analysis

in food and feed.

Acknowledgments

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 con-

taminated maize was a courtesy of the

Austrian National Reference Laboratory

for mycotoxins (AGES, Linz, Austria).

Disclaimer

Any trade names, trademarks, prod-

uct 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 prod-

ucts may lead to the same results.

References

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

son, and B.E. Boyes, J. Pharm. Anal. 3(5),

303–312 (2013).

(2) Food Quality and Standards Service

(ESNS). Worldwide regulations for myco-

toxins in food and feed in 2003. 2004;

Avai lable from: http://www.fao.org/

docrep/007/y5499e/y5499e00.htm.

(3) European Commission, Commission Reg-

ulation (EC) No 1881/2006 of 19 Decem-

ber 2006 setting maximum levels for cer-

tain 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 Edi-

tion: 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 Analyti-

cal Method for the Simultaneous Deter-

mination of Deoxynivalenol, Zearalenone,

T-2 and HT-2 Toxins in Unprocessed

Cereals - Validation Report. 2011; Avail-

able 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 Cere-

als and Feed: Results of a Collaborative

Study (Publications Office of the European

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

tions.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] ◾

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2

2,3

3

4

(a) (b)

4

2.477.19 2.31

6.56

3.81

4.18

4.29

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55

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50

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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.


Sheng Feng, Brandi

Bridgewater, Gregory L.

McIntire, and Jeffrey R. Enders

The Synthetic Cannabinoid Chemical Arms Race and Its Effect on Pain Medication Monitoring

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.

Synthetic cannabinoids, com-

monly 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 cannabi-

noids have become increasingly popular

among adolescents and young adults as

one of several frequently abused sub-

stances. 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 cannabi-

noids, 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 Administra-

tion (DEA), as “necessary to avoid immi-

nent hazard to the public safety” (4). In

response, the chemists instigating this

illegal proliferation have synthesized

many new K2 analogs by slightly altering

chemical structures (5). Therefore, com-

pared with the relatively stagnant pool of

other compounds, such as opiates, that

most pain medication monitoring labo-

ratories 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 modifica-

tions on the core structure. The first

THC analogs, including HU-210 (7)

and CP-47, 497 (8), were synthesized in

the 1980s. Their inventions allowed the

discovery of G protein-coupled recep-

tors, CB1 and CB2 (9). Later on, a struc-

turally different analog, WIN55, 212-

2, was reported. Surprisingly, WIN55,

212-2 has higher affinity toward CB1


and CB2 than THC does (10). Subse-

quently, John W. Huffman developed

a series of “JWH compounds” by sim-

ply replacing the aminoalkyl group in

WIN55, 212-2 with simple alkyl chains

(11). JWH-018 has become the proto-

typical JWH compound. Synthetic can-

nabinoids have also been developed by

generating f luoro-derivatives of JWH

compounds. For example, AM-2201

and MAM-2201 are f luoro-derivatives

of JWH 018 and JWH 122, respec-

tively (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 tetrameth-

ylcyclopropyl ketone indoles, such as

UR-144 and its f luoro-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 sophisti-

cated 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 col-

umn chemistries for definitively identify-

ing 13 synthetic cannabinoid metabolites

in standards and patient samples.

Materials and Methods

Chemicals

Reference standards of 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, MAM-

2201 4-hydroxypentyl metabolite,

PB-22 3-carboxyindole metabo-

lite, PB-22 pentanoic acid metabolite,

UR-144 5-hydroxypentyl metabolite,

UR-144 pentanoic acid metabolite, and

XLR11 4-hydroxypentyl metabolite

were purchased from Cayman Chemi-

cal Company. Reference standards of

11-nor-9-Carboxy-Δ9-THC (THCA),

THCA glucuronide, and THCA-D9

were purchased from Cerilliant Cor-

poration. Solvents including methanol

(optima grade), acetonitrile (optima

grade), and formic acid (88%) were

purchased from VWR. Dimethylsulf-

oxide (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.

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

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 1: Chemical structures of recent synthetic cannabinoids.

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), re-spectively. Blue dashed lines indicate solvent gradients.


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 concen-

tration at 1 ng/mL for all analytes except BB-22 3-carboxyin-

dole 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 pre-

pared 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 com-

bined 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 dispens-

ing-II (ALD-II) system for extraction. A light positive pressure

was applied to push the samples 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–for-

mic 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. Sam-

ples 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 spectrom-

etry (LC–MS-MS). Patient samples were selected for this study

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 1.4Time (min) Time (min)

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 gray 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

Time (min) Time (min)

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 pa-tient samples. The gray areas are integrated peaks. The dashed lines indicate the expected retention time based on the cali-brators.

