Journal of Analytical Sciences, Methods and Instrumentation, 2013, 3, 167-172 Published Online September 2013 (
Quantitati on of Ge netox I m purities Using a Surrogate
Standard Approach
Heather Wang, Regina Nardi, Yuri Bereznitski, Roy Helmy, David J. Waterhouse
Analytical Chemistry, Merck Research Laboratories, Merck Sharp & Dohme Corp., Rahway, USA.
Received August 20th, 2013; revised September 18th, 2013; accepted September 24th, 2013
Copyright © 2013 Heather Wang et al. This is an open access article distributed under the Creative Commons Attribu-
tion License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work
is properly cited.
With the ever increasing complexity of active pharmaceutical ingredient (API) preparations, more potential genotoxic
impurities (PGI’s) are being observed. It is thus necessary to determine if these PGI’s are present in the final API’s, and
if they are present, to ensure the levels are acceptable for any clinical uses. For PGI’s that have authentic standards
available, quantitation can be accomplished in a straightforward manner. However, for PGI’s that are expected to form
through rearrangements or side reactions, authentic standards may not be readily available, significantly complicating
the analysis. In this study we describe a surrogate standard approach for quantifying PGI’s that allows for relative re-
sponse factor calculations of PGI species utilizing both gas chromatography-mass spectrometry (GC-MS) and liquid
chromatography-mass spectrometry (LC-MS).
Keywords: Potential Genotoxic Impurity (PGI); Active Pharmaceutical Ingredient (API); Mass Spectrometry;
Surrogate Standard; Analyte; Relative Response Factor (RRF)
1. Introduction
Identification and control of genotoxic and potential
genotoxic impurities (PGI’s) in active pharmaceutical
ingredients (API’s) is of utmost importance to ensure
patient safety. The allowable levels of PGI’s are deter-
mined by a staged Toxicologic Threshold of Concern
(TTC) based on both the dose and duration of the in-
tended clinical study [1-3]. This allowable amount can be
in the low ppm range, which is much lower than the al-
lowable levels of non-PGI impurities controlled under
guideline ICH Q3a [4]. Therefore, analytical detection
and quantification of these low level PGI impurities can
be problematic when utilizing only conventional analyti-
cal tools such as HPLC with UV detection [5].
Once the synthetic process for the API preparation is
finalized, an assessment is undertaken to evaluate the
potential for genotoxic intermediates or reagents to per-
sist, the potential for genotoxic impurities to form as
by-products during the process, and the appropriate con-
trol limits for any alerting structures identified [6]. For
PGI’s that are reaction intermediates, reaction by-prod-
ucts, and for which standards are readily available, con-
ventional analytical detection and quantitation methods
typically allow for a relatively straightforward analysis.
However, the problem of PGI quantitation becomes sig-
nificantly more complex when dealing with suspected
theoretical PGI’s that could possibly be formed from
synthetic rearrangements, byproducts, compound de-
composition, etc. No authentic standards typically exist
for these PGI’s, and synthetic preparation may not be
feasible owing to inherent instability, synthetic complex-
ity, or matrix effects. These “PGIs without standards”
present the ultimate challenge for an analytical chemist,
since without authentic standards, accurate quantitation is
extremely difficult. In order to address this issue the cur-
rent study focuses on the use of surrogate standards with
MS detection as an alternative analytical strategy to de-
termine the relative amounts of PGI’s without authentic
standards. In order for this strategy to be effective, it is
essential to choose a surrogate standard that will afford a
similar detector response to the compound of interest. If
the surrogate does not ionize in a similar manner, then
the indirect quantitation of the PGI could be far from
accurate. Dealing with these factors is the focus of this
Copyright © 2013 SciRes. JASMI
Quantitation of Genetox Impurities Using a Surrogate Standard Approach
2. Materials and Methods of Use
2.1. Instrumentation and Analytical Conditions
The LC-MS system was comprised of a single quadru-
pole MS-9 Agilent (Palo Alto, CA) 1100 Series LC/MSD
equipped with an APCI source run utilizing Single Ion
Monitoring, an Agilent 1100 Series autosampler and di-
ode array. Three mobile phase conditions were used for
the study, Method 1: A/B 0.1% formic acid/acetonitrile
using gradient elution starting at 90% A to 5% A over 18
minutes and then held for 2 minutes at 5% A; Method 2:
A/B 0.1% formic acid/acetonitrile using gradient elution
starting at 95% A to 5% A over 18 minutes and then held
for 2 minutes at 5% A; Method 3: A/B 10 mM ammo-
nium acetate (pH 8.7)/acetonitrile using gradient elution
starting at 90% A to 5% A over 18 minutes and then held
for 2 minutes at 5% A. Methods 1 and 2 were used for
positive ion detection; Method 3 was used for negative
ion detection. The flow rate was 1.0 ml/min, the injection
volume was 10 µl, while the autosampler was kept at
ambient conditions throughout. All separations were ac-
complished using a Waters (Billerica, MA) XBridge C18
(4.6 × 150 mm, 3.5 µm) column. The MS conditions
were as follows: Drying gas flow 12 ml/min; nebulizer
pressure 60 psi; drying gas temperature 350˚C; vaporizer
temperature 400˚C; capillary voltage 4000 V; and corona
current 10 µA. The scans used were the full scan from 50
- 300 m/z and the fragmenter set at 80 V, while for SIM
the fragmenter was set to 120 V.
