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

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

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

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

5

In Depth Characterization and Key Analytical Readouts

uSP Screen Developability Cell Line Selection

Sequence Variance

, Signal Peptide

Off-Platform Programs Present New Challenges to Molecule Characterization

Alternative Scaffolds

ADC

Multi-Specifics

Vaccines

>50% of the Early Pipeline are not mAb

- 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

Bottom Up and Intact Mass Approach for Molecule Characterization

8

Intact Mass Analysis PipelinePeptide Mapping Analysis

Peptide Mapping Intact Mass & Subunit

Bottom Up and Intact Mass Approach for Molecule Characterization

9

Intact Mass Analysis PipelinePeptide Mapping Analysis

Peptide Mapping Intact Mass & Subunit

Data Analysis Bottleneck:Computational Pipelines to Automate Analysis

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

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

23

45

12

Automated Sweep Into Byos: Structured Data Folders & Filenames

BYOSData Files / Sequences Search Validate Report

Sequence Automatically Pulled from Master Database

13

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

14

Validation Through the Interactive GUI

15

Case 1: Developability

uSP Screen Developability Cell Line Selection

Sequence Variance

, Signal Peptide

PTM Analysis Generally Focuses on CDRs Where Modifications are Most Likely to Influence Potency

Heavy Chain Light ChainNIST Reference mAb

17

Automated Report Template

18

PTM Modification Tab

Chem Ox High pH Low PH Metal Ox Release Thermal

• Filter on specific modifications or molecule regions of interest

19

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

All Results Exported to CSV to Allow for Additional Formatting and Reporting

20

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

Feature Finder for Asp isomerization

21

Poster:P-249-M: Unexpected Asp-Isomerization Behavior in Therapeutic Proteins: Connecting Primary Structure with Higher Order Structure and Dynamics

22

Case 2: Cell Line Selection

uSP Screen Developability Cell Line Selection

Sequence Variance

, Signal Peptide

SVA in Clone Selection

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

25

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

26

Case 3 : Signal Peptide Screening

uSP Screen Developability Cell Line Selection

Sequence Variance

, Signal Peptide

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

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

Bottom Up and Intact Mass Approach for Molecule Characterization

29

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.

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

31

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

.

.

.

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

33

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)

Acknowledgements

Bo ZhaiAndy MahanHarsha GunawardenaEric BeilJeff BrelsfordBarry Morse

Eric CarlsonJing LiYong Joo KilAndrew NicholsIlker Sen