Research to Routine Workflows for Large and Small Molecules using the Q Exactive HR/MS

Research to Routine Workflows for Large and Small Molecules using the Q Exactive HR/MS Sept. 22, 2011 Patrick Bennett Director Pharma Strategic Marketing Thermo Fisher Scientific

Agenda Definitions Research to Routine Small Vs. Large Molecule Physicochemical Types of instruments/technology and experiments Small molecule regulations vs Large molecule regulations Application of HR/MS Why HR/MS Q Exactive Proven Proteomic workflow tools applied to routine quantitation 2

Definitions Pharma traditional pharmaceutical company focused primarily on small molecule drug discovery, development and sales. May have large molecule components and includes CRO s. BioPharma can be same company as Pharma or a company that specifically focuses on biologics based therapeutic agents. Includes CRO s. Biologics complex, natural proteins, blood products, clotting factors, antibodies, mab, peptides, analogues, truncated forms, fusion proteins, non-protein macromolecules RNA/DNA, antisense RNA, aptamer s/oligonucleotides Large molecule biologics; based on molecular weight Small molecule traditional drugs; based on molecular weight. 3

4 RESEARCH TO ROUTINE

Biologics Development: Research to Routine Unregulated Range of traditional Proteomics experiments through to high throughput screening. Research focus, minor component interest, many analytes, same type of test. Internal based procedures rather than regulated SOP s Regulated Routine and Semi-Routine experiments supporting safety and efficacy studies. Few drugs, many samples, high expense GLP & GMP environment strict SOP s Research Discovery DMPK QC/QA Activities Traditional Proteomics, Protein-protein interactions Pathway analysis Activity, PD Biomarker dev. PTM Analysis Disulfide Mapping Protein Characterization Structural Analysis Immunogenicity Neutralization PK/PD, LBA s, Cell based assays, PTM Optimization, Protein Characterization, Safety, Efficacy, Metabolism, DDI PK/PD, CQA/QbD, Production Characterizations, Drug monitoring 5

Small vs Large Chemical Characteristics Characteristic Small Large Molecular Weight <800 >5000 Endogenous No Often Yes Solubility Hydrophobic Hydrophilic Purity Homogeneous Heterogeneous Immunogenic No Yes Conjugated Yes No Valence Monovalent Divalent Kinetics Fast Slow Detection Isotopic Activity/functional Stability Chemical/enzymatic Immunologic/enzymatic Metabolic interference Yes/knowledge Unknown Protein Binding Yes No 6

Small vs Large Analytical Methodology Characteristic Small Large Basis of Measurement Analyte Antigen-Ab reaction Detection Direct Indirect Reagents Common and available Unique, not commercial or available Analytes Small Small and macromolecule Sample Preparation Yes No Calibration Curves Linear Non-Linear Assay Environment Organic Aqueous Development Time Weeks Months Technology LC/MS (Affinity based Extraction) LBA: ELISA, RIA, ECL, Multiplexing Stability Drug Drug + Reagents Regulations Very defined and rigid Some flexibility 7

8 APPLICATION OF HR/MS

Specificity = Resolution + Mass Accuracy Resolution: 10k, 30k, 50k, 100k 100 90 80 70 Butyl-Phthalate, 279.15909 (ubiquitous background ion) 54 ppm apart Relative Abundance 60 50 40 30 Ethinyl-Estradiol, 279.17434 20 10 0 279.12 279.14 279.16 279.18 279.20 m/z 9

High Resolution Ensures Accurate Target Selection R: 35K R: 70K R: 140K 492.2634 492.2665 492.2495 492.2511 492.2661 30ppm m/z Accurate quantification is only possible when the target can be correctly identified. An interference which is 30 ppm apart from the target can be completely separated using high-resolution of 140,000 using the Q Exactive. 10

When does HR/MS make sense? Research phase Early to late discovery phases Pre-clinical phase QA/QC - characterization Ligand binding assay development Specificity testing Stability testing Assay troubleshooting, unexpected results Reagents unavailable, difficult to produce, expensive Bridging methods, reagents Biomarker research, multiple biomarkers 11

Research to Routine: Range of Experiments for LC/MS Qualitative Identification Confirmation Research Low throughput Discovery Development Medium throughput Verification Quantitative Routine High throughput Optimized assays Traditional Proteomics, Metabolomics, Metabolism, Biomarker Research Translational Research, Biopharma, Metabolomics, Metabolism Drug Discovery, Various Biomarker Pharma & Biopharma Quantitation, Leachables, Extractables, Impurities, QA/QC Orbitraps Q Exactive Triples All Q TOF All Q TOF Triples & Q Trap 12