The GC-MS system was comprised of a single quad-
rupole (Agilent 5973 Network Mass-Selective Detector)
and an Agilent 6850 Series GC system and autosampler.
All separations were accomplished using a Restek (Belle-
fonte, PA) RX1-6245SIL MS column (20.0 m × 180 µm
× 1.00 µm) under the following gradient conditions; Ini-
tial: 70˚C for 3 min, increase 30˚C /min to 250 ˚C then
held for 10 min. The flow was 1.3 ml/min and the injec-
tion volume was 1 µl. Total Ion Monitoring was utilized
for all runs.
2.2. Data Analysis
All peaks were reviewed and integrated manually when
necessary. All data analysis was performed using Agilent
2.3. Chemicals
All surrogates and analytes tested were purchased from
Sigma Aldrich (Madison, WI) except for 3-ethoxy-2-
nitropyridine, 2-chloronicotinoyl chloride, 3-hydroxy-6-
methyl-2-nitropyridine, 3-hydroxy-2-nitropyridine, 3-
methylbenzyl chloride, 6-methylquinoline, 3,5-dimethyl-
benzyl bromide, 3-methylbenzyl bromide, 2-amino-6-
methylbenzoic acid, and 2-amino-3-methylbenzoic acid,
which were purchased from Alfa Aesar (Ward Hill, MA).
All solvents were HPLC-grade and purchased from
Fisher Scientific (Pittsburgh, PA).
2.4. Sample Preparation
For all positive mode analysis samples were dissolved in
acetonitrile, while for all negative mode analysis samples
were dissolved in 90/10 10 mM ammonium acetate (pH
2.5. Calculation of Relative Response Factors
 
RF analyte
Relative Response Factors RRFRF surrogate
where the individual Response Factor (RF) of each
compound is calculated as:
MS peakarea
RF=analyte concentration (2)
Single Ion Monitoring (SIM) of the base peak utilized
when calculating peak areas.
3. Results and Discussion
In order to determine the feasibility of this surrogate
methodology we began the study utilizing surrogate
standard and analyte pairs as separate runs. Our reason-
ing for this was that we could establish what compounds
would serve as appropriate surrogate standards vs the
corresponding analytes without the complications of any
matrix effects.
3.1. Determination of a Suitable Surrogate
Initial attempts in choosing and detecting surrogate stan-
dards involved exploring the work of Oss et al. [7]. This
work involved directly infusing the organic compounds
of interest into an electrospray ionization system. The
authors’ purpose was to establish ionization efficiencies
of various species, thus this procedure worked well for
their application. However, due to the nature of the PGI’s
being at much lower levels then the API’s themselves, it
seemed that this infusion method used would not be fea-
sible for quantitation since no separation occurs, and thus
the ionization of the PGI could potentially be suppressed.
Therefore, as an alternate approach, LC-ESI-MS was
employed as a starting point. However, the LC-ESI-MS
method quickly led to difficulties when gradient elution
was employed. It was found that as the gradient condi-
tions and mobile phase composition changed, so did the
RF factors of the analytes of interest (Table 1). The ob-
served effect is most likely due to the ESI ionization
method itself, which involves ion formation on the sur-
face of a droplet while exiting a narrow-bore capillary,
Copyright © 2013 SciRes. JASMI
Quantitation of Genetox Impurities Using a Surrogate Standard Approach 169
Table 1. Comparison of the RRF of dimethyl-p-toluidine
and dimethyl-m-toluidine under various LC conditions util-
izing LC-ESI MS analysis.
