David A. Weil*, Zoltan Timar and Michael Zumwalt. Agilent Technologies. Schaumburg, IL/ Boulder, CO. Impurity Profiling 2008
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1 Evaluation of the Importance of Accurate Mass, Mass Resolution and Dynamic Range for Impurity Profiling Applications with Multistage Mass Spectrometry David A. Weil*, Zoltan Timar and Michael Zumwalt Agilent Technologies Schaumburg, IL/ Boulder, C David_Weil@Agilent.com Page 1
2 Impurity Profiling.. Identification of Impurities in Active Pharmaceutical Ingredients (API) Arising from Manufacturing/Processing Differentiation from other Pharma Applications Chromatography, Quantitation, Identification Source of Impurities Residual Solvents, Intermediates, Catalysts, Processing Aids Techniques GC/MS, LC/UV, ICP/MS, LC/MS and LC/MS/MS Page 2
3 Traditional Method for Impurity Analysis Plant is Shutdown Product has Failed.. Why, When, Where, How Easy.. Just have Ph.D. Analytical Chemists Acquire Lots and Lot of GCMS and LCMS Data Dump data onto Coworkers Desk ID the Differences.. Manual, Biased Approach Look for Known Things First High/Low Major Differences Is the Change Real? Although Small a Needle in Hay Can Cause ne Pain Manually Compare LC/UV and MS Chromatograms from Control versus Contaminated Samples Page 3
4 API Degradation by Aging Pathways Hydrolysis, xidation, Dehydration, Ring Cleavage, Photolysis Challenge Identify low-level degradation products in the presence of the major API component Dream Solution All Components ID and Separated Chromatography Infinite Resolving Power and Ultra Fast Separation Mass Spec Infinite Scan Speed, Dynamic Range, Resolving Power with sub-ppm Mass Accuracy Reality: Coalition, ion suppression, limited dynamic range, accurate mass New Analog/Digital Technology Evaluate the Importance of Resolution, Accurate Mass, Dynamic Range with Automated Data Mining Tools for Impurity Profiling Page 4
5 Impurity Profiling Workflow: bjective: Detection - ID low-level Impurities in Active Pharmaceutical Ingredients. Targeted Analysis QQQ MRM Quantitation or Unknown ID Differential Analysis Impurity ID RRLC Q(TF) Control/Sample (3x) RT, MW, Formulas ID Compounds Mass Hunter MFE (databases) Mass Profiler ID RT, MW Unique Features ID Structures AutoMSMS EFG MS - MSMS Import Targeted MS/MS List RRLC MS/MS Page 5
6 Sensitivity versus Unknown Identification Ease of Use Scan speed Scan sensitivity Qualitative (identification, structural info) Sensitivity (specific detection) Quantitation (accuracy, precision) Better Single quad TF TF Q-TF (MS/MS w/ accurate mass) QQQ esp. dirty matrix, < 5 pg on-col. QQQ TF Q-TF Q-TF TF unknowns (acc. mass CID) Single quad (SIM) Single quad QQQ Single quad Single quad QQQ (MS/MS) TF (accurate mass EICs) TF Q-TF QQQ QQQ Single quad (CID) Q-TF * Q-TF * Page 6
7 Agilent LC/MS/MS Solution 1200 RRLC 6520 QTF Accurate Mass time-of-flight analyzer quadrupole collision cell Q-TF Analyzer Ion ptics Page 7
