Quantitation of Genetox Impurities Using a Surrogate Standard Approach

doi:10.4236/jasmi.2013.33021

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Journal of Analytical Sciences, Methods and Instrumentation, 2013, 3, 167-172

http://dx.doi.org/10.4236/jasmi.2013.33021 Published Online September 2013 (http://www.scirp.org/journal/jasmi)

167

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.

Email: [email protected]

Received August 20th, 2013; revised September 18th, 2013; accepted September 24th, 2013

tion License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work

is properly cited.

ABSTRACT

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

report.

Quantitation of Genetox Impurities Using a Surrogate Standard Approach

168

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

Chemstation.

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

8.7)/acetonitrile.

2.5. Calculation of Relative Response Factors

 



RF analyte

Relative Response Factors RRFRF surrogate

 (1)

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

Standard

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,

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-

p-toluidine

dimethyl-

m-toluidine

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-

p-toluidine

dimethyl-

m-toluidine

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

(a)

(b)

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-

sis.

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.

Quantitation of Genetox Impurities Using a Surrogate Standard Approach

170

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.

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