Driving Efficiency in Pre-Clinical Development with ......with Automated Mass -Spectrometry Analysis...
Transcript of Driving Efficiency in Pre-Clinical Development with ......with Automated Mass -Spectrometry Analysis...
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Driving Efficiency in Pre-Clinical Development with Automated Mass-Spectrometry Analysis and Characterization of Novel Biologics
Hirsh NandaJanssen Pharmaceuticals, Spring House PACell & Developability Sciences, BioTD
September 12, 2018
CASSS MS 2018
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Pharmaceutical Development & Manufacturing Sciences 2
Target Research “Target
validation”
Hit and Lead Generation“Candidate
source”
Lead Optimization“Candidate
Engineering”
Cell & Developability
Sciences
GMP Batch Development
NME IND
Steps in Large Molecule Early Development
DiscoveryDevelopment
102-103 10-20 1-4Num
ber
of
Can
dida
tes:
Drive candidate selection and development of the manufacturing cell line
Developability | Early Formulation | Cell Line Development
C e l l & D e v e l o p a b i l i t y S c i e n c e s
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Pharmaceutical Development & Manufacturing Sciences
DEVELOPABILITY process
In SilicopItheo
PTM risks/motifsSAP
3
* If appropriateSIA: Stability Indicating AssaysIMW: Intact Mass Spectrometry
ReleaseBuffer Screen
cIEFHIC
IMWDLS
CaliperSEC
CEX*DSC
Fab arm exch*
Free Thiol*
ConcentrationA280/A350 conc@ 0, 1 & 4 weeks
Serum CompSEC
pH3.5Aggregation
FeOxidation
H2O2Oxidation
SIA
DLScIEF
SECIMW
Caliper
PTM Risk
40˚Caggregation
pH8.5deamidation
MS Methods
Activity Assays
81 Assays per Candidate
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Pharmaceutical Development & Manufacturing Sciences
Cell Line Development and Clone SelectionExpression vector (DNA for mAb)
Host cells
Expand top clone(s)2nd screen - Clonality
Productivity
Expressing Stability
Cell Culture Performance
Product Quality
1st screen – Rare expressers
Productivity
Manufacturing Cell Line
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In Depth Characterization and Key Analytical Readouts
uSP Screen Developability Cell Line Selection
Sequence Variance
, Signal Peptide
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Off-Platform Programs Present New Challenges to Molecule Characterization
Alternative Scaffolds
ADC
Multi-Specifics
Vaccines
>50% of the Early Pipeline are not mAb
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- Large molecule therapeutics susceptible to numerous post-translational modifications and other variants- Off-platform biologics have only added to this complexity
Complexity of Biologics
Challenges : Know More Sooner
- Characterization and PTM analysis of multiple different candidate molecules within pre-clinical development.
- “Speed to IND”
Fast Turn-around Time
Mass spectrometry data provides information on many important molecule attributes but often requires multiple software packages and extensive manual interpretation.
Complexity of MS Data
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Bottom Up and Intact Mass Approach for Molecule Characterization
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Intact Mass Analysis PipelinePeptide Mapping Analysis
Peptide Mapping Intact Mass & Subunit
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Bottom Up and Intact Mass Approach for Molecule Characterization
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Intact Mass Analysis PipelinePeptide Mapping Analysis
Peptide Mapping Intact Mass & Subunit
Data Analysis Bottleneck:Computational Pipelines to Automate Analysis
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Generation 1: Peptide Mapping Analysis Pipeline
Data Acquisition
• Mass-SpecInstruments
• CRO
Identification
Thermo Proteome Discoverer• PMI Preview
(system & sample suitability)• SequestHT• PMI Byonic• Mascot Server
Peptide QuantitationSkyline (XICs)
Report
Excel, PPT
Vendor Specific Focused on PTMs – Separate Searches for Other Attributes
Manual Steps in Transferring Files Between Software Packages
Extensive time in data validation and report generation
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Generation 2: End to End Pipeline for Accelerated Characterization
Mass-SpecInstruments
CRO
Peptide ID
Product Variants:• PTMs• Sequence Var• Glycation• Signal Peptide• Glycosylation• Clipping• Unknows
(Wildcard)
Biologics/ LabKey
End-to-End Automation
Byologic Viewer
Protein Metrics: BYOS
Intelligent False Positive Detection
Validation
1. Automated data sweep into search software – Vendor Agnostic2. Extensive Product Variant Search3. Reduce manual validation time – Define Criteria to flag false-positives4. Automated export of results5. Aggregate data with molecule information to build ‘In-house’ knowledge base (also auto QC)
Reporting: PDF / CSV
Exports
Data Acq. Data Aggregation
1
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Automated Sweep Into Byos: Structured Data Folders & Filenames
BYOSData Files / Sequences Search Validate Report
Sequence Automatically Pulled from Master Database
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BYOS Preset Workflow: Executes Multiple Enzyme Searches Depending on Files in the Project Folder
Identify enzymes based on folder name
Modifications ‘one-pot’ search:PTMs, Seq Var, Glycosylation,
Glycation, Signal Peptide, Wildcard, etc…
Report Template
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Validation Through the Interactive GUI
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Case 1: Developability
uSP Screen Developability Cell Line Selection
Sequence Variance
, Signal Peptide
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PTM Analysis Generally Focuses on CDRs Where Modifications are Most Likely to Influence Potency
Heavy Chain Light ChainNIST Reference mAb
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Automated Report Template
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PTM Modification Tab
Chem Ox High pH Low PH Metal Ox Release Thermal
• Filter on specific modifications or molecule regions of interest
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PTM Modification Tab
Chem Ox High pH Low PH Metal Ox Release Thermal
• Filter on specific modifications or molecule regions of interest
[Peak Eval] : Flag Identifications That Require Further Screening
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All Results Exported to CSV to Allow for Additional Formatting and Reporting
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Subunit PTM Region Motif %PTM Release
%PTM Chem Ox
%PTM Metal Ox
%PTM Low pH
%PTM High pH
%PTM Thermal
Heavy Chain
Oxidation CDR 1 W N.D. N.D. N.D. N.D. N.D. N.D.Oxidation CDR 2 W N.D. N.D. N.D. N.D. N.D. N.D.Oxidation CDR 3 W N.D. N.D. N.D. N.D. N.D. N.D.
