Tony Mire-Sluis Vice President, Corporate, Product and Device Quality Amgen Inc

Transcription

1 The Regulatory Implications of the ever increasing power of Mass Spectrometry and its role in the Analysis of Biotechnology Products Where do we draw the line? Tony Mire-Sluis Vice President, Corporate, Product and Device Quality Amgen Inc

2 The Sensitivity of Mass Spectrometer (MS) Methods is Progressing Rapidly Year Detection limit of peptide (pmol) 2

3 Mass Spectrometry Is Not ne Method MS applied to biologics is a rapidly evolving field and as such, it is important to relay the rationale for the method of choice for a particular application and if it is adequate for the intended use, for example: Ion Trap for sequencing due to its MS n capability TF for identifying whole mass and impurities due to mass accuracy Resolution (M/ M peptide mass) Ion trap: 1,000-4,000 Q-TF: 10,000-50,000 rbitrap: 10, ,000 FT-ICR: 50,000 1,000,000 Mass Accuracy (Low ppm) Ion trap: ~200 ppm Q-TF: ~5 ppm (with an internal calibrant) rbitrap: ~ 4 ppm FT-ICR: ~ 2 ppm

4 The Power of Fragment Assignment is Method/Equipment Specific N L = 4. 7 e N L = 1. 6 e N L = 1. 4 e m / z m / z m / z Ion trap Resolution (M/ M) ~ 3,000 Accuracy ~ 300ppm Q-TF Resolution ~ 10,000 Accuracy ~ 50 ppm Simulated spectra rbitrap Resolution ~ 30,000 Accuracy ~ 4 ppm

5 Sensitivity improvements in Mass Spectrometry are Allowing Increasing Detection of Product Variants but also Faces Challenges MS ionization, transmission and detection improvements enable peptide mapping based detection of minor species as low as 0.001% compared to the expected species These improvements can be applied to: Sequence Variants (errors in the DNA) Misincorporations (errors in transcription or translation) Post-translational Modifications due to cellular processes PTM s due to storage stability studies Key Concept: ionization efficiency of a specific species can be impacted by sequence changes and matrix effects Example: a methionine oxidation variant elutes at a different retention time and is suppressed in the presence of a major expected peptide.

6 Sensitivity improvements in Mass Spectrometry are Allowing Increasing Detection of Product Variants but also Faces Challenges Advantages: Increases the likelihood of observing variant species that coelute with expected peptides (i.e. not observable using UV) Increases the likelihood of observing variants that are below the LD of UV detection By comparing the signal intensity between samples, relative differences can be determined Disadvantages: Absolute quantitation requires isotope labeled standards Making isotypic RS, running under specific mode for each species, generating calibration curves etc. requires significant effort Ionization efficiency differences can greatly impact detection: A small peptide from a Lys variant does not bind to the column Two peptides formed due to a Lys variant have improved ionization and are over-represented compared to the expected peptide Difficult to assess the relevance of a variant at < 1%.

7 Implementing MS Technologies Into a Control Strategy Data from orthogonal methods should support nonunequivocal MS data interpretation MS analysis that leads to peak assignments for other coupled analytics is an important characterization tool but it should be linked to relevance of the assigned peak. e.g., is the peak critical for potency and functionality of the product? MS should help inform a control strategy program on the most adequate release and stability analytical methodology needed for the particular product.

8 Implementing MS Technologies Into a Traditional Analytical Program Need extensive knowledge of method capability: Reproducibility/Ruggedness Factors that affect Mass Spec results: m/z working range Non-linear MS effects, non-specific peaks, matrix effects, high background noise Analyte specific fragmentation efficiency Coupling techniques should be carefully evaluated for compatibility with MS (e.g., use of adequate chromatography method, matrix compatibility) Identification of species Differential ionization efficiency may drive the need to have different ionization conditions and detection Data interpretation Relationship to other methods

9 Conventional Bottom Up Protein Characterization Protease MS/MS MS/MS MS/MS MS/MS GLSDGEWQQVLNV VEADIAGHGQE LFTGHPETLEK FDKFKHLKTEAE ASEDLKKHGTV GLSDGEWQQVLNVWGKVEADIAGHGQEVLIRLFTGHPETLEKFDKFKHLKTEAEMKASED

10 Bottom-Up methods have Advantages and Disadvantages The digestion improves the ability to detect posttranslational modifications and ability to perform sequence analysis but: The entire molecule often not covered A high analyte concentration is required for digestion May be difficult to achieve sometimes Artifacts can occur during digestion Reduction Alkylation Proteolysis Disulfide formation or scrambling Carbamylation in the presence of urea Transpeptidation Amino acid rearrangements Loss of labile modifications (e.g., succinimide)

11 Digestion artifacts Asparagine turns into aspartic/isoaspartic acid (deamidation) Aspartic acid turns into isoaspartic acid (isomerization) Succinimide turns into aspartic/isoaspartic acid N H NH 2 H N N H N N H H H N Aspartic acid Asparagine Succinimide intermediate HN HN H isoaspartic acid

12 MS/MS of intact proteins Top Down MS/MS GLSDGEWQQVLNVWGKVEADIAGHGQEVLIRLFTGHPETLEKFDKFKHLKTEAEMKA SEDLKKHGTVVLTALGGILKKKGHHEAELKPLAQSHATKHKIPIKYLEFISDAIIHVLHSK HPGDFGADAQGAMTKALELFRNDIAAKYKELGFQG