( Keeping quality control under control. )

Amino acid analysis in accordance toEuropean Pharmacopeia 8.0

www.pickeringlabs.com

CATALYST FOR SUCCESS

PINNACLE PCX


Table I: 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-hydroxy-pentyl

382.11

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-hy-droxypentyl

376.11

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-carboxy-indole

258.01

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-penta-noic acid

372.21

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 acid

358.21

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-hydroxy-pentyl

372.11

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)

390.11141.00 380 48 2 1.53 1.04

169.00 380 10 7 1.53 1.04

PB-22 3-carboxy-indole

232.01

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 acid

389.31

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-hydroxy-pentyl

328.1155.00 380 44 2 1.74 0.93

125.00 380 10 3 1.74 0.93

UR-144 N-pentano-ic acid

342.11

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-hydroxy-pentyl

346.11143.90 380 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


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 sys-

tem (1290 Inifinity binary pump, 1290

TCC, 1290 autosampler, and 1290 ther-

mostat) with a 100 mm × 2.1 mm, 2.7-

μm dp Agilent Poroshell 120 EC-C18 or

50 mm × 2.1 mm Phenomenex Kinetex

2.6 μm Phenyl-Hexyl column. Source

conditions were optimized with a

250 °C gas temperature, gas f low at

19 L/min, nebulizer set to 45 psi, sheath

gas heater at 300 °C, sheath gas f low

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 question-

able 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 metabo-

lite, PB-22 3-carboxyindole metabo-

lite, 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 stan-

dard, 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 I. The chromatographic start-

ing 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

Table II: 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

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0.5-mL/min f low throughout (Tables

II and III). The 2.5-min phenyl-hexyl

method was validated according to a

previously published procedure (16).

Results and Discussion

Various methods including colorimet-

ric detections (17), immunochemical

assays (18), nuclear magnetic resonance

(NMR) (19), gas chromatography–mass

spectrometry (GC–MS) (20), and LC–

MS-MS (21), have been developed for the

analysis of synthetic cannabinoids. With

those methods, many synthetic cannabi-

noids have been successfully analyzed in

different samples such as plant materi-

als, human hair, saliva, serum, and urine.

Several analytical reviews have summa-

rized the identification and quantifica-

tion techniques for synthetic cannabi-

noids that are currently popular (22,23).

Among those methods, LC–MS-MS

has clear advantages of ease and speed

of sample preparation and the capabil-

ity 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 inter-

est (usually longer than 10 min, see Table

IV). To improve the analysis of synthetic

cannabinoids, we developed new LC–

MS-MS methods with two different col-

umn chemistries (C18 and phenyl-hexyl),

which take either 2.5 min or 5 min for

each sample to achieve optimal resolu-

tion. 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 com-

pounds 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 com-

pounds that share the tetramethylcyclo-

propyl 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 col-

umns. In both the 2.5-min and 5-min

methods, those three compounds were

eluted much 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

Table III: 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

Table IV: LC–MS-MS conditions for synthetic cannabinoids in urine samples in

selected studies

Targets Purification ColumnTime of

Gradient

LOD

(ng/mL)Reference

Metabolites of JWH-018 and JWH-073

Dilution (hydrolysis)

Zorbax Eclipse XDB-C18 (150 mm × 4.6 mm, 5 μm)

10 min <2.0 (24)


SPE (hydrolysis)

Zorbax Eclipse XDB-C18 (150 mm × 4.6 mm, 5 μm)

10 min <0.1 (25)

Metabolites of 8 synthetic cannabinoids

LLE (hydrolysis)

AQUASIL C18 (100 mm × 2.1 mm, 5 μm) (Thermo Scientific)

14 min 0.1 (26)


LLE (hydrolysis)

Acquity UPLC HSS T3 (100 mm × 2.1 mm, 1.8 μm) (Waters)

More than 3.2

min(27)

Metabolites of 7 synthetic cannabinoids

LLE (hydrolysis)

Luna C18 (150 mm × 2 mm, 5 μm) (Phenomenex)

15 min (28)

Metabolites of UR-144 and its pyrolysis product

LLE (hydrolysis)

Zorbax Eclipse XDB-C18 (150 mm × 2.1 mm, 3.5 μm) (Agilent)

19 min (29)

9 synthetic cannabinoids, 20 metabo-lites

PP (hydrolysis)

XB-C18 (50 mm × 3.0 mm, 2.6 μm) (Kinetex)

10 min 0.5–10 (21)

15 indole derivative synthetic cannabinoids

LLE (hydrolysis)

Ascentis C18 (150 mm × 2.1 mm, 5 μm) (Supelco)

16 min 0.1–0.5 (30)

17 me-tabolites of synthetic cannabinoids

LLE (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


due to their tetramethylcyclopropyl structure having a higher

affinity toward 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 con-

siders that synthetic cannabinoids with different chemical

structures will have different elution behaviors in two dis-

tinct 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 posi-

tives for this class of compounds using two different column

chemistries might help better separate compounds with simi-

lar 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 ana-

lyzed using both C18 and phenyl-hexyl columns, both quanti-

fier (quant) and qualifier (qual) peaks for JWH-018 pentanoic

acid metabolite came out earlier than expected based on cali-

brators (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 instru-

ment 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 pos-

itive 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 detec-

tion of JWH-018 pentanoic acid metabolite in our methods

compared to the C18 column. The fact that this patient sam-

ple 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 sam-

ple, 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 envi-

sioned (for example, straight chain versus 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

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 gray 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 chro-matographically separated; however, the integration software (under reasonable integration conditions) incorrectly selected the interferent for integration.

