Advancing the Promise of Analytics of the Future using Multi Attribute Methodology Anthony Mire-Sluis Vice President, North America, Singapore, Contract and Product Quality Amgen Inc
Outline Multi Attribute Method purpose and rationale Principles & Development of the multi-attribute MS-based method MAM Examples of quantification of Product Quality Attributes Risks associated with MAM application Conclusion
Rationale for a Multi-Attribute Method Cornerstone analytical method for development of processes and analytics that embrace the principles of Quality-by-Design Direct monitoring of biologically relevant PQA s rather than indirect monitoring by conventional methods (ie CEX) thereby ensuring safety and efficacy More complete analysis of the product quality profile during and after processing compared to current methodologies Reduces the number of assays used for process development, product disposition and in-process control supporting Analytics of the Future initiatives and reducing cost
MAM will replace non-attribute specific assays with a method capable of specifically detecting and measuring critical attributes Current Release Method Product Understanding Future Release Method 70% Potency Attribute 1 Attribute 2 Attribute 3 Attribute 4 100% Potency Main peak CEX separation 150% Potency Attribute 5 A1, A2 2 x A3 A3, A4 CEX separation Sub-fraction Potency Assessment Attribute Main peak Potency 100% A1 50% A2 110% A3 95% A4 102% A5 150% A5 A1 A3 A5 MAM MS Based method Replacing CEX monitoring of pre-peaks with more specific method monitoring relevant attributes: A1 (efficacy) A3 (safety) A5 (safety and efficacy)
A Multi-Attribute Method (MAM) has been developed Orbitrap Mass Spectrometer Hi resolution Fast scan speed Small footprint Technology allows for Plug and Play peptide map analysis Simple to use and more robust due to design and minimal features (1 button tuning, calibration) Automated software is used to generate a comprehensive attribute target list and automated quantification. Alignment of method and instrumentation for process development, PAT control and product disposition
MAM Peptide Map Sample Preparation Denature Proteins Denature the sample Reduce and alkylate Desalt Digest with trypsin Inject the digest Analysis
Single Multi-Attribute method is able to directly monitor more attributes than all other conventional methods combined Multi-Attribute Method Conventional Release Methods Antibody PQA Pep Map-MS SEC CEX rce-sds nrce-sds HILIC ID ELISA HCP ELISA Aggregate Assessment Deamidation (Isomerization) Assessment Disulfide Isoform Assessment Glycation Assessment High Mannose Assessment Methionine Oxidation Assessment Signal Peptide Assessment Unusual Glycosylation Assessment CDR Tryptophan Degradation Assessment Non-consensus Glycosylation Assessment N-terminal pyroglutamate Assessment C-terminal Lysine Assessment Galactosylation Assessment Dimer Assessment Fragmentation (peptide bond) Assessment Disulfide Reduction (DS Fragmentation) Assessment Host Cell Protein Assessment Mutations/Misincorporations Assessment Hydroxylysine Assessment Thioether Assessment Trisulfide Assessment Non-glycosylated Heavy Chain DNA Assessment Cysteine Adducts Assessment C-terminal Amidation Assessment CDR Conformers (HIC Isoform) Assessment O-linked glycans Assessment Fucosylation Assessment Residual Protein A Identity
Conventional CEX-HPLC Assay Monitors Peak Profiles Main Acidic Basic 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 min Attribute Acidic* Main* Basic* HC W 107 Oxidation x% y% z% LC W 92 Oxidation x% y% z% LC K 153 Glycation x% y% z% HC N 390 Deamidation x% y% z% HC M 258 Oxidation x% y% z% HC M 434 Oxidation x% y% z% LC N-term Q x% y% z% HC C-term K x% y% z% HC N-term pe x% y% z% HC D 276 P Cleavage x% y% z% Glycans Acidic Main Basic M5 x% y% z% A1G0F x% y% z% A2G0F x% y% z% A2G1F x% y% z% A2G2F x% y% z% * - content adjusted per molecule
MAM can serve as ID assay Read out of Product Specific CDR Peptides Ensures Specificity RT: 0.00-60.30 100 NL: 1.47E8 TIC F: FTMS + c 90 ESI Full ms [300.00-2000.00] 80 MS HC20130708_AMG 224_TS1_DSI_T1 70 60 50 40 30 20 10 100 0 90 80 70 60 50 40 30 20 10 RS Sample 0 0 10 20 30 40 50 60 Time (min) System Suitability NL: 1.40E8 TIC F: FTMS + c ESI Full ms [300.00-2000.00] MS HC20130708_AMG 224_TS2_DSI_T1 Sample Acceptance Criteria Sample Pass/Fail Criteria Parameters ΔRT of reference peaks Total peak area of reference peaks from RS runs %RRA (ratio of relative peak area) of reference peaks Mass accuracy < 5 ppm S/N for reference peptide value (TBD) The levels of PQAs (2-3) monitored from product specific reference standard within historical range Total peak area of reference peaks from sample runs ΔRT of sample reference peaks %RRA of sample reference peaks Mass accuracy < 5 ppm No new peak above IL limit
Comparison of HILIC Glycan Map and MAM Excellent Agreement EU A2G0F 250.00 200.00 150.00 A2G1F 100.00 50.00 0.00 60.0% A1G0 A2G0 A1G0F A2G1 A2G2F M5 A1G1F A2G1 M6 M7 M8 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 Minutes 40.0% 20.0% MAM HILIC 0.0%
Product Quality Risk Assessments are Performed to Assess Risk of Each Attribute PQA Assessment captures platform and product specific knowledge, criticality ranking and rationale Recommendation of attributes for control strategy Justification of specifications (in regulatory filings) Severity Score 9 Severe 7 Major 5 Moderate 3 Minor 1 Insignificant