Mobile Phase dimethyl-
0.1% TFA/acetonitrile 1.0 0.8
0.1% acetic acid/acetonitrile 1.0 0.6
0.1% formic acid/acetonitrile 1.0 1.7
5 mM ammonium acetate/acetonitrile1.0 1.1
and therefore it is expected to be very dependent upon
the solvent composition of the droplet [8-10].
In contrast the ionization mechanism of APCI is much
different than that of ESI. This ionization technique relies
on a corona discharge to supply the charge on the analyte,
and thus it hypothesized that use of this method would
aid in minimizing RF differences caused by variability of
mobile phase and gradient conditions [11]. In addition,
acceptable linearity utilizing this technique has been
demonstrated; therefore APCI LC-MS seemed to be the
logical choice for the present study [12]. A repeat of the
previously mentioned experiment confirmed APCI to be
a better ionization choice for our purposes and was thus
utilized in this study (Ta ble 2). Day-to-day reproducibil-
ity was also satisfactory as fresh samples were prepared
on three different days and the RRF results obtained were
consistent. In parallel, we also explored using GC-MS as
the separation and detection mode. The underlying as-
sumption was that since the EI ionization mode is rather
universal, the detection of similar surrogate standard/
analyte species could be accomplished.
As can be inferred from this study, the surrogate stan-
dards that have the closest relative response factors are
those having functionality similar to that of the PGI’s,
the best choice being isomers of the PGI’s themselves.
We have determined relative response factors of unity for
positional isomers using LC-APCI-MS (M + H for posi-
tive mode and M H for negative mode). If positional
isomers are not readily available other structures can be
used provided that the ionization mechanism of both is
carefully assessed. For instance, two species may seem
structurally similar, however if one of the species has
functionality that can readily fragment, or if it possess a
labile functional group, this can lead to significant over/
underestimation where PGI calculated values do not re-
flect the quantity of the PGI that is actually present in the
sample. An example of this involves the 2-chloronicoti-
noyl chloride/6-chloronicotinoyl chloride pair. When
both species were subjected to chromatography followed
by MS analysis the parent ions (m/z 176) were not ob-
served. This can be clearly seen in the total ion chroma-
togram (TIC) for both species (Figure 1).
Table 2. Comparison of the RRF of dimethyl-p-toluidine
and dimethyl-m-toluidine under various LC conditions util-
izing LC-APCI MS analysis.
Mobile Phase dimethyl-
0.1% TFA/acetonitrile 1.0 1.0
0.1% acetic acid/acetonitrile 1.0 1.0
0.1% formic acid/acetonitrile 1.0 1.2
5 mM ammonium acetate/acetonitrile 1.0 1.2
Figure 1. a) TIC of 2-chloronicotinoyl chloride; b) TIC of
6-chloronicotinoyl chloride.
The base peak detected was the carboxylic acid de-
rivative for both (m/z 157.6). When comparing the RRF
for this pair utilizing this base peak (see Table 3), the
value was 1.6 in the positive APCI mode. However, if
another species without the corresponding label aldehyde
functionality was used for the calculation, the value may
be very different depending on the ion chosen for analy-
The results of the surrogate standard/analyte RRF
study are shown in Tables 3 and 4. The species are sepa-
rated into two tables, one displaying isomers (Table 3)
and the other displaying surrogate/analyte species con-
taining similar functional groups but different formula
weights (FW’s) (Table 4). For the isomer pairs, the
RRF’s using APCI vary from 0.8 to 2.9, while the me-
thylquinoline pair RRF’s utilizing EI ionization were
unity. Greater variability was observed for the pairings
containing similar functional groups but different FW’s.
These values varied from 0.9 to 4.9 when using APCI
and from 0.9 to 1.4 for EI ionization.
Copyright © 2013 SciRes. JASMI
Quantitation of Genetox Impurities Using a Surrogate Standard Approach
Copyright © 2013 SciRes. JASMI
Table 3. Comparison of surrogate standard and analyte RRF values of structural isomers utilizing APCI (positive and nega-
tive) and EI modes.