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window for the phenyl-hexyl column.

These types of interferences are ram-

pant among positive and questionably

positive synthetic cannabinoid patient

samples.

Patient 03 had a very strong well sepa-

rated quant peak for UR-144 N-penta-

noic acid, but the qual peak showed an

interferent just a few seconds away from

the targeted retention time. This inter-

ferent 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 inte-

grated the interferent. With the phenyl-

hexyl column chemistry, the qualifier

peak has coalesced into the interfer-

ent peak entirely and is not able to be

resolved, even with manual integration

intervention. The fact that this interfer-

ent 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 syn-

thetic cannabinoids in patient urine

samples has been described. Two dif-

ferent column chemistries (that is, C18

and phenyl-hexyl) have been applied

using this method. Three compounds,

including XLR-11 N-(4-hydroxylpen-

tyl), UR-144 N-pentanoic acid, and

UR-144 N-(5-hydroxylpentyl) metabo-

lites, 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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HPLC Column Technology in a Bioanalytical Contract Research Organization

High performance liquid chromatography–tandem mass spectrometry

(HPLC–MS-MS) is the go-to technique for high-throughput analysis of small-

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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 flex-

ibility of the C18 is that it allows for the

standardization of many HPLC–MS-MS

methods, which greatly increases the pro-

ductivity of high-throughput analysis.

With multiple standardized methods rely-

ing 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 fac-

tor (AF), or poor repeatability, decisions

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

2-μm solid core

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

Figure 1: Representative column method development flowchart.

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


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 flow-

chart 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 devel-

oped on a C18 column, the next step is typi-

cally to evaluate the polar moieties and func-

tional 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 particu-

larly small, polar molecule, another option

available is to choose a column such as an F5

column (a pentafluorophenylpropyl station-

ary phase) or to use a hydrophilic-interaction

chromatography (HILIC) method. HILIC

methods use gradients with a high percent-

age of organic content coupled either with

an unmodified silica column, an amino col-

umn, 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 bio-

analytical 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 bench-

marks may have been met during develop-

ment, 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 over-

all 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 instrumenta-

tion was devised; thus, UHPLC was born

(2,3). Using an UHPLC system available

from various vendors, it is possible to success-

fully 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 bio-

analysis 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 desir-

able 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 per-

meable shell of porous silica. While the outer

shell of the particles are similar in materials

and function as a conventional fully porous

column particle, the inner core is imperme-

able (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 represen-

tation 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 diffu-

sion relates to quicker, more efficient separa-

tions than were previously possible with fully

porous columns, and results in a tighter peak

shape as the shorter path reduces the diffu-

sion of the analytes (8).

Emerging Technologies

Yet another approach of reducing costs and

increasing efficiency in bioanalytical analy-

sis is the implementation of microflow LC

coupled with a mass spectrometer. As com-

pared 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

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.


below 100 μL/min, greatly reducing the

consumption of solvents. This reduction in

solvent use directly translates to a cost sav-

ings in the purchasing of solvents, disposal

of solvent waste, and the labor of solvent

preparation—none of which are insignifi-

cant expenses in a high-throughput labora-

tory that is virtually running continuously.

The drastically lower flow rates associated

with microflow LC–MS-MS also translate

to less solvent flowing through the electro-

spray ionization (ESI) source. This means a

cleaner MS system and a lower cost associ-

ated with MS maintenance.

Microflow LC–MS-MS employs col-

umns with drastically decreased inter-

nal 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 integra-

tion 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 tub-

ing 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 com-

pared 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 com-

bined 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, devel-

oping robust methods for novel therapeu-

tics 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 biomark-

ers. Increasing efficiency and productivity

on both the front end (method develop-

ment) 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 pharmaceu-

tical 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 para-

mount 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. Chro-

matogr. 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. Vou-

ros, 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. Direct correspondence to:


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 sur-rogate 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.


Ronald E. Majors

and Linda L. Lloyd

Characterizing SEC Columns for the Investigation of Higher-Order Monoclonal Antibody Aggregates

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.

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. Chromato-

graphic separations will still play a key role

not only in the purification of these biolog-

ics, 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 requir-

ing nondenaturing conditions will not tol-

erate high concentrations of organic mobile

phases or, when LC coupled to mass spec-

trometry (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 sen-

sitive 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 favor

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 pro-

cedures 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 aggrega-

tion with the possibility of visible precipi-

tation 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), effi-

cacy (decreased bioactivity), and immu-

nogenicity (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-exclu-

sion chromatography (SEC) is a required

technique for soluble aggregation analysis

and quantitation.

Size-Exclusion Chromatography

Unlike all other modes of high perfor-

mance liquid chromatography (HPLC),

pure SEC involves absolutely no interac-

tion between the analyte and the pack-

ing 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 Fig-

ure 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 per-

meate 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 resi-

dence 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 vol-

ume (Vi), of the column and the smallest

molecules that permeate all of the pore vol-

ume 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

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.

www.jmscience.com 716.774.8706

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HPLC Columns


many column volumes. Also, for SEC, the

elution order is unlike other LC modes

such as reversed-phase chromatography

where the larger, more-hydrophobic mol-

ecules are eluted last and the smaller, more-

hydrophilic molecules are eluted first.