Q Exactive TM Hardware Innovations S-Lens ion source Quadrupole mass filter Advanced signal processing 13

Specifications/Details Thermo Scientific HyperQuad mass filter Mass range: 50-4000 m/z Linear range: 4-5 orders of magnitude Variable precursor isolation width selection from 0.4 Da to full mass range Resolution : up to 140,000 17k, 35k, 70k, 140k at m/z 200 scan speed dependent on resolution setting Sources: ESI probe compatible with liquid flow rates of < 1 μl/min to 1 ml/min without splitting APCI source compatible with liquid flow rates of 50 μl/min to 2 ml/min without splitting Nanospray/microspray 14

What Do We Gain by Selected Ion Monitoring? In Full MS, total C-trap charge capacity is shared between multiple signals of different intensity Signal-to-noise ratio becomes dependent on the ratio of compound of interest to other analytes-much less so in SIM! In Orbitrap instruments, SIM could become MRM without any additional overhead! 100 80 60 40 20 0 100 80 60 40 20 0 195.0876 N=248402.81 195.0877 N=20741.58 Full MS S/N = 745 IT= 0.245 ms SIM (10amu) For the same target: S/N = 5400 IT= 1.321 ms NL: 1.94E8 [150.00-2000.00] Lowest signal 250330 NL: 1.12E8 [190.10-200.10] Lowest signal 28240 Gain in sensitivity (7x) 6000 Sensitivity gain 5 10 x with SIM mode The gain will be higher in more complex matrices S/N (spectrum) 5000 4000 3000 2000 1000 Caffeine 0 195.082 195.084 195.086 195.088 195.09 195.092 195.094 15 S/N (FMS) S/N (SIM10)

16 QUANTITATION

Traditional Workflow (Triple Quadrupoles) NCEs Tune MRM PP Sample Clean Up Bioanalysis PK Estimates (NCE only) LC-SRM Analysis Tuning MRM takes time & requires some level of expertise MRM methods are not easily transferable between platforms from different vendors, which makes scalability difficult. Peptides require determination of charge state and the optimal SRM transition, which is again platform dependent. Expertise required, even for a basic assay. Limits the number of transitions (duty cycle & no. of scans per analyte). Difficult to automate set-up to get sequence information expertise required. 17

HRMS Workflow (Q Exactive) NCEs PP Sample Clean Up Bioanalysis PK Estimates (NCE) PK Estimates Metabolites LC-HRMS No compound dependent tuning required easier to use/faster to set-up Post-acquisition data analysis Providing PK data as well as critical new information (metabolites, biomarkers) More value in terms of the Fail Fast paradigm Multiple Analytes (IS) Peptides Post-Acquisition Data Query 18

Quantitation Summary of Small Molecules on Q-Exactive Q Exactive Full Scan Compound LOQ Curve Fit Oxycodone 50 fg L - 1/X2 Paroxetine 100 fg Q - 1/X2 Ketoconazole 50 fg L - 1/X2 Clonazepam 500 fg Q - 1/X2 Verapamil 50 fg Q - 1/X2 Clopidogrel 50 fg L - 1/X2 Q Exactive Targeted-SIM LOQ Curve Fit 50 fg L - 1/X2 50 fg L - 1/X2 50 fg L - 1/X2 500 fg Q - 1/X2 50 fg L - 1/X2 50 fg L - 1/X2 Triple Quad Vantage (SRM) LOQ Curve Fit 50 fg L - 1/X2 50 fg L - 1/X2 1000 fg Q - 1/X2 100 fg L - 1/X2 10 fg Q - 1/X2 50 fg Q - 1/X2 Q-Exactive achieves similar quantitation performance of above compound mixture as Vantage 19

Uroguanylin in Glucagon Peptide Matrix (Full Scan) Q Exactive Test-003 #487-492 RT: 2.28-2.30 AV: 6 NL: 1.17E6 T: FTMS + p ESI Full ms [820.00-1700.00] 871.66876 100 95 90 85 80 75 70 65 Relative Abundance 60 55 50 45 40 891.16079 35 30 25 20 15 10 834.31346 [M+2H] 2+ 981.82791 1161.88527 1177.54283 [M+H] + 1667.61833 5 0 939.13037 1026.99763 1128.20213 1195.51589 1472.23880 1689.60049 1266.47914 1356.68300 1408.69556 1529.25853 1607.28170 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700 m/z 20