Unit Operation Correlation (, or testing only) Occurrence Supporting Information Occurrence Decision Tree Occurrence Score Preliminary Hazard Risk Level Detection Method Capability (n) Stringency (i) Detection Score Detected downstream (if yes, list step)? Overall Detection Score Overall Unit Operation Risk Level Comments MAM Reduces Risk through Better Capability and/or Stringency Quality Attribute: Potential Adverse Impact: Severity Score: Methionine Oxidation (non-cmet ox impacts FcRN binding, impact to PK 7 Occurrence Detection at Unit Operation Downstream Detection 37 Transport unlabeled DP Extent of oxidation low (~2-3%, comparable to other projects), except for highly stressed conditions from MA data (TRPT-021224) L 7 High Testing by peptide map for characterizat ion only 1 5 3 No 3 Medium Applied MAM, therefore reduced stringency. Overall Risk Assessment RPN PQA Criticality Assessment Severity Process Capability Occurrence = X X Testing Strategy Detection
Application of MAM reduces risk due to more specific method - Methionine Oxidation Methionine Oxidation (Traditional) Methionine Oxidation (MAM - Monitoring) Methionine Oxidation (MAM-Specification) High High High High High High High High High Medium Medium Medium Medium Medium Medium Medium Medium High Low Low Low Low Low Low Low Low High Testing DSI DS DP High Medium Low Overall risk of non-cdr Met oxidation decreased from high to medium when applying MAM for clinical monitoring because it is actually detected versus being part of a chromatogram peak The risk can further decrease to low when applying MAM for a release test with rejection limits
Advancing Highly Sensitive Analytical Technology When utilizing highly sensitive methods, one has to assure that you have extensive knowledge of method capability: Reproducibility/Ruggedness Factors that affect results Sensitivity, Interference, Critical method parameters Identification of species Data interpretation Relationship to other methods
Criteria for evaluating a peptide or attribute using the multi-attribute method The experimental mass is less than 5ppm from the predicted mass Identification of the peptide/attribute is confirmed by MS2 fragmentation + orthogonal characterization methods (HILIC-MS for glycosylation) The experimental isotopic distribution must have a dot product score better than 0.95 when compared to the theoretical isotopic distribution. The retention time for the peptide/attribute must be within a set retention time window (determined by characterization of the molecule)
Automation vs Manual Interpretation Automation enables identification of variant species but computational decisions are based on statistical confidence. Manual confirmation is an important component for confirming nature and site of variants. Advantages: Identification can be made for species that would not be found using manual interpretation. Disadvantages: A thousand times more data to review and correlate with sample handling. Difficult to assess cause and impact due to a specific change. Clinical scale deamidation at 0.1%; Commercial scale at 1%.
Technology can Provide Great Detail to Product Characterization - But What do we do With it? 140 120 100 80 60 40 20 0 0 30 40 5 0 700 90 100 120 140 Yves Aubin, Health Canada Mass Spectrometry Analysis NMR Analysis Such complex profiles result can only result in Must be identical within method variability acceptance criteria if we do not understand what each peak is and whether it is relevant to product quality, safety or efficacy Therefore, new analytical technology, without an understanding of criticality of product attributes could become increasingly burdensome while providing little additional value for risk assessment, safety, etc.
MAM qualification progress is underway System suitability is defined: Based on reference peak area, RT and S/N Specificity: Based Mass accuracy, isotopic distribution, retention time Precision: Based on area % of peptide measured by MS extracted ion chromatogram Repeatability Intermediate precision Accuracy: Based on comparison to theoretical mass Linearity: Based on area of peptide measured by MS extracted ion chromatogram LOD/LOQ: Based on quality of spectral data (TBD) Integrity limit: Still defining threshold peak detection parameters Robustness Sample prep conditions Chromatography conditions MS conditions
Path forward Correlation with current release methods Multi-attribute method for release System suitability / Sample acceptance criteria strategy Specification strategy Numbers are reported compared to reference standard Need to establish specifications around acceptable limits Validation strategy Analysis program for automated quantification Analysis program for detection of new peaks CFR Title 21 Part 11 Compliance Application of MS in QC principles in regulatory filings
Conclusion Fundamentals of the single multi-attribute method for release: Automated quantification combining Orbitrap technology and dedicated software for QC application Flexibility Method allows constant input resulting from increased knowledge of the drug attributes during process development and better understanding of their criticality from clinical experience Science-based Critical quality attributes-centered information using most advanced technology Scientifically superior to current methods (CE-SDS, CEX). MSmethods needs science-based arguments on why we monitor these specific parameters Reduces cost of quality Reduced number of release tests Universal method: Process development simplified & more efficient
Acknowledgements Rohini Deshpande Jim Navratil Armineh Stone Jette Wypych Izydor Apostol Mee Ko Janice Chen Arezu Sesoleimany Susan Callahan Richard Wu Cindy Ren Kelli, Matthies Yuh-feng Chen Dora Delgado George Svitel Sabrina Benchaar Wenzhou Li Rich Rogers Alain Balland Bob Bailey Art Hewig Oliver Kaltenbrunner Greg Flynn Mark Benke Gregg Nyberg Roger Hart Eli Kraus Eugene Babcock Thermo Fisher: Amol Prakash and Scott Peterman (Pinpoint software) Jennifer Sutton (Sieve software) Ryo Komatsuzaki and Christoph Nickel (Chromeleon software)