Surrogate Analyte RRF Mode
dimethyl-p-toluidine dimethyl-m-toluidine 1.0 APCI/positive
2-chloro-3-pyridine carboxaldehyde 3-chloro-4-pyridine carboxaldehyde 1.5 APCI/positive
2-amino-6-methylbenzoic acid 2-amino-3-methylbenzoic acid 2.2 APCI/positive
4-chloromethyl benzoic acid 3-chloromethyl benzoic acid 0.8 APCI/negative
6-nitroquinoline 8-nitroquinoline 2.9 APCI/positive
6-chloronicotinoyl 2-chloronicotinoyl 1.6 APCI/positive
6-methylquinoline 8-methylquinoline 1.0 EI
Table 4. Comparison of surrogate standard and analyte RRF values of compounds containing similar functional groups util-
izing APCI (positive and negative) and EI modes.
Surrogate Analyte RRF Mode
3-methoxy-2-nitropyridine 3-ethoxy-2-nitropyridine 2.2 APCI/positive
8-methylquinoline 8-quinolin-N-oxide 0.9 APCI/positive
2-hydrazinopyridine 2-chloro-6-hydrazinopyridine 1.3 APCI/positive
2-(chloromethyl)pyridine hydrochloride 2-chloromethyl quinoline 1.3 APCI/positive
4-chloromethyl benzoic acid 4-nitrobenzoic acid 0.9 APCI/negative
3-hydroxy-2-nitropyridine 3-hydroxy-6-methyl-2-nitropyridine 4.9 APCI/positive
N-ethylcarbazol carbazol-9-ethanol 3.3 APCI/positive
benzyl chloride 2-methyl benzyl chloride 1.0 EI
benzyl chloride 3-methyl benzyl chloide 1.0 EI
2-chloropyrimidine 2-bromopyrimidine 1.3 EI
benzyl bromide alpha-bromo-p-xylene 1.0 EI
2-ethylthiophene 5-ethyl-2-thiophenecarboxaldehyde 0.9 EI
N,N-dimethylaniline dimethyl p-toluidine 1.2 EI and APCI/positive
benzyl bromide 3-methylbenzyl bromide 1.1 EI
benzyl bromide 3,5-dimethylbenzyl bromide 1.4 EI
3.2. Method Specificity and Utility
In addition to comparisons of RRF’s of pure compounds
in solutions, the comparison of compounds in the pres-
ence of API’s was undertaken. This was utilized to estab-
lish if the overwhelming excess of API in the sample
matrix vs the PGI/surrogate standard would lead to quan-
titative errors. In order to investigate this, quantities of
PGI’s were spiked into API’s known to contain none of
the PGI’s of interest, and the amounts obtained utilizing
the surrogate standard method were compared with the
actual amounts added. From the data shown (Table 5), it
was determined that satisfactory quantitation can be ob-
tained utilizing the surrogate standard method.
To further evaluate the API matrix effect, an API
which contained a known amount of a PGI (non spiked)
was analyzed to establish if the surrogate approach
would yield a value close to that actually determined
using the authentic standard. The API of interest con-
tained 78 ppm of the 3-methyl substituted indole (Figure
2) with indole-6-carboxylic acid employed as the surro-
gate standard for quantitation. The calculated value of the
3-methyl substituted indole in the API utilizing the RRF
method described was found to be 75 ppm. Therefore,
proof of concept for this methodology in an actual API
as been demonstrated. h
Quantitation of Genetox Impurities Using a Surrogate Standard Approach 171
Table 5. Comparison of known spiked amounts of PGI’s to those calculated utilizing the surrogate standard method (APCI
positive ion mode).
Surrogate Analyte Amount Spiked into API Amount Calculated in the API
N,N-dimethylaniline N,N-dimethyltoluidine 21 ppm 26 ppm
3-methoxy-2-nitro-pyridine 3-ethoxy-2-nitro-pyridine 19 ppm 26 ppm
(a) (b)
Figure 2. Structure of the PGI, substituted 3-methyl indole
(a) and the surrogate, indole-6-carboxylic acid (b).
4. Conclusions
An analytical method for quantitation of PGI’s in API’s
utilizing surrogate standards was developed and demon-
strated to ppm levels. This method can be utilized for
assessing the levels of PGI’s when authentic standards
are not readily available.
For small volatile PGI’s of similar structures, the
GC-MS-EI source gave good RRF agreement. Similarly,
when utilizing the LC-MS-APCI source in both the posi-
tive and negative modes surrogate standards can be also
successfully used provided that the species chosen for the
surrogate and analyte have similar functionalities, with
isomers of the actual PGI being the preferred compounds
of choice.