How is the SEC data used? Most fre-

quently, 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 reten-

tion time (or elution volume). In Figure 3,

a protein–peptide standard mix consisting

of various known molecular weight com-

pounds was used to make up this plot. The

proteins, peptides, and their respective MWs

are identified in the figure caption. The cali-

bration plots are generally-fitted to a polyno-

mial. Because the SEC separation is based on

the hydrodynamic volume of a molecule in

solution and not solely on MW, any extrapo-

lated 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 appar-

ent MW of the main compound was deter-

mined to be 18.4 kDa, which coincides with

the MW of β-lactoglobulin. The small peak

eluted just before the major peak has a reten-

tion time of 8.3 min, which from the calibra-

tion 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 detec-

tion must be used. Most often a light scatter-

ing (LS) detector is used to provide absolute

MW and also provides an increased sensitiv-

ity for the higher MW aggregates. A mass

spectrometer can also be used to measure an

absolute MW and provide structural identi-

fication 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 quan-

titation. A typical SEC column has notable

parameters that define its separation charac-

teristics, some unique to the SEC mode and

some that are well known chromatographic

principles. Table I provides typical column

parameters that are useful for comparison

with advantages and disadvantages listed.

Out of this large number of parameters, we

shall now look at the more important ones

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

8.24

1

7.84

2

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 molecu-lar weight and as small molecule, uracil. By plotting the retention time against mo-lecular weight the polynominal fit equation can be used to calculate the equiva-lent 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 2: Mechanism of SEC in the separation of different sizes of molecules. Mol-ecules 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.


Table I: Important parameters in the characterization of an SEC column

Column

ParameterInfluences Advantages Disadvantages Comments

Particle pore size

Defines molecular sizes that can be resolved (separa-tion range)

Large pore sizes allow sepa-ration of larger macromol-ecules; 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 pro-vide 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 packing

Resolution Larger pore volume extends useful range of calibration curve giving higher resolu-tion 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 column

Resolution Longer columns or multiple columns extend separation range by increasing total pore volume

Additional columns slow down separation and in-crease the cost

Multipore columns have been developed but single multipore columns have limited resolution

Particle size Column efficiency Smaller particles provide narrower peaks and there-fore better resolution and better sensitivity than larger particles

Smaller particles give rise to higher back pressure, may generate frictional heating; may require lower band dis-persion 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 mol-ecules; typical particle sizes are 1.7, 2.7, 5, and 10 μm

Column length Resolution Longer 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 sensi-tivity 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, accura-cy, and reproducibility is af-fected; surface deactivation procedure with hydrophilic properties is paramount

Flow rate Speed and efficiency

High flow rates decrease analysis time, may affect ef-ficiency and raise pressure

Low flow rates increase anal-ysis time, increase efficiency, and lower pressure

Compromise must be made just like any chromatograph-ic experiment

Particle stability Column lifetime and performance

Robust silica-based particles stand up to UHPLC conditions and allow higher pressure operation

Unstable particles create voids, give higher back pres-sure as they break down, and create problems with LS and MS detectors.

Modern particles are gener-ally engineered to withstand UHPLC conditions; older particles may not handle as well

Column stability

Replacement 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 labo-ratory practice

Batch-to-batch and column-to-column repro-ducibility

Data reproducibil-ity and quantita-tion

Reproducible batches of packings and packed col-umns provide data integrity and eliminate unnecessary revalidation

Nonreproducibility of pack-ing and columns provides nonrugged methods and lots of rework

Manufacturers should ensure that their products meet the performance needs of their customers.


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 pro-

tein mixture on two different columns

with the same dimensions but with dif-

ferent 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 col-

umn, 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 4a). 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 4b). In addition, the larger-pore-

size column also possesses a larger pore

volume, which allows for better resolution

throughout the chromatogram. Some-

times 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

Time (min)

Time (min)Ab

so

rban

ce (

mA

U)

Ab

so

rban

ce (

mA

U)

Monomer

DimerTrimerHigher orderaggregates

Mobile phase: 150 mM sodium phosphate, pH 7.0Flow rate: 0.5mL/minSample: 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

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.

300 mm x 4.6 mm

Time (min)

Ab

so

rban

ce (

mA

U)

Flow rate: 0.35 mL/minInjection volume: 2 μL

300 mm x 7.8 mm

Flow rate: 1.0 mL/minInjection volume: 6 μL

200

175

150

125

100

75

50

25

0

Ab

so

rban

ce (

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 5: Separation of protein standards on 7.8-mm and 4.6-mm i.d. columns. Upper chro-matogram: 300 mm × 4.6 mm, 2.7-μm dp AdvanceBio SEC 300 Å, 0.35 mL/min. Lower chro-matogram: 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.

