Automated sequence variant analysis supporting high tier ...€¦ · The need for fast sequence...

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Automated sequence variant analysis supporting high tier media selection Bo Zhai, PhD Biotherapeutic Development Janssen Research & Development

Transcript of Automated sequence variant analysis supporting high tier ...€¦ · The need for fast sequence...

Page 1: Automated sequence variant analysis supporting high tier ...€¦ · The need for fast sequence variant analysis in cell line development. 2. Automated analysis workflow reduced sequence

Automated sequence variant analysis supporting high tier media selection

Bo Zhai, PhD

Biotherapeutic DevelopmentJanssen Research & Development

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Agenda

Automated SVA

Minimal manual intervention

Less manual validation

Introduction

Cell & Developability Sciences

Cell line selection process

Spent Media

Analysis

Verification

Cell line selection support

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Introduction

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Large Molecule Early Development

Target Research

“Target validation”

Hit and Lead Generation

“Candidate source”

Lead Optimization

“Candidate Engineering”

Cell & Developability

Sciences

GMP Batch Development

NME IND

Discovery

Development

102-103 10-20 1-4Num

ber

of

Candid

ate

s:

Drive candidate selection and development of the manufacturing cell line

Cell Line Development | Early Formulation | pre-NME Analytical Support

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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More Molecules and Reduced Timeline

MOAs

(More molecules)

Cell Line Development

Faster to IND

(Reduced Timeline)

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New Cell Line / New Process

1 MONTH 2 MONTHS 3 MONTHS 4 MONTHS 5 MONTHS 6 MONTHS

Parental Cloning

10L BRX

Early Look Material,

Analytical

Transfectionup to 4 candidates

ambr250

100’s 10’s

Select the

Manufacturin

g Cell Line

Begin Early

Development

(from transfection pool)

# of clones

▪ Eliminated subcloning reduced timeline by 1.5 months (VIPS Technology)

▪ Site directed integration. Titers are more predictable, screen fewer clones.

▪ ‘Early Look Material’ produced from transfection pool (not clonal): Start Development Sooner.

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In Depth Characterization and Key Analytical Readouts

Sequence Variance

, Signal Peptide

& O-glycosylation

Proper chain recombination

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Off-Platform Programs Present New Challenges

Alternative Scaffolds

ADC

Multi-Specifics

Vaccines

>50% of the Early Pipeline are not mAb

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Don’t be the bottle neck

1 MONTH 2 MONTHS 3 MONTHS 4 MONTHS 5 MONTHS 6 MONTHS

Parental Cloning

10L BRX

Early Look Material,

Analytical

Transfectionup to 4 candidates

ambr250

100’s 10’s

Select the

Manufacturin

g Cell Line

Begin Early

Development

(from transfection pool)

# of clones

Don’t be the bottle neck

▪ Comprehensive characterization, high product quality in the lead cell line

▪ Analytical also has to shorten timelines and increase bandwidth

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Bottom Up and Intact & Subunit Mass Approach

Intact & Subunit Mass Analysis PipelinePeptide Mapping Analysis

Native Degly IdeSReducedReduced, Alkylated

Trypsin Chymotrypsin

Forced Degradation Set, Clones, etc.

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Peptide Mapping Auto Workflow with ByosTM

Quantitation

PTMs

MS Files

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Automated Sequence Variant Analysis

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• Replication error

• DNA damage

DNA mutations

Sequence Variant and Causes

• Codon misreading (most common): incorrect

tRNA is recruited during mRNA translation

• tRNA mischarging: incorrect amino acid is

attached to the correct tRNA

mRNA mistranslation

1) Feeney, Lauren. et. al. (2013).. Biotechnology and Bioengineering. 110 (4)

2) Harris, Robert., Kilby, Peter. (2014) Current Opinion in Biotechnology. 30

Unintended change in the amino acids

sequences that could potentially contribute to

efficacy, product safety and immunogenicity.

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Proprietary High Titer Media Improves Productivity

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Sequence Variants Identified

Peptide Position Mod. Names Clone AClone B Clone C Clone D Clone E Clone F Clone G Clone H

TVAAPSVFIFPPSDEQLK 119Pro->Ala/-26.0157 0.26

VYACEVTHQGLSSPVTK 204Pro->Ala/-26.0157 0.24 0.05

ALPAPIEK 330Pro->Ala/-26.0157 0.35 0.10 0.18

ALPAPIEK 332Pro->Ala/-26.0157 0.27 0.13

ASQDINR 30Asn->Ser/-27.0109 0.04 0.39

FNWYVDGVEVHNAK 287Asn->Ser/-27.0109 0.52

NQVSLLCLVK 362Asn->Ser/-27.0109 0.50

Peptide Position Mod. Names Clone 1 Clone 2 Clone 3 Clone 4 Clone 5 Clone 6 Clone 7 Clone 8