Uroguanylin Singly Charged Species Test-003 #487-492 RT: 2.28-2.30 AV: 6 NL: 1.32E5 T: FTMS + p ESI Full ms [820.00-1700.00] 100 95 90 85 1667.61833 R=25584 z=1 1668.62129 R=25350 z=1 Uroguanylin was quantified by summing the first 3 isotopes of both singly and doubly charged ions. 80 75 70 Relative Abundance 65 60 55 50 45 40 1669.62036 R=25986 z=1 35 30 1670.62126 R=26333 z=1 25 20 15 10 5 0 1671.62188 R=26133 z=1 1672.62227 R=25043 z=1 1673.62198 R=26044 z=1 1665 1666 1667 1668 1669 1670 1671 1672 1673 1674 1675 m/z 21

Uroguanylin Doubly Charged Species Test-003 #487-492 RT: 2.28-2.30 AV: 6 NL: 1.13E5 T: FTMS + p ESI Full ms [820.00-1700.00] 834.31346 R=36727 z=2 100 95 90 85 80 75 834.81445 R=35417 z=2 70 65 Relative Abundance 60 55 50 45 40 835.31439 R=36214 z=2 35 30 25 835.81451 R=36408 z=2 20 15 10 5 836.31443 R=35710 z=2 836.81542 R=32095 z=2 837.40331 R=33958 z=4 0 833.5 834.0 834.5 835.0 835.5 836.0 836.5 837.0 837.5 838.0 m/z 22

Q Exactive: 100 pg/ml to 10,000 pg/ml Uroguanylin in Glucagon Peptide Matrix (t-sim) R 2 =0.9977, Linear 1/x 2 400000000 380000000 360000000 340000000 Uroguanylin Y = -11732.2+366792*X R^2 = 0.9977 W: 1/X^2 Linear Dynamic Range 1 x 10(4) 320000000 300000000 Area 280000000 260000000 240000000 220000000 200000000 180000000 160000000 140000000 120000000 100000000 80000000 60000000 Area 2000000 1900000 1800000 1700000 1600000 1500000 1400000 1300000 1200000 1100000 1000000 900000 800000 700000 600000 500000 400000 300000 Uroguanylin Y = -11732.2+366792*X R^2 = 0.9977 W: 1/X^2 40000000 20000000 0 0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 ng/ml 0 100 200 300 400 500 600 700 800 900 1000 1100 ng/ml 200000 100000 23

Insulin Quantitation Results - Plasma Nominal Concentration (ng/ml) Replicate # Mean Calculated Concentration Stdev % CV 0.25 4 0.260 0.0300 11.5 0.5 4 0.434 0.0501 11.5 1 4 0.906 0.0540 5.96 2.5 4 2.81 0.0568 2.02 5 4 4.79 0.112 2.33 10 4 10.3 0.284 2.77 25 4 27.9 0.247 0.89 50 4 44.0 1.35 3.08 100 4 92.8 4.29 4.62 250 4 276 9.99 3.62 1000 4 979 36.7 3.75 24

Exendin Quantitation Results - Plasma Nominal Concentration (ng/ml) Replicate # Mean Calculated Concentration Stdev % CV 5 4 5.143 0.418 8.13 10 4 9.693 0.520 5.36 25 4 24.37 1.22 5.00 50 4 45.46 0.705 1.55 100 4 92.83 13.0 14.0 250 4 261.7 5.31 2.03 500 4 507.3 2.03 0.40 1000 4 966.0 25.2 2.61 2500 4 2675.6 60.7 2.27 5000 4 5205 169 3.24 10000 4 9740 150 1.54 25

GLP-1 Quantitation Results - Plasma Nominal Concentration (ng/ml) Replicate # Mean Calculated Concentration Stdev % CV 0.1 4 0.099 0.0098 9.91 0.25 4 0.251 0.0205 8.16 0.5 4 0.534 0.0337 6.31 1 4 0.905 0.0226 2.50 2.5 4 2.69 0.0578 2.15 5 4 5.36 0.126 2.36 10 4 9.99 0.120 1.20 25 4 26.6 0.664 2.50 250 4 50.6 0.562 1.11 100 4 80 0.692 0.86 250 4 243 14.2 5.86 500 4 462 15.5 3.35 1000 4 860 7.90 0.92 5000 4 5383 62.8 1.17 10000 4 9796 164 1.67 26

PROTEOMICS RESEARCH TO ROUTINE 27

Workflow Steps Define the Experiment Identify the protein sequence under study Selection of Peptides Literature search, in silico digestion, BLAST searchers to ensure sequence specificity WRT to the background matrix Selection of Targeted m/z values Sensitivity based on intense fragmentation, selectivity WRT background Verification of Targeted m/z values Comparison of experimental LC-MS and MS/MS parameters to references (incorporation of recombinant protein analysis and/or heavy labeled synthetic peptides Optimization of Targeted m/z values Keeping only the best peptides/product ions, collision energies, scheduled time windows 28