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


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, every-

body 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 labo-

ratories practicing 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 limita-

tions of column dimensions (smaller col-

umn lengths and volumes mean lower reso-

lution 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 lin-

ear velocity (0.35 mL/min). Compared to

the 7.8-mm i.d. column, the overall resolu-

tion for the 4.6-mm i.d. column was barely

impacted for these proteins. However, the

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 downward based on the inverse

square of the column radii. In addition, a

lower flow rate for the 4.6-mm i.d. col-

umn 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 elu-

ents 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 con-

taining 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 chro-

1

1

1

1

2

2

2

2

2

2

2

2

1

1

1

1

3

3

3

3

3

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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 15Time (min)

5 10 15Time (min)

5 10 15Time (min)

5 10 15Time (min)

5 10 15Time (min)

4 62 8 10 12 14Time (min)

4 62 8 10 12 14Time (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)

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.


matographic 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 micrometers)

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 frag-

ile 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 size comes

into play to a greater extent than in other

LC modes. This can be clearly seen in Fig-

ure 7 where several popular commercial

products of different particle sizes and pore

sizes are compared. The sample was a stan-

dard 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 vari-

ous 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 manufac-

tured 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 (Figure 9).

Rather than testing each column with a

series of proteins and mAb aggregate sam-

ples, 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 col-

umn that is received has not seen any pro-

tein sample. In addition, to prevent any pos-

sibility 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 ven-

dor 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 precau-

tions 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 pro-

cedures. Silica gel is a more rugged packing

than the soft gels of yesteryear, but neverthe-

less 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

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

an

ce (

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

11.1

65

11.3

228

.878

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

.21

2

5.6

23

6.4

98

7.2

28

8.4

16

8.7

62

11

.32

3

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 8: Batch-to-batch reproducibility of SEC columns for protein standards. Col-umn: 300 mm × 7.8 mm, 2.7-μm dp AdvanceBio SEC 300 Å; mobile phase: 150 mM so-dium phosphate, pH 7.0; flow rate: 1.0 mL/min. Protein standards: 1 = thyroglobu-lin dimer, 2 = thyroglobulin, 3 = IgA, 4 = IgG, 5 = ovalbumin dimer, 6 = ovalbumin, 7 = myoglobin, and 8 = vitamin B12 (marker).


interactions, silica gel SEC columns require

some surface deactivation by bonding, coat-

ing, or building into the phase strong hydro-

philic characteristics. The bonding of the

diol functionality appears to be the favored

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 adsorp-

tion with subsequent low recovery and non-

reproducible 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 replac-

ing 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 injec-

tions. 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 con-

taining 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 medica-

tion 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 result-

ing 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 add-

ing hydrochloric acid to the sample solu-

tions 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

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 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 se-quence. 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; mo-bile phase: 150 mM sodium phosphate, pH 7; flow rate: 0.35 mL/min.

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

ce (

mA

U) 80

60

40

20

0

Ab

sorb

an

ce (

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

911.8

34

11.8

53

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 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.


60 min. Figures 11a (innovator drug, red

trace) and 11b (biosimilar drug, red trace)

show the initial profile of each drug deter-

mined 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 experi-

ments were carried out, the SEC profiles

were dramatically changed. The innovator

drug (Figure 11a, blue trace) showed evi-

dence 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 11b, 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 infor-

mation 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 quan-

titation of dimer and higher-order aggregates.

Conclusion

As the shift in pharmaceutical drug devel-

opment toward biological-based entities

continues, HPLC and UHPLC column

technology will have to shift with the mar-

ket 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 char-

acteristics that impact the performance of

an aqueous SEC column, particularly one

that is suited for the separation and quanti-

tation 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 frag-

ment 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, EvaluatePha-

rma (2014).

(3) L. Lloyd, LCGC North Am. 32(s4), 30–35

(2014).

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

Klasper, R.J. Vreeken, A.J.R. Heck, and W. Jis-

koot, 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. Linda L. Lloyd

is with Agilent Technologies in Church

Stretton, Shropshire, UK. Direct correspon-

dence to: [email protected] ◾

Ab

sorb

an

ce (

mA

U)

Ab

sorb

an

ce (

mA

U)

(a)

(b)

160

140

120

100

80

60

40

20

04 6 8 10 12 14

160

140

120

100

80

60

40

20

0

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)

Figure 11: Application of SEC to characterize a commercial mAb and its biosimilar: intact and stressed conditions. SEC Chromatograms of (a) intact ribuximab innova-tor (red trace) overlaid with pH and heat-stressed sample (blue trace) and (b) intact rituximab biosimilar (red trace) overlaid with stressed sample (blue trace). Chromato-graphic conditions: Column: 300 mm × 7.8 mm, 2.7-μm dp AdvanceBio SEC 300 Å; mo-bile 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.


Michael J.P. Wright

and Sophie Hepburn

Positive Impacts of HPLC Innovations on Clinical Diagnostic Analysis

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.

Chromatographic techniques (includ-

ing liquid, gas, and thin-layer chro-

matography), 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 toward mass

spectrometry (MS) detection rather than

conventional detection methods (ultraviolet

[UV], fluorescence, and electrochemical) (2).