Isomerization CDR 1 DS 0.61 0.38 0.59 0.32 20.30 5.96Deamidation CDR 1 NN 2.71* 3.29* 3.45* 2.13* 4.28* 3.18*
Light ChainOxidation CDR 1 W N.D. N.D. N.D. N.D. N.D. N.D.
Deamidation CDR 1 NL N.D. N.D. N.D. N.D. N.D. N.D.
Heavy Chain : FCOxidation CH3 M 6.14 31.81 7.28 6.59 7.70 13.84
Deamidation CH3 NN 4.37 4.20 4.63 3.96 28.28 12.73
* total of all deamidation states N.D. : Not Detected
Compare chemical stability profile across several candidates Correlate PTMs with bio-assay results on forced degradation samples
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Feature Finder for Asp isomerization
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Poster:P-249-M: Unexpected Asp-Isomerization Behavior in Therapeutic Proteins: Connecting Primary Structure with Higher Order Structure and Dynamics
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Case 2: Cell Line Selection
uSP Screen Developability Cell Line Selection
Sequence Variance
, Signal Peptide
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SVA in Clone Selection
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SVA in Clone Selection
WT detectedRetention time shift
K/R varianceMonoisotopic Peak
Peptide Score Explained by common Mod
SVA Decision Treesequence variant annotated based on filter logic
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Validated List of Sequence Variants for Eight Screened Clones
Protein Name Var. Pos. Mod. AA Mod. Names Sequence C3267B C3268B C3268C C3268D C3269B C3270B C3271B C3272B
CDS000045130 61 D Asp->Ala/-43.9898 R.LLIYSTSNLASGIPaR.F 0.00 0.00 0.00 0.00 0.32 0.00 0.00 0.00CDS000045130 105 L Leu->Val/-14.0157 K.vEIK.R 0.00 0.00 0.00 0.00 0.00 0.15 0.00 0.00CDS000045130 105 L Leu->Val/-14.0157 K.vEIKR.T 0 0 0 0 0 0.46 0 0CDS000055476 9 S Ser->Gly/-30.0106 -.qVQLVQSGgELK.K 0.00 0.00 1.43 0.00 0.00 0.00 0.00 0.00CDS000055476 34 M Met->Thr/-29.9928 K.ASGYTFTDYStHWVR.Q 0.00 0.00 0.00 0.05 0.11 0.12 0.00 0.00CDS000055476 256 M Met->Thr/-29.9928 K.DTLtISR.T 0.06 0.06 0.07 0.07 0.19 0.18 0.06 0.07CDS000055476 418 K Lys->Arg/28.0062 K.LTVDr.S 0.00 0.00 0.00 0.00 0.10 0.09 0.08 0.00
CLONE1 CLONE2 CLONE3 CLONE4 CLONE5 CLONE6 CLONE7 CLONE8
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Case 3 : Signal Peptide Screening
uSP Screen Developability Cell Line Selection
Sequence Variance
, Signal Peptide
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Transient ExpiCHO Expression for Unprocessed Signal Pepetide (uSP) Prediction
ExpiCHO transient expression platform
High expressing CHO-S cell line, optimized culture feed and efficient transfection reagent
7-day culture
Generate constructs with multiple leader sequence
Comparison of SP Levels in Bioreactor and Transient CHO Expression
MoleculeCHO Stable ExpiCHO**
Size of bioreactor %Total uSP %Total uSP
Molec 1 1000L 10.3 16.8
Molec 2 10L 1.6 1.0
Molec 3 2000L ND ND
Molec 4 250L 2.4 2.3
Molec 5
10L 6.0
4.650L 4.6
50L 5.4
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Transient ExpiCHO Expression for Unprocessed Signal Pepetide (uSP) Prediction
ExpiCHO transient expression platform
High expressing CHO-S cell line, optimized culture feed and efficient transfection reagent
7-day culture
Generate constructs with multiple leader sequence
Molec Chain Signal Peptide Sequence uSP Motif uSP %
1HC MAWVWTLLFLMAAAQSIQA -- --
LC MARSALLILALLLLGLFSPGAWG -- --
2
HC MAWVWTLLFLMAAAQSIQA -- --
LC MAWSPLLLTLLAHCTGSWA
AWSPLLLTLLAHCTGSWA 3.8
LAHCTGSWA 0.8AHCTGSWA 0.6
HCTGSWA 0.4
3HC MAWVWTLLFLMAAAQSIQA -- --LC MAWALLLLTLLTRDTGSWA LLTRDTGSWA 5.3
Pipeline searches for all possible ragged clips to the leader sequence
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Bottom Up and Intact Mass Approach for Molecule Characterization
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Intact Mass & SubunitPeptide Mapping
Native Degly IdeSReduced
UNIFI WorkgroupIntact Mass Analysis Pipeline
Reduced, Alkylated
Trypsin Chymotrypsin
In-house Data Analysis Pipeline
Forced Deg Set, Clones, etc.
