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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

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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


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.

Rela

tive a

bu

nd

an

ce

Time (min)

RT: 11.92

RT: 10.29

RT: 14.09

18.009.108.385.643.052.69 16.2514.61

RT: 5.97

100

95

90

85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

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] ◾

Rela

tive a

bu

nd

an

ce

Time (min)

11

2

2,3

3

4

(a) (b)

4

2.477.19 2.31

6.56

3.81

4.18

4.29

100

95

90

85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

0

Rela

tive a

bu

nd

an

ce

100

95

90

85

80

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

00 1 2 3 4 5 6 7 8 9 10

Time (min)

0 1 2 3 4 5 6 7 8 9

Figure 3: Total ion current of a maize sample highly contaminated with DON, AcDONs, and ZON; sample extract was diluted eight times; separation with (a) Kinetex PFP and (b) Kinetex C18 columns; Peaks: 1 = DON, 2 = 15-AcDON, 3 = 3-AcDON, 4 = ZON.


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 OO

OO

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


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.

BensonpolymericTM

HPLC Columns for Organic Acid Analysis

Over 25 years of experience providing high quality polymeric

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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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Enders are with Ameritox Ltd., in Greens-boro, North Carolina.

Direct correspondence to:

[email protected] ◾

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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-

molecule therapeutics, metabolites, and biomarkers. Through technological

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

analyte in the contract research environment has become easier and faster

than ever. Increasingly shorter run times, higher sensitivity, and greater

separation have all become possible in a standard method. This is, in part,

because of column technologies that have enabled the standardization of

the method development process. Method efficiency and productivity are

also improving because of emerging column technologies such as sub-2-μm

particles coupled with ultrahigh-pressure liquid chromatography (UHPLC)–

MS-MS, superficially porous particle columns, and microflow HPLC–MS-MS.

Increasing efficiency and productivity in high-throughput bioanalysis is

becoming more important as the applications for HPLC–MS-MS expand

to large molecules such as peptides, proteins, and oligonucleotides.

Over the course of the last several

decades, high performance liquid

chromatography–tandem mass

spectrometry (HPLC–MS-MS) has become

the method of choice for high-throughput

analysis of small-molecule therapeutics,

metabolites, and biomarkers. This is due,

in large part, to the selectivity and sensitiv-

ity provided by HPLC–MS-MS, combined

with the ability to rapidly develop an assay

consisting of quick extractions and short run

times for a vast majority of small molecules.

When presented with a new analyte at

a bioanalytical contract research organiza-

tion (CRO), the goal is to develop a robust

method with good chromatographic reso-

lution, repeatable results, and a quick run

time. However, after these scientific crite-

ria have been met, the ultimate end goal

for any bioanalytical CRO is productivity

and efficiency—analyzing the most sam-

ples possible while using the minimum

amount of solvent, supplies, and resources,

and still remaining scientifically sound.

In short, the goal at a CRO is to create

the most productive method in the most

efficient manner possible, all while using

sound science. This approach benefits not

only the CRO, but also its bioanalytical

clients, and most importantly, the end

users; patients that can receive care from

these novel therapeutics provided by the

industry.

There is an increasing trend in the

industry to monitor (possibly multiple)

metabolites, as well as a push toward using

HPLC–MS-MS for the analysis of large

molecules, including peptides and proteins.

As the industry shifts toward the analysis

of more-complicated therapeutics, there is

a need to increase efficiency and productiv-

ity wherever possible. With that in mind,

when developing a new HPLC–MS-MS

method for a novel molecule, every tool

in the chromatographic arsenal should be

used to grant the best chance of success.

Perhaps the strongest, most versatile tool in

the bioanalytical setting is the LC column.

A large reason that method development

can be performed with the amount of effi-

O


ciency necessary to function as a CRO in

today’s bioanalytical world is the develop-

ment of column technology over the past

few decades. The reliable repeatability of

columns on the market today, combined

with the plethora of unique column types

that can be implemented, allow for the effi-

cient development of an HPLC–MS-MS

method for high-throughput analysis.

Because all bioanalytical work depends

on high-throughput analysis, many of the

trends in emerging technologies in the

bioanalytical market are directly related to

increasing on-instrument productivity and

reducing costs. This includes smaller par-

ticle size in columns coupled with ultrahigh

pressure liquid chromatography (UHPLC),

superficially porous shell column technol-

ogy, and microflow HPLC. This article

presents a quick background into the details

of developing an HPLC–MS-MS method

from the perspective of a CRO in relation

to column choice. It also focuses on recent

column technologies, the instrumentation

surrounding them, and their benefits in a

CRO environment.

Method Development

High-throughput bioanalysis CROs are usu-

ally a fast-paced environment, where it is nec-

essary to create a productive, rugged method

from the ground up for what is often times

an unknown novel therapeutic. A large part

of a CRO’s efficiency stems from its ability

to quickly develop a rugged method that

will repeatedly hold up to rigorous indus-

try and regulatory standards. As efficiency

can often be derived from simplicity, when

developing a new method the simplest solu-

tion is always the first approach. This is why,

despite the plethora of columns available for

use, it is almost always best to start with a

C18 or C8 column. One of the most versatile

and widely used columns, the C18 column

has been in use in one form or another for

decades. Comprising a simple octadecyl

carbon chain bonded silica-based stationary

phase, the C18 column is the go-to column

of choice for a large majority of molecules

analyzed by HPLC–MS-MS. C18 columns

have proven to provide good retention and

resolution for a vast array of small molecules.

With a proven track record of negligible

lot-to-lot and column-to-column variabil-

ity, there is minimal concern of anomalous

behavior throughout the life of a method

on a C18. C18 columns also tend to be very

rugged, with the average lifespan lasting for

upwards of thousands of injections. This is

a very important point in the development

of any method; if a seemingly scientifically

sound method has been developed, but the

column only lasts a few hundred injections

before peak deterioration, then the method

probably isn’t rugged or productive enough

to be feasible. A large benefit in the 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 s

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