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INTRODUCTION

The market of peptide-based drugs is growing due to the broad range of activity and low toxicity of peptides.1 Process impurities and product related impurities can affect the efficacy and safety of the drug.2,3 The International Council for Harmonisation (ICH) guidelines require impurities to be identified based on toxicity and dosage levels of new product.4 Optical thresholding based on LC-UV system is commonly used to determine the impurity levels. However, optical detection can only be applied to known or pre-characterized samples, which typically require a laborious process of fractionation, enrichment, and then analysis using mass spectrometry (MS)-based techniques for identification. Techniques that incorporate in-line orthogonal detection methods, such as MS, can overcome these challenges with improved productivity in the impurity profiling of synthetic peptides. The ACQUITY QDa mass detector is a cost-effective solution to add MS detection to LC-UV based workflows. The software ProMass developed by Novatia for MassLynx provides an automated processing method for MS data generated by QDa mass detector. This study is to demonstrate a high throughput and cost-effective LC-UV/MS workflow using MassLynx with ProMass for mass confirmation and impurity profiling of synthetic peptides using the ACQUITY QDa mass detector as an in-line orthogonal detector.

ADDING MASS DETECTION FOR IMPROVED PRODUCTIVITY AND CONFIDENCE IN THE ANALYSIS OF SYNTHETIC PEPTIDES Ximo Zhang, Brooke Koshel, Jing Fang, William Alley, Robert Birdsall and Yinq Qing Yu

Science Operations, Waters Corporation, Milford, MA

Figure 2. Optimized separation of synthetic peptide Eledoisin with orthogonal

detection system. A) UV detection at 215 nm. Using MassLynx integration tool, 11 impurity peaks were identified and annotated with their retention time and area. Peaks

above 0.2% area are labeled in blue, otherwise in red. B) MS detection by ACQUITY QDa mass detector.

Sample:

Eledoisin (1188.4 Da, pGlu-Pro-Ser-Lys-Asp-Ala-Phe-Ile-Gly-Leu-Met-

NH2). Mass load is 2 µg unless otherwise noted.

LC conditions:

LC system: ACQUITY UPLC H-Class Bio

Detectors: ACQUITY TUV detector, 5mm flow cell, λ = 215 nm

ACQUITY QDa mass detector (performance model) LC column: ACQUITY CSH C18, 1.7 µm, 130 Å, 2.1 × 100 mm

Column temp.: 60 °C Injection volume: 2 µL

Mobile phase A: H2O, 0.1% FA Mobile phase B: ACN, 0.1% FA

QDa setting:

References

1. Vlieghe, M., Lisowski, V., Martinez, J., Khrestchartisky, M. Synthetic therapeutic peptides: science and market. Drug Discovery Today. 2010, 15:40-56.

2. Sanz-Nebot, V., Toro, I., Barbosa, J. Fractionation and characterization of a crude peptide mixture for the synthesis of eledoisin by liquid chromatography-electrospray ionization mass spectrometry. Journal of Chromatography A. 1999, 846:25-38.

3. Zeng, K., Geerlof-Vidavisky, I., Gucinski, A., Jiang, X., Boyne, M. T. Liquid chomatorgraphy-high resolution mass spectrometry for peptide drug quality control. The AAPS Journal. 2015, 17:643-651.

4. Guidance for industry Q3B (R2) impurities in new drug products. 2006, Revision 2. 5. Birdsall, R., E., McCarthy, S., M. Increasing specificity and sensitivity in routine

peptide analyses using mass detection with the ACQUITY QDa detector. Waters Application Note. 2015 (p/n 720005377EN)

6. Birdsall, R., E., Yu, Y., Q. High-throughput screening of oligonucleotides for identity and purity assessment using the ACQUITY QDa detector and ProMass for MassLynx. Waters Application Note. 2016, (p/n 720005681EN)

RESULTS AND DISCUSSION

CONCLUSION

Automated workflow of synthetic peptide mass

confirmation and impurities profiling using the ACQUITY QDa mass detector with MassLynx and ProMass.