This shift was driven by the uptake of liq-

uid 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 para-

mount. 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 selectiv-

ity 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–elec-

trochemical detection (ECD), and HPLC–

fluorescence detection (FD) methods and

an ever-increasing number of LC–MS-MS

methods.

Diagnostic clinical chemistry depart-

ments, 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 auto-

mated colorimetric, nephelometric–turbidi-

metric, 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 chromatogra-

phy and MS equipment vendors supplying


instrumentation to specialist clinical chem-

istry laboratories. As a result, obtaining the

capital funds to purchase LC–MS-MS

instrumentation often requires detailed busi-

ness 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 com-

monplace 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 sam-

ples from various patient populations can

necessitate more than one chromatographic

method for the analysis of a target biomarker

to enable measurement across all patient sub-

groups and allow for confirmatory testing

when unusual interferents are present. This

need places a great deal of emphasis on sta-

tionary-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

centers 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 of replacing instrumentation with

ultrahigh-pressure liquid chromatography

(UHPLC) equipment capable of recogniz-

ing 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 with-

out 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-hydroxyindoleace-

tic 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

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

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 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.

Figure 2: Back-pressure and robustness advantages of 2.7-μm particle columns ver-sus 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 indi-cates the back-pressure limit of the standard HPLC systems in the laboratory.


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 chroma-

tography further is no longer the back pres-

sure, but rather a combination of other fac-

tors including autosampler operating speed,

detector cell volume, and the data collection

rate limit of the detector.

Accelerated chromatography can cer-

tainly 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 col-

umn, is the requirement for cleaner, particu-

late-free mobile phases and more exhaustive

sample preparations before injection to pre-

vent blockages. In a high-throughput clini-

cal laboratory these extra sample preparation

requirements can be an additional burden

on staffing and workflow. SPP columns

with >2-μm particles provide an intermedi-

ate solution.

To assess robustness we performed the fol-

lowing experiment: 100 μL of serum sam-

ples were protein precipitated by the addition

of 25 μL of 0.2 mol/L zinc sulfate followed

by 200 μL of methanol. The resulting solu-

tion was passed through a 0.45-μm 96-well

Multiscreen Solvinert filter plate (Millipore)

before being loaded onto a Nexera series

UHPLC system (Shimadzu) coupled to

an API 6500QTRAP mass spectrometer

(Sciex). The three columns under evalua-

tion 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 metha-

nol. A rapid gradient of 50–100% B was per-

formed 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 deter-

mined by an injection of a system suitabil-

ity 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 pres-

sure increased for all columns as the injec-

tion 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 instru-

ments over a large number of injections.

Innovations in

Stationary Phases

The move toward LC–MS-MS analysis

in clinical chemistry has provided many

benefits; however, challenges involving

chromatographic separation of similar com-

pounds 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 station-

ary phase has taken on increased importance

(4). Chromatography is required not only for

the removal of interferents causing ion sup-

pression, 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 separa-

tions 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 chem-

istry laboratories over the past 10 years; 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 sepa-

rating the C3-epimeric forms often found

in samples from infants. The 3-epi-25OH

form of vitamin D3 is thought to be an inac-

tive 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 spec-

tra 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, chro-

matography using cyano stationary phases

were utilized but limited selectivity of the

phase resulted in run times of 18–45 min,

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 elu-tion 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.


which were too long to be feasible for the

volume of test requests (6). The develop-

ment 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 clini-

cal 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 criti-

cal 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 station-

ary phases with a wide range of chromato-

graphic properties that are capable of oper-

ating at 100% aqueous mobile phases (8).

In this example, an EPG stationary phase,

operated under aqueous conditions, enabled

resolution of these critical pairs (Figure 4a).

For the measurement of serum ste-

roids 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 interfer-

ences are common. To further complicate

matters, because of their structural similar-

ity, steroids often have similar fragmenta-

tion patterns and can also be present at sup-

raphysiological concentrations, for example,

when used for treatment. Thus, even for

compounds that have slightly different pre-

cursor mass-to-charge ratios (m/z), the pos-

sibility of interference from naturally occur-

ring 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 selec-

tivity 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 sep-

aration of common isobaric steroid interfer-

ences, such as those outlined in Figure 4b.

Leveraging the Most

Out of Instrumentation

For small to moderate-sized specialist clini-

cal 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 applica-

tions rely on different mobile and station-

ary phases to achieve the chromatographic

selectivity required. To leverage the capacity

of the LC–MS-MS instruments to achieve

favorable 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 selec-

tion-valve configurations allowing multiple

mobile phase and column combinations

to be run simultaneously have existed for

some time in research and assay develop-

ment laboratories. However, because of reli-

ability issues, complicated software, con-

cerns 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 instru-

ment software.