Workflow for Targeted Protein Quantitation Development Sample Preparation Mass Spectrometry Data Processing MS Heavy Labeled Protein Protein(s) Digest 1. Ionization (electrospray) 2. MS (full spectra) m/z Quantification Heavy Labeled Peptides PRTC Kit 3. MS Pre-cursor selection 4. Fragmentation (CID, HCD, ETD) Separation HPLC 5. MSn (Product Ion spectra) Reference Database Intensity [counts] MS/MS 4000 3000 y?? 749.47 y?? 877.53 Peptide sequence verification Time 2000 1000 0 [M+2H]²?-H?O, [M+2H]²?-NH? 553.27 y?²? 439.35 y?? y?²?-h?o, y?²?-nh? 476.34 430.38 y?? b?? 662.37 247.07 b?? y??-nh? y?? 648.28 860.53 b?? 290.27 949.42 y?? 1024.58 m/z 200 300 400 500 600 700 800 900 1000 1100 29 Domon and Aebersold Nature Biotechnology 2010, 7(28), 710-721

Target Verification Using Heavy Labeled Peptides Relative Abundance Relative Abundance NL: 1.71E5 100 90 80 70 60 50 40 30 20 10 0 100 NL: 5.33E6 90 80 70 60 50 40 30 20 10 0 4 6 8 LC 20.79 VFQSWWDR m/z 562.284 20.79 VFQSWWDR m/z 567.2720 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 Time (min) Relative Abundance MS VFQSWWDR 561 562 MS/MS VFQSWWDR VFQSWWDR 562.2684 562.7704 VFQSWWDR 567.2720 567.7727 568.2739 568.7753 563 564 565 566 567 568 569 570 571 572 573 m/z 476.22 430.39 553.21 749.45 877.46 247.12 544.29 662.33 219.15 290.14 375.18 512.81 648.37 860.61 949.36 558.52 759.33 887.38 486.35 444.33 435.22 672.40 247.09 219.12 300.17 375.19 517.79 648.31 870.44 200 300 400 500 600 700 800 900 1000 30

31 HeavyPeptide TM AQUA TM Standards

HeavyPeptide TM AQUA TM Benefits HeavyPeptide AQUA products enable absolute quantification of all proteins in a sample. The HeavyPeptide AQUA kits can now be prepared with covalent modifications, such as phosphorylation, which are chemically identical to naturally occurring post-translational modifications (PTMs). As a result, the HeavyPeptide AQUA kits are an extremely cost-effective solution, enabling researchers to identify and quantify peptides of interest much faster, with significantly increased precision. This answers the need for relative and absolute quantification of the expression levels for all proteins in complex samples. This is essential since PTMs significantly increase the size of proteomes over their corresponding genomes. The HeavyPeptide AQUA product range produces a clear and consistent gain in efficiency, transparency and reproducibility of experiments. 32

