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Large Molecule Bioanalysis: LC-MS or ELISA? A Case Study

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Both ligand binding assays (LBA) and mass spectrometry
(MS) methods are widely used in routine bionalysis with expanded applications of MS to large molecules in
the years ahead. In this presentation, PK parameters in the rart for three monoclonal antibodies (mAbs) are compared as derived from plasma concentration data as measured by LBA or Immunocapture LC-MS/MS.

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Large Molecule Bioanalysis: LC-MS or ELISA? A Case Study

  1. 1. Large Molecule Bioanalysis: LC-MS or ELISA? A Case Study Zamas Lam, Ph.D. SVP Preclinical Development
  2. 2. Goal: Compare LC-MS/MS vs. LBA using three mAbs Compare PK parameters using 2 different bioanalytical methods Primary Concern LLOQ: 10 ng/mL Dynamic range: >4 orders if possible Sample volume: <5 µL for serial sampling from a single mouse vs. n = 3/time-point Selectivity: effectiveness of immunocapture & capacity, capacity, capacity … Robustness with respect to batch size Assay throughput: automatable Ease of use: well trained analysts vs. Ph.D.-level scientist Timeline: from assay concept to AUC data Cost: reagent and equipment Secondary Concern Transferability wrt matrices: serum vs. plasma; other tissues? Transferability wrt species: mice vs. rats vs. NHPs vs. human 2015 ASMS Sciex user Mtg 2
  3. 3. Which biologics to test? 2015 ASMS Sciex user Mtg 3 RIA LOD- 8 µU/mL ULOQ- 160 µU/mL Matrix- Human Serum ELISA or Gyros LOQ-250 ng/mL ULOQ-10,000 ng/mL Matrix- Rat, Mouse & Human Serum ELISA or Gyros LOQ-250 ng/mL ULOQ-10,000 ng/mL Matrix- Human Serum INSULIN ADALIMUMAB INFLIXIMAB ELISA or Gyros LOQ-500 ng/mL ULOQ-100,000 ng/mL Matrix- Rat, Mouse & Human Serum ELISA or Gyros LOQ-250 ng/mL ULOQ-3,000 ng/mL Matrix- Human Serum ELISA or Gyros LOQ-100 ng/mL ULOQ-5,000 ng/mL Matrix- Rat, Mouse & Human Serum TRASTUZUMAB BEVACIZUMAB RITUXIMAB
  4. 4. Experimental: in-life Order Adalimumab, Rituximab, Trastuzumab Single SC dose mid-scapular area @ 10 mg/kg Housing: metabolism cages; Feeding/Water: ad libitum Time-points: Pre-dose, 0.5 h, 2 h, 6 h, 1, 2, 3, 6, 8, 10, 14, 17, 21, 24, 28 d 2015 ASMS Sciex user Mtg 4 Male Sprague Dawley rats: 250-300 g n = 4/test article Sample collection individual time-points; tail-snip @ 150 µL/time-point processed to serum split to 2 samples for LBA and immunocapture LC-MS/MS Male CD-1 mice: 20-22 g n = 24/test article Sample collection 3 animals/group/time-point retro-orbital and cardiac puncture @ 150 µL/time-point processed to serum split to 2 samples for LBA and immunocapture LC-MS/MS
  5. 5. Experimental: LBA 2015 ASMS Sciex user Mtg 5 Coat with Target or Capture Ab Sample Dilution and Addition Detection Ab Substrate Read 450nM 96-well plate
  6. 6. Experimental: Immunocapture LC-MS/MS 2015 ASMS Sciex user Mtg 6 Antibody Enrichment Tryptic Digestion LC/MS Analysis Animal Serum Add SIL Whole Protein Y Y Y Y Y Y • Streptavidin coated Magnetic Beads binding with target IgG Y Y YYY YY Y Y Y Y YY Y Y Wash & Elute Y Y Y Y Y Y Y Y Interferences Anti Fc Anti TNF α Anti Insulin Anti PEG Anti Drug ExionLC™ QTRAP® 6500 System