Figure 5a 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 Gen-

eral Conditioning Method*: direct

line (no column) and mobile-phase A4

and B4 (cleaning solvent)—this step

purges the system with 50% metha-

nol, removing the mobile phases from

Method 1 and thus preventing the pos-

1.65

1.37

Time (min)

Inte

nsit

y (

cp

s)

3.0

1.37

1.01 3.71

3.58

3.71

4.41

2.75

2.352.26

Time (min)

Inte

nsit

y (

cp

s)

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 biphe-nyl 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 de-tecting the naturally occurring M+2 isotope.


sibility 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*: direct line

(no column) and mobile-phase A2 and

B2 (Method 2 mobile phases)—This

primes the system with the correct

mobile phases for Method 2 in prepara-

tion 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 Gen-

eral 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*: direct line (no

column) and mobile-phase A3 and B3 . . .

and so on, with up to five different clini-

cal assay methods running without user

intervention.

t� *The liquid flow during the various

conditioning batches is diverted to waste

immediately before the mass spectrom-

eter to prevent fouling of the ion source.

On-line solid phase extraction (SPE) is

a popular technique in clinical diagnostic

laboratories because of the labor and cost

savings it represents compared to off-line

SPE. Adding multiple on-line SPE stations

to a system (Figure 5b) 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 dur-

ing 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 spec-

trometer ion source conditions for the subse-

quent sample batch.

A clear advantage in running assays

sequentially on a single system (or even par-

allelism in larger laboratories) is that of opera-

tion 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 sam-

ple congestion during working hours where

instruments would be better used for assay

development and improvement processes. It

also allows LC–MS-MS methods to com-

pete 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 biomark-

ers. 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 chromato-

graphic challenges facing clinical labora-

tories 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 unfavorable,

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. Chaud-

hary-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, Bio-

analysis 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 Depart-

ment of Clinical Chemistry and Endocri-

nology at the Prince of Wales Hospital

in Sydney, Australia. Direct correspon-

dence to: [email protected] or


(b)

(a)

Mass

spectrometer

Mass

spectrometer

Column

oven

Autosampler

Solvent

selection valve

On-line SPE cartridge Two-position divert valve

Six-position selection valve

Analytical column

Autosampler

Pumps 2Waste

Pumps 1

Pumps 1

Column

oven

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 se-lection; (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.


Denise Wallworth

Latest Advances in Environmental Chiral Applications

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.

While in earlier years environ-

mental applications concen-

trated mainly on agrochemi-

cals in use, it is now a much broader field

covering not just preferential enantiose-

lective activity, but also the influence of

microbial population on selective degra-

dation. The impact of excess and metab-

olized pharmaceuticals is also widely

studied along with persistent organic

pollutants (POPs), that includes a range

of both pesticides and fluorinated organ-

ics. 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 sta-

tionary-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 comprehen-

sive multicomponent screening. A signifi-

cant 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 utili-

zation of sub-2-μm ultrahigh-pressure liq-

uid chromatography (UHPLC) particles

for chiral separations, mostly on brush

type and cellulosic CSPs. A recent paper

by Gasparrini (1) demonstrated the ben-

efits of both UHPLC and supercritical

fluid chromatography (SFC) of the high

efficiencies obtained by bonding onto

Whelk-O-1 onto both 1.7-μm porous sil-

ica 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 introduc-

tion of a 1.9-μm monodisperse totally

porous particle (TPP) (2) that appears

to provide new opportunities to increase

CSP efficiencies even further. These par-

ticles, when bonded with C18 exhibited

an extremely low reduced plate height, h,

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

umns, extremely low when compared to

classical porous particles. Gasparrini (3)

demonstrated extremely high efficiencies

obtained by bonding teicoplanin to TPPs

and carried out extensive fundamental

studies of the CSP, reporting efficien-

cies of 200,000–250,000 plates/m at the

optimum flow rate. Additionally, Arm-

strong and coworkers (4,5) reported ultra-

fast 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 moni-

toring 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 sepa-

W


ration of multichiral center pesticides in

the near future (4).

Environmental Applications

The fast growth in agrochemicals has

fueled much research into their environ-

mental 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 com-

mercial cost for multitonnage agricultural

requirements. Despite this, some 24%

of these are applied as a racemate (7),

resulting in the potential release of inac-

tive products into the environment. Of

the $223 billion global pesticide indus-

try, 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 produc-

tion industry.

The fate of pesticides in the environ-

ment is expected to be subject to enan-

tioselective biodegradation by microor-

ganisms, possibly in quite a different way

0 2 4 6 8 10 12 14

Cl Cl

Cl

Cl

Cl

Cl

ClCl

Cl

ClClCl

Mirrorα-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: chlor-dane 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.)