8 New Ultra High Speed Acquisition Intelligence at the Molecular Level 4 GHz (8 bit) Analog-Digital-Converter ADC Adapted from Agilent High Speed scilloscope Systems Ultra High Speed FPGA Processors and Memory 4Ghz peak detection 4Ghz gain scaling Up to 20,000 m/z depth Dual Input / Dual Gain High Bandwidth Input Amplifier for Extended Dynamic Range Picture of 4GHz board Goes here FPGAs Dual Input Amplifier 4 GHz ADC Page 8
9 Enhancements in Time-of-Flight and QTF New Acquisition Technology Increasing Resolving Power H Butyl paraben [M+H] Methyl 5-acetylsalicylate [M+H] H 8 bit 14 GHz Analog Digital Converter Transient Peak Apex Picking ppm ppm Da 14,000 6,100 8,000 Resolving Power (FWHM) FIA, 2 scans/sec (6713 transients/scan) 2 IRM averaged over five scans Counts vs. Mass-to-Charge (m/z) Page 9
10 Enhanced Resolving Power Improved Mass Accuracy for Isobars Previous 1 GHz Sampling MAS 2.9 ppm (MAS) at high level, poor accuracy when BP abundance increases 128:1 dilution BP (unresolved, not detected at low levels) +1.3 ppm 1:1 MAS -0.2 ppm 128:1 dilution New 4 GHz Sampling -0.8 ppm 1:1 dilution BP Scan (# 3-7, 5 scans) MAS_BP_1_128.d Zoom view 128:1 dilution -1.4 ppm BP Counts (%) vs. Mass-to-Charge (m/ z) Counts vs. Mass-to-Charge (m/z) H Methyl 5-acetyl-salicylate (MAS) [M+H] H Counts (%) vs. Mass-to-Charge (m/z) Butyl paraben (BP) [M+H] Page 10
11 Extended Dynamic Range Mode Hardware (32 staggered ADCs) Real Time Signal Processing and Summing Memory SIGNAL Frontend_A Frontend_B Dual Gain Front End Amplifilers Agilent TALN ADC 4GSPS 8-BIT CLCK 4GSPS BUS 2GSPS BUS FPGA Master FPGA Slave PULSE CNTRL BUS DATA T INSTRUMENT CNTRLLER Page 11
12 Extended Dynamic Range Mode 12X Time Data from low gain channel Time signal Time Final spectrum gain transition Time Data from high gain channel Page 12
13 Extended Dynamic Range Up To 5 Decades f In-Spectrum Dynamic Range Max Abd 3.6x10 7 x Scan (# 31-35, 5 scans) niacinamide_erythromycin.d * x10 6 cts Niacinamide, 10 ng/µl [M+H] + = m/z Error = +0.8 ppm In-Scan Dynamic Range This Example 9x10 6 / 250 = Maximum 3.6x10 7 / 250 = 1.4x cts Counts vs. Mass-to-Charge (m/ z) x Scan (# 31-35, 5 scans) niacinamide_erythromycin.d Erythromycin, 500 fg/µl [M+H] + = m/z Error = +0.6 ppm Counts vs. Mass-to-Charge (m/ z) Page 13
14 Mass Accuracy Function of Acquisition State High Res -0.1ppm -0.53ppm 0.94 ppm -0.31ppm -0.31ppm -1,01ppm 1.74 ppm -0.03ppm Extended DR Page 14
15 Resolution Comparison High Resolution Mode 15K Resolution 0.98 ppm Extended Dynamic Range 8.5K Resolution 0.99 ppm 12K Resolution 0.09 ppm 8.5K Resolution ppm Page 15
16 Application of Enhanced Resolving Power C 9 H 10 N Product from Albuterol from C 10 H 13 N [C 9 H 11 N] + [C 10 H 14 N] + [C 9 H 11 N] + Page 16
17 Automated Data Analysis Show me the Data Find Compounds from Background MFE Algorithm Differential Analysis Mass Profiler Software Identification: Molecular Formula Generation, Databases Automation: MetID for Impurity Profiling Page 17