  7. 7. Data: Adalimumab in the Rat 2015 ASMS Sciex user Mtg 7 10 100 1000 10000 100000 0 96 192 288 384 480 576 672 SerumAdalimumabConc.(ng/mL). Hours Rat # 5 Rat # 6 Rat # 7 Rat # 8 10 100 1000 10000 100000 0 96 192 288 384 480 576 672 SerumAdalimumabConc.(ng/mL). Hours Rat # 5 Rat # 6 Rat # 7 Rat # 8 ELISA Immunocapture LC-MS/MS
  8. 8. Data: Adalimumab in the Rat 2015 ASMS Sciex user Mtg 8 100 1000 10000 100000 0 96 192 288 384 480 576 672 SerumAdalimumabConc.(ng/mL). Hours ELISA MS Adalimumab (Humira) 10 mg/kg SC Mean SD Mean SD Cmax (ng/mL) 68200 7970 49800 4860 tmax (h) 102 49.5 78.0 45.4 AUClast (h*ng/mL) 21900000 4000000 16100000 3210000 t1/2 (h) 108 139 132 186 ELISA LC-MS/MS 100 1000 10000 100000 100 1000 10000 100000 LC-MS/MS ELISA Rat # 5 Rat # 6 Rat # 7 Rat # 8 Unity ~20% bias
  9. 9. Data: Trastuzumab in the Rat 2015 ASMS Sciex user Mtg 9 ELISA Immunocapture LC-MS/MS 100 1000 10000 100000 0 96 192 288 384 480 576 672 SerumTrastuzumabConc.(ng/mL). Hours Rat # 9 Rat # 10 Rat # 11 Rat # 12 10 100 1000 10000 100000 0 96 192 288 384 480 576 672 SerumTrastuzumabConc.(ng/mL). Hours Rat # 9 Rat # 10 Rat # 11 Rat # 12
  10. 10. Data: Trastuzumab in the Rat 2015 ASMS Sciex user Mtg 10 ~10% bias 100 1000 10000 100000 0 96 192 288 384 480 576 672 SerumTraztuzumabConc.(ng/mL). Hours ELISA MS 1000 10000 100000 1000 10000 100000 LC-MS/MS ELISA Rat # 9 Rat # 10 Rat # 11 Rat # 12 Unity Trastuzumab (Herceptin) 10 mg/kg SC Mean SD Mean SD Cmax (ng/mL) 72800 3880 71496 6873 tmax (h) 60 13.9 66.0 12.0 AUClast (h*ng/mL) 26900000 5020000 29600000 5570000 t1/2 (h) 258 150 268 160 ELISA LC-MS/MS
  11. 11. Comparison: LBA vs. Immunocapture LC-MS/MS 2015 ASMS Sciex user Mtg 11 Parameters LBA Immuno-LC-MS/MS LLOQ (mAb usually high exposure) High Sensitivity (~10 ng/mL) vs. Standard Sensitivity (~150 ng/mL) ~10 ng/mL Dynamic Range ~2-3 orders for colourmetric ≥3 for Gyros and ECL ~4 orders Sample Volume <5 µL (Gyros ~0.1 µL) ~25 µL Selectivity Single dimension, but manageable Higher Robustness Singlet vs. Duplicate ≥90% ISR Potential Stable label IS mAb & catabolites, but Why Depends on the epitopes TBD Transferability High Higher Multiplexing, but Why Not really Potentially Assay Throughput High (120-180 samples/analyst/day) Medium Equipment Cost Low (USD$10K) High (USD$500K) Reagent Cost Low Medium (SILmAb) Timeline Specific Ab – limiting step (e.g. Rituximab) Target capture – not rate limiting (e.g., Adalimumab , Bevacizumab, Imfluximab) Shorter initially
  12. 12. Additional Studies in progress/Thoughts More data set needed Adalimumab – mice Rituximab – mice and rats Trastuzumab – mice Understand the AUC differences, if any, and what is “acceptable” Understand realistic LLOQ and dynamic range What is the approach for new mAb Discovery screening (generic IgG assays) vs. development (selectivity) Confirm feasibility of single mouse PK (≤5 µL per time-point): LBA vs. LC-MS/MS Robustness with respect to batch size and ISR Ease of use Assay throughput and Timeline Serum vs. plasma vs. tissues 2015 ASMS Sciex user Mtg 12
  13. 13. Acknowledgement Sciex Suma Ramagiri Hua-Fen Liu Witold Woroniecki Lei Xiong Ian Moore Chang Liu Gary Impey Debadeep Bhattacharya Joe Fox Elliot Jones 2015 ASMS Sciex user Mtg 13 QPS Bruce Aungst Danielle Graden Erin Reynolds Helen Shen Jamie Stefanick Sarah Patterson QPS Caroline Becker James McClean John Kolman Melissa Calvarese Quynh-Giao Pham Stacey Gottschall Xun Wang

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