It should be also emphasized that the results obtained
using this methodology are based on calculation of rela-
tive response factors determined in a given system. The
RRF data obtained in the study indicate that there can be
significant variation in the amounts predicted depending
on the analytical method and surrogate standard chosen.
Therefore, the quantitive results obtained using the sur-
rogate methodology should only serve as an approxima-
tion of the PGI impurity present. Additionally, data for
this surrogate approach are useful in determining which
PGI’s need to be prepared as standards based on the rela-
tive amounts determined and the levels allowable using
the staged TTC guidelines.
5. Acknowledgements
The authors thank the Merck & Co. Inc., MRL Summer
Intern Program for their support.
[1] T. McGovern and D. Jacobson-Kram, “Regulation of
Genotoxic and Carcinogenic Impurities in Drug Sub-
stances and Products,” Trends in Analytical Chemistry,
Vol. 25, No. 8, 2006, pp. 790-795.
[2] V. Gangadhar, P. Saradhi and R. Rajavikram, “The De-
termination and Control of Genotoxic Impurities in
APIs,” Pharmceutical Technology, Vol. 35, 2011 pp. s24-
[3] L. Muller, R. J. Mauthe, C. M. Riley, M. M. Andino, D.
D. Antonis, C. Beels, J. De George, A. G. M. De Knaep,
D. Ellison, J. A. Fagerland, R. Frank, B. Fritschel, S. Gal-
loway, E. Harpur, C. D. N. Humfrey, A. S. Jacks, N.
Jagota, J. Mackinnon, G. Mohan, D. K. Ness, M. R.
O’Donovan, M. D. Smith, G. Vudathala and L. Yotti, “A
Rationale for Determining, Testing, and Controlling Spe-
cific Impurities in Pharmaceuticals That Posses Potential
For Genotoxicity,” Regulatory Toxicology and Pharma-
cology, Vol. 44, No. 3, 2006, pp. 198-211.
[4] “Guidance for Industry Q3A Impurities in New Drug
Substances,” ICH, 2008.
[5] P. Kushwaha, “Genotoxic Impurities in Pharmaceuticals,”, 2010.
[6] A. Teasdle, D. Elder, S.-J. Chang, S. Wang, R. Thompson,
N. Benz and I. H. Snaches Flores, “Risk Assessment of
Genotoxic Impurities in New Chemical Entities: Strate-
gies to Demonstrate Control,” Organic Process Research
& Development, Vol. 17, No. 2, 2013, pp. 221-230.
[7] M. Oss, A. Kruve, K. Herodes and I. Leito, “Electrospray
Ionization Efficiency Scale of Organic Compounds,”
Analytical Chemistry, Vol. 82, No. 7, 2010, pp. 2865-
[8] C. G. Enke, “A Predictive Model for Matrix and Analyte
Effects in Electrospray Ionization of Singly-Charged
Ionic Analytes,” Analytical Chemistry, Vol. 69, No. 23,
1997, pp. 4885-4893.
[9] P. Kebarle, “A Brief Overview of the Present Status of
the Mechanisms Involved in Electrospray Mass Spec-
trometry,” Journal of Mass Spectrometry, Vol. 35, No. 7,
2000, pp. 804-817.
[10] M. Yamashita and J. B. Fenn, “Electrospray Ion Source.
Copyright © 2013 SciRes. JASMI
Quantitation of Genetox Impurities Using a Surrogate Standard Approach
Another Variation on the Free-Jet Theme,” Journal of
Physical Chemistry, Vol. 88, No. 20, 1984, pp. 4451-
[11] D. I. Carroll, I. Dzidic, R. N. Stillwell, K. D. Haegele and
E. C. Horning, “Atmospheric Pressure Ionization Mass
Spectrometry: Corona Discharge Ion Source for Use in
Liquid Chromatograph-Mass Spectrometer-Computer
Analytical System,” Analytical Chemistry, Vol. 47, No.
14, 1975, pp. 2369-2373.
[12] J. F. Anacleto, L. Ramaley, F. M. Benoit, R. K. Boyd and
M. A. Quilliam, “Comparison of Liquid Chromatogra-
phy/Mass Spectrometry Interfaces for the Analysis of
Polycyclic Aromatic Compounds,” Analytical Chemistry,
Vol. 67, No. 22, 1995, pp. 4145-4154.
Copyright © 2013 SciRes. JASMI