18 Molecular Feature Extraction (MFE) Automated Data Reduction Software Finds Features in TF/QTF Data 3D 3D Plot Plot Before No Coeluting Features Background riginal TIC Processed TIC Data Reduced sum intensities of isotopes, adducts, clusters and multiply charges ions together. Page 18
19 Molecular Feature Extraction (MFE) Generate Empirical Formulas Molecular Formula Generation and Database Search Page 19
20 Prednisolone: C 21 H H CH 3 CHH 3 CH 3 2 year old Suspension Page 20
21 Sequential Neutral Water Losses Detected x ECC Scan Prednisolone0002.d Counts vs. Acquisition Time (min) Page 21
22 12 Potential Degradation Products in Prenisolone CH 2 Loss -H 2, -H 2, -C 2 H 2, +H 2, +CH 4 +H 2 -, Page 22
23 Prednisolone 342 CH 3 H 358 CH 3 CHH 3 H CH CHH H 3 CH 3 CH H CH H 3 CH 3 CH CH 3 H 374 H CH 3 CH H 3 H CH 3 CH 3 Page 23
24 Is 6-methyl Prednisolone Present? [M+H]+ 375 Page 24
25 C 16 H 19 N 3 S 5 Degradation Products of Amoxicillin and AmoxClavin MW NH 2 Source Tablet 875mg New Tablet 500mg 09/07 Sample Preparation H NH N S H CH 3 CH 3 Tablets Dissolved in 40mL Methanol Water with 0.1% Formic Acid Syndicated 20 minutes Spin 5 minutes RPM Dilute 100 and 1000 fold with water Page 25
26 Experimental Conditions Chromatography Agilent 1200 RRLC Ecilpse Plus C18 2.1x100mm 1.8µm heated to 50 o C Mobile Phase: Water/Methanol 0.1% FA Water/Methanol 5mM NH4Ac Multiple Gradients Tested 0 to 95% in 16 Minutes 0 to 95% in 13 Minutes Flow Rate: µl/min Mass Spectrometry Agilent 6520 QTF Positive ion ESI Mass Range m/z Acquisition Rate: 2 spectra/s Drying Gas: 250 o C Internal Reference Mass m/z 121 and 922 Fragmenter: 165C Enhanced and High Resolution Modes Page 26
27 Buffer in Mobile Phase 10X Enhancement with NH 4 Acetate 0.1% Formic Acid 5mM NH 4 Acetate Page 27
28 Effect of Gradient 14 Separated Degradation Products 0-95% in 13 minutes 10 Separated Degradation Products 0-25% in 13 minutes Page 28
29 Degradation Pathway of Amoxicillin (previous TF/Trap work) H H H H CH H CH NH NH 2 N CH 3 H 2 NH CH NH 3 H 2 NH NH S CH 3 S CH 3 H H H H H H NH H NH S H CH CH 3 CH 3 H H N H 2 H H CH NH H N CH 3 NH S CH 3 H H H 5 4 H N N H HN H S CH CH 3 CH 3 1 Amoxicillin 2 Amoxicillin penicilloic acid 3 Amoxicillin penilloic acid 4 Diketopiperazine amoxicillin 5 4-Hydroxyphenylglyl amoxicillin E. Naegele, R. Moritt, J. Am. Soc. Mass Spectrom. 2005, 16, Page 29
30 Accurate Mass: High Resolution Mode RT [min] Compound name Formula Calculated mass Measured Mass Mass accuracy accuracy Mass [mda] [ppm] 3.71 amoxicillin penicilloic acid 2 C 16 H 22 N 3 6 S amoxicillin 1 C 16 H 20 N 3 5 S amoxicillin penilloic acid I and II 3 C 15 H 22 N 3 4 S Amoxicillin Acid C 17 H 23 N 3 S diketopiperazine amoxicillin 5 C 16 H 20 N 3 5 S Page 30
31 Structural Information from MS/MS C 16 H 19 N 3 S 5 H H NH 2 NH H H N S H CH CH 3 CH 3 H N N H HN H S CH CH 3 CH 3 H C 6 H 10 N 2 S 3.53 ppm Error Page 31
32 Differential Analysis Using Mass Profiler Page 32
33 Impurity Analysis: Mass Profiling Software Processed Processed TIC Processed TIC Group TIC A (Impure) Processed Processed TIC Processed TIC Group B TIC (Control) Aligns Data RT, Mass, Abundance What s Changed? Mass/RT >2 Fold Change What s All Unique!! Data RT/Mass Impurity Control Page 33