ETYGEMADCCAK 139/140Cys->Tyr/3.0327 0.11 0.07 0.07 0.12 0.04 0.10 0.14 0.06

AAFTECCQAADK 217Cys->Tyr/3.0327 0.10

VHTECCHGDLLECADDR 302Cys->Tyr/3.0327 0.22

YICENQDSISSK 314Cys->Tyr/3.0327 0.09 0.05 0.04 0.08 0.03 0.08 0.10 0.04

LKECCEKPLLEK 327Cys->Tyr/3.0327 0.04 0.04 0.06 0.05 0.12

LKECCEKPLLEK 328Cys->Tyr/3.0327 0.04

Cys TGC Tyr TAT

TGT TAC

Pro CCT Ala GCT

CCA GCA

CCG GCG

CCC GCC

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Initial Report on Sequence Variants

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Cys->Tyr Variant Manual Validation

MS1 XIC

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Cys->Tyr Variant Manual Validation

MSMS MSMS

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Sequence Variant Annotated Based on Filter Logic

• Monoisotopic peak

• Peptide score

• Retention time shift

• Explained by common mod

• K/R variance

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Cross validation with multiple enzymes

multiple enzymes

Processing

Reporting

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Cross validation with multiple enzymes

Peptide (GluC) Position Mod. Names Clone 1 Clone 2 Clone 3 Clone 4 Clone 5 Clone 6 Clone 7 Clone 8

MADCCAKQEPERNE 139/140Cys->Tyr/3.0327 0.09 0.05 0.06 0.10 0.04 0.08 0.11 0.05

CADDRADLAKYICE 314Cys->Tyr/3.0327 0.20 0.13 0.13 0.21 0.08 0.19 0.30 0.12

CADDRADLAKYICE 302Cys->Tyr/3.0327 0.11

CCEKPLLE 327Cys->Tyr/3.0327 0.19 0.06 0.07 0.09 0.04

Peptide (Trypsin) Position Mod. Names Clone 1 Clone 2 Clone 3 Clone 4 Clone 5 Clone 6 Clone 7 Clone 8

ETYGEMADCCAK 139/140Cys->Tyr/3.0327 0.11 0.07 0.07 0.12 0.04 0.1 0.14 0.06

AAFTECCQAADK 217Cys->Tyr/3.0327 0.1

VHTECCHGDLLECADDR 302Cys->Tyr/3.0327 0.22

YICENQDSISSK 314Cys->Tyr/3.0327 0.09 0.05 0.04 0.08 0.03 0.08 0.1 0.04

LKECCEKPLLEK 327Cys->Tyr/3.0327 0.04 0.04 0.06 0.05 0.12

LKECCEKPLLEK 328Cys->Tyr/3.0327 0.04

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Spent Media Analysis and Sequence Variant

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Introduction of Spent Media Analysis

Nutrients

Salts

VitaminsTrace

Elements

Amino Acids

• Amino acids and nutrients consumed

• Metabolites and by-products secreted

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Purpose of Spent Media Analysis

• Optimize the growth conditions for clones

• Ensure high quality product (Minimize clipping, PTM)

• Maximize productivity (titer)

• Promote high cell viability

• Reduce/eliminate misincorporations (sequence variant)

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Spent Media LC-MS Workflow (Scheduled MRM)

1290 Infinity II LC

UHPLC separation

AdvanceBio MS Spent

Media HILIC Column

A wide range of compound

classes

SCIEX

QTRAP 6500+

Speed and Sensitivity

P-119-T: Andrew Mahan

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Correlating the C->Y to Amino Acids Depletion

Cystine

Tyrosine

Cystine

Tyrosine

Cys & Tyr Feed

Clone 7 Clone 8

Trend plots show the timepoint the depletion started.

1.0e5

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LC-MS Spent Media Analysis and Clone Selection

Allows for the quantitative measure of different classes of metabolites & amino acids in a 20 min LC-

MS run.

LC-MS based Spent Media Analysis

Verifying of misincorporation observed in peptide map analysis.

Monitoring amino acids and metabolites profiles of different clones.

Implementation into Clone Selection

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Theoretical Intact Reconstruction of mAb HC from Peptide Map Degradation QuantificationExperimental LC-MS mAb HC

❖ Can help determine if modifications are stochastic or not.

❖ Quickly compare quantification between bottom up and intact data.

❖ Can elucidate underlying modifications that contribute to Intact LC-

MS peak shape, particularly combinations of modifications.

❖ Can be used to quickly evaluate analysis parameters.

L

C

HC

Intact Mass Reconstruction with Peptide Mapping Data

P-173-T: Andrew C Nichols

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Data Acq.

Integrating Both Workflows Into One Data Analysis Pipeline

Mass-Spec

Instruments

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

1. Automated data sweep into search software – Vendor Agnostic

2. Extensive Product Variant Search

3. Reduce manual validation time – Define Criteria to flag false-positives

4. Automated export of results

5. Aggregate data with molecule information to build ‘In-house’ knowledge

base

Data Aggregation

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Summary

1. The need for fast sequence variant analysis in cell line development.

2. Automated analysis workflow reduced sequence variant analysis time.

3. LC-MS based spent media analysis provides complimentary information.

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Team

Hirsh Nanda

Andy Mahan

Harsha Gunawardena

Eric Beil

Jeffrey Brelsford

Elsa Gorre

Eric Carlson

Jing Li

Yong J. Kil

Rose Lawler

Andrew Nichols

K.Ilker Sen