Extracted from: C:\Scott Peterman\Backup\Marketing_Monthly_Updates\2011_Marketing_Plan\Thermo_Instruments\Seed_Unit_Requests\Amgen\Control_trainer_180grad_inj1.raw #6273 RT: 88.55 ITMS, CID, z=+2, Mono m/z=872.43262 Da, MH+=1743.85796 Da, Match Tol.=0.8 Da 100 80 60 40 20 0 b₃+ 306.13 y₂+ 333.30 y₅+ 687.38 y₆+ 788.43 Extracted from: C:\Scott Peterman\Backup\Marketing_Monthly_Updates\2011_Marketing_Plan\Thermo_Instruments\Seed_Unit_Requests\Amgen\Control_trainer_180grad_inj1.raw #2982 RT: 41.53 ITMS, CID, z=+1, Mono m/z=1712.74365 Da, MH+=1712.74365 Da, Match Tol.=0.8 Da y₈+ 988.54 30 [M+1H]+-H₂O 1694.69 b₁₀+-h₂o y₁₂²+ 1039.54 720.39 b₁₃+ y₇+ b₉+-h₂o25 y₉+ 1411.69 b₁₄+ y₃+-nh₃ b₅+-h₂o b₇+ b₈+ 901.54 938.52 1101.60 b₁₄+-nh₃, y₁₄+ 1566.60 444.35 462.23 y₁₀+ 756.43 1580.73 y₃+ y₁₁²+-h₂o, y₁₁²+-nh₃ 843.46 1264.62 y₁₁+ 20 y₁₂+ b₁₄+ 461.28 667.34 1351.66 Extracted from: C:\Scott Peterman\Backup\Marketing_Monthly_Updates\2011_Marketing_Plan\Thermo_Instruments\Seed_Unit_Requests\Amgen\Control_trainer_180grad_inj1.raw #4001 RT: 55.85 1438.74ITMS, CID, z=+2, Mono 1597.76 m/z=525.29041 b₉+ Da, MH+=1049.57353 Da, Match Tol.=0.8 Da 1093.47 90 b₁₃+-h₂o 400 600 800 15 1000 1200 1400 1600 1419.59 y₆+ m/z 710.39 80 b₈+ 964.44 y₇+ 10 70 b₁₁+ b₆+ y₉+ b₁₀+ 823.48 a₇+-nh₃ 1237.40 b₁₂+-h₂o 726.32 987.59 1150.41 b₅+ 782.24 y₈+ b₈+-h₂o b₉+-h₂o b₁₁+-h₂o 1320.52 b₁₄+-h₂o 60 1075.47 627.40 y₇+ 886.46 946.40 1219.45 1548.63 5 y₁₃+ y₁₂+ b₇+-h₂o y₆+ 749.40 50 1462.69 1375.65 [M+2H]²+ y₅+ 809.40 620.40 y₇²+ 525.22 547.22 412.34 40 0 b₂+ 600 800 1000 227.16 1200 1400 1600 30 m/z 20 10 0 a₃+-nh₃ 295.32 b₃+ 340.31 y₃+ 376.26 b₄+ 503.28 b₅+ 560.39 200 300 400 500 600 700 800 900 1000 m/z Experimental Purified Protein Stock Solution Treatment Digestion PRTC Kit Control H 2 O 2 treated (40 hrs) ph 8.0 treated (40 hrs) Intensity [counts] (10^3) 100 80 60 40 20 0 100 80 60 40 20 Relative Abundance 0 100 80 60 40 20 0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 Time (min) Intensity [counts] (10^3) Intensity [counts] (10^3) Sequence coverage, AUC, PTMs, %CVs, RT confirmation Sequence for Spectral Libraries 33

Pierce Peptide Retention Time Calibration Kit + Pinpoint 1.2 Software What s New? Peptide Retention Time Calibration Kit Pinpoint 1.2 Software for Targeted Protein Quan Application: Quickly assess and optimize chromatography and MS instrument performance Predict peptide retention times using calculated hydrophobicity factors Predict peptide elution across multiple instrument platforms Improve quantification and increase multiplexing with optimized scheduled SRM windows Incorporation of the PRTC kit provides a system QC, normalization, and RT correlation across experiments and instrumental platforms. Key features High-purity 15 synthetic heavy peptides mixed at equimolar ratio Elutes across entire chromatographic gradient Fully automated using Pinpoint 1.2 QC page Pinpoint 34

Peptide Retention Time Calibration (PRTC) Kit (Heavy Peptides) # Sequence Observed Mass ( Z=2) Hydrophobicity Factor (HF) 1 SSAAPPPPPR 493.7 7.5681 2 GISNEGQNASIK 613.3 15.50003 3 HVLTSIGEK 496.3 15.52207 4 DIPVPKPK 451.3 17.65144 5 IGDYAGIK 422.7 19.15385 6 TASEFDSAIAQDK 695.8 25.8834 7 SAAGAFGPELSR 586.8 25.23967 8 ELGQSGVDTYLQTK 773.9 28.36797 9 GLILVGGYGTR 558.3 32.17702 10 GILFVGSGVSGGEEGAR 801.4 34.51977 11 SFANQPLEVVYSK 745.4 34.96488 12 LTILEELR 498.8 37.30326 13 NGFILDGFPR 573.3 40.41916 14 ELASGLSFPVGFK 680.4 41.18506 15 LSSEAPALFQFDLK 787.4 46.66305 35

Retention Time Analysis Comparison with Internal Standards 2.14591x + 7.46657 R 2 = 0.95902 1.91004x + 11.44465 R 2 = 0.97641 36

Conclusions Quanfirmation enabled characterization and quantification were performed in 1 experiment Separating quantification (MS-level) and qualitative enables reprocessing data for targeted peptide expansion Introduction of PRTC kit enabled method reproducibility for the AS, LC, and MS methods PRTC kit provides direct relationship of calculated hydrophobicity factors to measured retention times and scalability Absolute and/or relative quantitation using heavy peptides Entire method is integrated with Proteome Discoverer and Pinpoint 37

Acknowledgments Kevin Cook Zhiqi Hao Scott Peterman Thank You 38