13 Top Down Mass Spectrometry Also Has Advantages and Disadvantages Advantages: Entire molecule examined Reduced sample concentration requirement Speed Minutes/hours vs. days Reduced artifacts due to minimal sample manipulation Compliments bottom-up method Disadvantages: Availability of the instruments Very expensive Training of Analysts Data Analysis Software (Mass Analyzer) developed in-house Extensive experience still required to appropriately interpret the data For large proteins, only certain part of the molecule may be analyzed Generally cannot cut through intact disulfide bonds Degradation analysis is an average

14 Assessing Conformational Differences by MS Conformational differences can be assessed by MS in the: Gas phase - Ion mobility or charge state distribution differences Fast analysis using low sample amounts. The meaning of gas phase differences is not universally correlated to solution phase differences and the precision of the % change may not be sensitive to minor species. Solution phase chemical labeling (H/D, covalent labeling) Improvements in reproducibility and throughput enable small % differences in conformation to be detected. However, the specific structure of the conformational change is not known making it difficult to assess the biological relevance.

15 Existing Regulatory Issue Identity vs. Purity FDA is challenging use of any method solely for identity testing if it reveals other information about the purity of the product. This thinking can also be extended to characterization. For Mass Spec this will necessitate: Better understanding of variability of peaks More work on identifying peaks So does the increasing power of MS provide incremental value? More justification of conforms to standard What other product or process related substances could appear on Mass Spec Spectra?

16 The Need To Understand What Affects Mass Spec Results Interpretation of any method relies on knowledge of what is real and what is artifact the more sensitive you get, the more this is essential to understand complex data Sample preparation is critical in MS applications. There should be a careful consideration on sample treatment and how representative is the data obtained of that sample when compared to the drug product material that will be administered to the patient: Buffer/matrix changes to make the sample compatible with chosen MS application How representative is the sample coming out of the analytical method coupled to MS (e.g., chromatography)

17 Implementation of MS Technologies Providing the Necessary Supporting Data There is a need to develop standards and controls that provide a better understanding of the data: Purified product variants Develop orthogonal identification methods accounting for method matrices Scientifically justified method acceptance criteria Relevant experimental controls Appropriate reference materials that illustrate method variability

18 NIST Mass Spectral Library: Consensus Spectra Building High Quality MS Reference Data Peptide Library 500,000 peptides for 8 species Data from the NIST program kindly provided by Stephen Stein and Mike Tarlov of NIST NIST/EPA/NIH Mass Spectral Library EI spectra of 212K compounds IgG Library with NIST reference material peptides glycopeptides Small Molecule Tandem MS 7,020 compounds Ion Trap/Collision Cell glycans intact & large fragments?

19 Consensus vs. Single Spectrum Consensus of 38 Spectra HCD 42eV TKPREEQYNSTYR Individual Spectrum HCD 42eV Consensus spectra can distinguish between noise and real signals, e.g., low intensity peaks between 1010 and 1275 m/z might be interpreted as noise and discarded, but consensus spectra indicate these are real species.

20 NA2G1F from Rituximab Matches Library Rituximab Head to Tail Comparison Glycan Library

21 Protein Structure: Reference Mass Spectral (MS) Library of Antibody Therapeutics Antibody Library with NIST reference material peptides glycans glycopeptides intact & large fragments? Real spectra of species High quality data: consensus spectra Confident identification Faster data analysis

22 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. Example: Identification of methionine oxidation when there are two Met s and a Trp residue in the peptide. 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%.

23 Implementing MS Technologies Into an Analytical Program The Equipment Equipment availability Sole sourcing Lot to lot variability of equipment Transferability of method Lifecycle of method Vendor changes Upgrades of hardware Upgrades of software etc.

24 Implementing MS Technologies Proving it Works in a QC Environment Method Qualification/Validation Identifying appropriate parameters Ability to control method Creating appropriate standards/controls Reagent quality control Training

25 Summary for Successful Implementation of Lot Release/Stability Commercial MS Based Methods Performance: Low failure rate Method operation and data interpretation not analyst dependent Characteristics Robust from sample prep through instrumental analysis and data interpretation Automated integration preferred (integration guideline) utlier data points determined mathematically and not by analyst interpretation Highest possible throughput without sacrificing robustness Practical run time relative to analyst shifts

26 Summary for Successful Implementation of Lot Release/Stability Commercial MS Based Methods Cost effective; doesn t waste significant amount of sample Audit compliant Not dependent on poorly available instrumentation or reagents No patent interference Validatable Clearly defined purpose with respect to product attribute(s) under evaluation Targeting multiple quality attributes desirable as long as don t sacrifice robustness

27 Conclusions It is important for you and regulators to fully understand the technology you are using Industry can help the regulators through meetings, publications and regulatory submissions Industry must evaluate mass spectrometry technologies depending on their use (e.g. characterization vs. lot release), the nature of the product and what provides real value in understanding safety, efficacy and consistency of our products How relevant is 0.1% of your product?

28 Acknowledgments Joseph Phillips Izydor Apostle Stephen Stein (NIST) Mike Tarlov (NIST) Brent Kendrick Dean Pettit Dave Hambly