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UNIFI Workgroup – Intact Mass Workflow
• Separates instrument control and data analysis
• Multiple scientists can work in parallel
• Streamline intact mass workflow:
Acquisition -> Processing -> Reporting -> ELN
• Scientific Library of Molecules – automated peak identification
• Reporting templates for different assays:• intact mass, reduced mass and sub-
units analysis
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Unifi Automated Analysis – Early Clone Screening During CLD
Sampleg/L by RP
g/L by Octet
Rel. % Intact
Rel. % -AP Clip
Rel. % -A Clip
(14429.4 Da)
(14261.2 Da)
(14358.3 Da)
4319.DRP.1D2 3 2.8 91.8 6.5 1.84319-JZ2-23 2.2 1.7 85.3 10.8 44319.FA.4.D7 2.1 2.8 91.6 5.5 2.94319.RCN.1 2.1 2.5 86.4 8 5.64319-JZ1-5 2.1 1.4 94.4 4.2 1.44319.LG.F11 1.9 1.6 94.4 3.5 2.14319.VRH.4A9 1.9 1.5 91.1 5 3.94319.LG.C8* 1.8 2.2 -4319.RCN.4 1.8 1.7 90.7 5 4.34319-JZ2-12 1.8 1.9 88.9 5.9 5.14319.DRP.4F7 1.7 1.4 94.4 1.1 44319-JZ2-4 1.7 1.4 91.6 5 3.44319.RCN.6 1.6 1.4 87.6 10.5 1.94319.FA.1.C6 1.5 1.1 86.6 9.7 3.74319.RCN.3 1.5 1.6 87.6 10.5 1.94319-JZ2-1 1.5 1 88.9 5.9 5.14319-JZ2-29 1.5 1.4 93.1 4.8 2.14319.DRP.3B3 1.4 1 88.8 5.7 5.54319.FA.1.F4 1.3 0.9 86.7 8.8 4.6
4319.XS.MC2-0.5m-4 1.3 1.3 80.2 3.4 16.4
4319-JZ2-24 1.3 1.4 75.3 3.4 21.34319.FA.1.B6 1.2 1 82.4 3.3 14.34319.FA.1.F6 1.2 0.9 76.2 4.4 19.54319.LG.D12 1.2 1.2 92.8 4.5 2.74319.MS.2B8 1.2 1.1 93.6 4.8 1.64319.MS.2G10 1.2 1.1 95.6 4 2.14319.MS.2G7 1.2 1 93.9 4 2.14319.RCN.11 1.2 1.2 89 5.9 5.14319.XS.MC1-1m-2 1.2 1.6 88 2.2 9.84319.VRH.4D4 1.1 0.8 95 3.9 1.1
-AP
-A
Glycoprotein: Monitoring Potential Clipping Sites in Parental Clones
.
.
.
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Data Acq.
Integrating Both Workflows Into One Data Analysis Pipeline
Mass-SpecInstruments
CRO
Peptide ID
Peptide Mapping Based Product Variant Search
Protein Metrics: BYOS – Master Script for End-to-End Automation
BYOSValidation
Joint Reporting
Comparison of
Modifications
Intact Mass Database
Intact Mass Deconvolution and Peak Annotation
Whole Protein or Subunit
Peptide Mapping
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Conclusions Established workflow for in depth
characterization of molecules in early phase programs
Automation of data processing has allowed us to meet the challenges of fast turn-around-times and off-platform molecules Intelligent Filtering to Reduce Manual Validation Time (It will get
smarter as we do)Future Direction: Next generation pipeline to integrate intact/subunit and peptide map
characterizationModification knowledge base and data mgmt Automated clip and fragment detection by N-terminal Labeling (P-224-M)
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Acknowledgements
Bo ZhaiAndy MahanHarsha GunawardenaEric BeilJeff BrelsfordBarry Morse
Eric CarlsonJing LiYong Joo KilAndrew NicholsIlker Sen