HILICpak VG-50

A polymer based tertiary amino columnfor phosphorylated saccharide HILIC analysis


compared to microorganisms present in

water because of residue matrix bind-

ing effects. The differing enantiomeric

activities of chiral pesticides, the effect

of various microorganisms giving differ-

ing modes of degradation, and the result-

ing 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 con-

cerns. CSPs used for environmental sepa-

rations need to be capable of separating

relatively polar molecules. Fortunately,

high performance liquid chromatography

(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 using a 3-μm

bonded amylose tris(3,5-dimethylphenyl-

carbamate) CSP in carbon dioxide–meth-

anol. Formic acid in methanol was added

post column to enhance mass spectrom-

etry (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 carried

out 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 elut-

ing 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 organochlo-

rine pesticides in air and surface water in

the Indian Ocean were measured using

chiral GC–MS (12) employing EI detec-

tion in multiple reaction monitoring

(MRM) mode and a 20% tert-butyldi-

methylsilyl-beta-cyclodextrin CSP dis-

solved in 15% phenyl-, 85% methylpoly-

siloxane. 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 pharma-

ceuticals in wastewater, a method for the

simultaneous enantioselective determina-

tion of ibuprofen, naproxen, and keto-

profen 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 van-

comycin 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 trac-

ing MS-MS method was used to inves-

tigate the fate of the four isomers of IPP,

a novel, broad spectrum neonicotinoid

insecticide (7). Stereoselective soil bind-

ing and the microbial influence on epi-

mer-selective degradation were reported.

Enantioselective Activity

As is well known for chiral pharmaceu-

tical products in biological systems, if a

pesticide is a chiral molecule, it is com-

mon 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

0

20

40

60

80

100

120

0 1 2 3 4

Rela

tive c

on

ce

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-haloxy-fop acid in soil. (Reproduced with permission reference 10.)


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 herbi-

cide 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 difenocon-

azole 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 metabo-

lite, 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 enantioselec-

tive 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 mag-

nesium sulfate to protect the chiral GC

column. Relative enantioselective bioac-

tivity 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 investi-

gated the different enantioselective degra-

dation rates under various soil conditions

as a possible cause and concluded that dif-

fering 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 micro-

organisms in the environment is chiral

and can result in differing metabolism

(microbial transformation), causing pos-

sible selective accumulation of one iso-

mer over the other. Many recent studies

provide evidence of such microbial trans-

formation by comparing transformation

profiles in sterile and nonsterile soils.

In the case of haloxyfop and haloxyfop

methyl, a study was carried out using chi-

ral 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 inver-

sion 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-enan-

tiomer. Interestingly, faster inversion was

observed for the acid when originally

applied as haloxyfop methyl.

Individual enantiomers were isolated

for the study using a cellulose tricin-

namate CSP in 95:5:0.1 heptane–isopro-

panol–acetic acid, purifiying 2 mg from

a total of 10 injections (20 min per injec-

tion) and confirmed with >99% enan-

tiomeric purity by chiral GC–MS as the

methyl ester. Analytically, 85:5:10 hep-

tane–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-enantio-

mer results in independence of herbicidal

activity from the enantiomeric composi-

tion 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 apply-

ing 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 confir-

mation of its degradation by soil micro-

bial 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 configu-

rations of the two dufulin enantiomers,

confirmed as the S-(+)-enantiomer for

the first eluting enantiomer, and R-(−)-

enantiomer as the second one.

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


It is also now established that there

is enantioselective toxicity from many

pharmaceutically active compounds and

illicit drugs to freshwater species, espe-

cially through adsorption on sediments

and suspended solids. For example, S-(+)-

fluoxetine and S-(-)-atenolol significantly

inhibit the growth of a freshwater proto-

zoan, Tetrahymena thermophilia, compared

to the opposite enantiomer (18). This study

aimed to develop a comprehensive screen-

ing protocol for multiresidue identification.

After microwave assisted extraction and

solid-phase extraction (SPE), separations

were carried out on a 5-μm cellobiohydro-

lase 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% for-

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

method was used to investigate stereoselec-

tive 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 com-

pound and its acid metabolite was achieved

using a tris(3,5-dimethylphenylcarbamate)

coated cellulosic CSP in a mobile phase of

n-hexane and 2-propanol (91:9, v/v). Elu-

tion order, determined using a polarimet-

ric 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-dimethylphenylcarba-

mate) in normal phase reported no inter-

conversion but degradation of each isomer

depended on soil pH and its microbial

activity (20). Many studies have been car-

ried 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 nonse-

lective maternal transfer to chicks and it

was found that enantiomeric enrichment

of PCBs 95, 132, and 149 and intercon-

version of PCB 135 later occurred in the

chick resulting in different toxicity com-

pared to the adult.

Interestingly, the unexpected appear-

ance of the banned antibiotic chloram-

phenicol 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 stud-

ied by chiral LC–MS using an α1-acid

glycoprotein CSP and found to be related

to its bioavailability (22).

Summary

Stereoselective investigations need to con-

tinue to play a significant role in the study

of the environmental impact of agrochem-

icals, POPs and pharmaceutical products.

Apart from their impact on living organ-

isms, a critical outcome of their presence

is the disruption of the natural microbial

status resulting from stereospecific trans-

formation of these molecules, as well as the

potential for their enantioselective persis-

tence in the environment. The majority of

applications reported used either polysac-

charide 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 ultraeffi-

cient TPP-based CSPs bonded with a wide

range of chiral selectors is set to transform

chiral HPLC separations yet again.

References

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

Chromatogr. A 1355, 179–192 (2014).

(2) A. Cavazzini, N. Marchetti, R. Guzzi-

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

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

TrAC, Trends Anal. Chem. 63, 95–103

(2014).

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

parrini, 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.



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