34 S/N 5:1, RI > 0.01%, Mass , RT 1-11 Minutes 835 Features Page 34
35 36 Features after Filtering Isotope Pattern, Background Subtraction, # Ions Page 35
36 Detected 17 Degradation Products Page 36
37 Composition and Database Searching Page 37
38 MetID Software For Impurity Profiling Page 38
39 verview MetID 1. Parent Compound: MW, Formula and Structure 2. Transformations: List Proposed Degradation Products 3. Identification Criteria: Vary Importance of Tests 4. Find Compounds by MFE: Molecular Feature Extraction 5. Find Compounds by AutoMSMS: For MSMS data 6. Sample Comparison: Mass Profiler What is Different 7. Isotope Pattern Filtering: Best for Halogenated Species 8. Mass Defect Filtering: From Proposed Compounds 9. EIC Generation: Confirms Presence of Compounds Page 39
40 Page 40
41 Method Input Parent Compound Propose Degradation Products Page 41
42 Proposed Degradation Products Qualified by Mass Defect and Isotope Pattern Let s Determine Composition of MW 411 Page 42
43 Accurate Mass Generates Composition Acid Hydrolysis (H 2 +C 2 H-H) Accurate Mass of Fragments Ions Page 43
44 verlay MSMS Spectrum Parent/Product Page 44
45 MSMS of MW 380 Compound Page 45
46 3D of MSMS Spectra Fragmentation Pattern Page 46
47 Summary: 1. New 4GHz A/D Electronics, Resolution > 10,000: m/z > 100, Which Enables Resolving Trace Level Degradation Products from Chemical Background 2. Automated Data Analysis: Molecular Feature Extraction 3. Differential Analysis: MassProfiler 4. Identification: Personal Metlin Database 5. Impurity Profiling: MetID Software with MS/MS Data Page 47
48 Acknowledgements Edgar Naegele Agilent Technologies, Germany Lehmann Horst Agilent Technologies, Germany Patrick Perkins Agilent Technologies, Santa Clara CA Mike Woodman Agilent Technologies, Schaumburg, IL Dawn Kasper, RDH Buffalo Grove, IL Thank you.. Kentucky Fried Chicken Boulder, C.. For being open at 10:50pm. Thank you.. For your Attention.. Page 48
49 References: J. Roy, AAPS PharmSciTech, 2002, 3,(2) L. Zhou, B. Mao, R. Reamer, T. Novak, Z. Ge, J Pharm. Biomed. Analysis, 44(2007) S. Erram; C. Fanska, M. Asif; J Pharm. Biomed. Analysis; 40(2006) Y. Wu; Biomed Chromatography; 14(2000) Page 49
50 Albuterol Sulfate/Levosalbutamol C 13 H 21 N 3 MW Sources H CH 3 CH 3 NH CH 3 Syrup 2MG/ML 10/26/99 Aerosol 90ug/dose New Suspension 0.65mg/3mL New Add reference article H H Page 50
51 Loratadine C 22 H 23 N 2 2 Cl MW Source Cl N Syrup 10mg/mL 05/02 Claritan D 07/02 N CH 3 Page 51
52 Naproxen C 14 H 14 3 MW Source Tablet 500mg 08/97 H CH 3 CH 3 Tablet 220mg New Page 52
53 Diphenoxylate Diphenoxylate C 30 H 32 N 2 2 MW H 3 C Atropine N C 17 H 23 N 3 ME Source Tablet 5/1994 CH 3 N N H Page 53
54 Hyosophen-Donnatal Phenobarbital C 12 H 12 N 2 3 MW Atropine C 17 H 23 N 3 MW Scopolamine C 17 H 21 N 4 MW Tablets 90mg 1/97 H H 3 C CH 3 N NH NH Page 54
55 Atarax Atarax H C 21 H 27 N 2 2 Cl MW Source Tablet 10mg 7/2002 N N Cl Page 55
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