Successfully detect and identify impurities above

0.2% optical threshold for Eledoisin at 2 µg mass load.

Intuitive summary of percent purity by color coded

sample plates.

Summarize information of both target peptide and

impurities in ProMass deconvolution summary tables and deconvolution peak reports.

Allow high throughput batch processing to improve

the productivity of synthetic peptide impurity profiling in quality control environments.

Gradient table

Time

(min)

Flow

(min) %A %B

Initial 0.200 82.0 18.0

2.00 0.200 82.0 18.0

2.01 0.200 82.0 18.0

22.01 0.200 72.0 28.0

22.02 0.200 20.0 80.0

24.02 0.200 20.0 80.0

24.03 0.200 82.0 18.0

30.00 0.200 82.0 18.0

Mass range: 350-1250 m/z

Mode: ESI Positive Cone voltage: 10 V

Capillary voltage: 1.5 kV Software: MassLynx, ProMass

Interactive results

Mass load optimization

MassLynx Sample List for data processing Upstream characterization using UPLC-HRMS

Figure 1. An example of serine deletion impurity identified using UNIFI on

a XEVO G2-XS Qtof MS. LC-MS data were acquired via online UPLC-HRMS at optimal condition. Presented are the full MS (inset) and peptide

fragment from Collision Induced Fragmentation.

Customizable database of ProMass

Figure 5. An example of Sample List in MassLynx, which

contains the instrument methods for data acquisition and information needed for data deconvolution. Batch acquisition

and processing can be performed by selecting multiple runs in the Sample List. Zoom-in image shows the format for target

peptide mass calculation. ProMassBridge Parameter file is a connection between ProMass and MassLynx raw data, and

Znova Parameter file is for defining the parameters for deconvolution of MS spectra. Both files are customizable.

Figure 4. Znova Processing File,

which contains a customizable database. Naturally occurring amino

acids and selective impurities were already included in the database,

while entries in blue rectangle were manual ly added for target

identification and impurity profiling of Eledoisin.

Figure 6. Individual or batched processed sample results can be displayed in an

intuitive color-coded plate readout format for straightforward data interpretation. The summary table results page can be accessed though the embedded hyper

link for each vial position. Percent purity and target peptide are shown in these tables, along with the detected impurities. Information including ESI spectrum,

deconvoluted spectrum, and peak list report of individual peaks from each analysis can be accessed through an additional layer of hyperlinks. Resolved

peaks are annotated with the same format of numbers beside the retention time column in Chromatogram Summary table for a direct comparison with Figure 2.

Figure 3. Comparison of mass load at A) 0.1 µg, B) 2 µg, and C) 5 µg for synthetic

peptide separation. Purity was calculated and reported as area percent of target peptide relative to total peak area detected. A 2 µg mass load offered optimal chromatographic performance with respect to peak selectivity and detector response.

Identify impurities by UNIFI Data Processing

Collision Induced Fragmentation

for peptide impurity confirmation

Table 1. Impurities identified by UNIFI, including their retention time,

identity, m/z value, mass accuracy, intensity, and number of high energy MSE ions used for identification. Components were filtered by mass error

(5 ppm). X and Z stand for pyroglutamic acid and Methionine amide, respectively. The identified impurities will be monitored in the

QDa-ProMass workflow.

High Resolution Mass Spectrometry (HRMS) was used to characterize the impurity profile of eledoisin prior to implementation of the QDa based workflow for routine monitoring of process and product related impurities in the manufacturing of therapeutic peptides.

Routine monitoring of impurities with ACQUITY QDa

Eledoisin:

Therapeutic peptide for treatment of high blood

pressure and dry eyes.

HRMS conditions:

Instrument: XEVO G2-XS Qtof

m/z range: 300-1500 m/z Lockspray: Lgu-Fibrinopeptide (785.8421 (2+))

Mode: ESI positive, MSE sensitivity mode Low energy: 6 V Capillary voltage: 3.0 kV

High energy: 15-30 V Software: UNIFI 1.8

METHODS

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