QPCR in QPCR in Biopharmaceuticals & Biopharmaceuticals &

Current IssuesCurrent Issues

Chaminda SalgadoChaminda SalgadoHead of PCR ServicesHead of PCR Services

SummarySummary

Biopharm lifecycle● Candidate Plasmid Selection● Cell Line Selection● Cell Banking● Process Support● Potency/Stability testing● Tox Studies● Clinical Trials● Post launch diagnostics

Issues

A bit about me…A bit about me…

● 1996 CBD Porton Down Scientific OfficerChemical & Biological DefenceGene Probes- Detection

● 1999 GlaxoSmithKlinePrincipal ScientistBPCEDD (Biopharmaceutical Center of Excellence Drug Discovery)

● 2008 NDA AnalyticsHead of PCR Services

Candidate plasmid selectionDNA vaccines, Proteins (mAbs, dAbs, fAbs…)

● Promoter● Humanisation● Codon optimisation

Selection using RT-QPCR based on the highest expressors (mRNA transcripts)

Cell line selectionCell line selection

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2H3 (0) 2H3 (60) 4H8(0) 4H8 (60)

mRN

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heavy mRNAAntibody

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mRN

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light mRNAAntibody

Choosing the right target, and transcript can correlate with translated protein

Cell BankingCell Banking● Virus testing

Test Method28 day 4-cell line in vitro assay (incorporates 324K cells for detection

of Minute Mouse Virus)Adventitious viruses

In vivo assays (adult and suckling mice, guinea pigs and embryonated eggs)

Extended S+L- focus assay on mink lung cellsReverse Transcriptase, QFPERTTEMCo-cultivation with a human cell line or other speciesIn vitro assay for bovine virusesBovine VirusesQPCR and/or in vitro assay for bovine polyomavirus

Porcine Viruses In vitro assay for porcine viruses

Hamster Antibody Production (HAP) testSpecies Specific VirusesLymphocytic choriomeningitis Virus (LCMV) challenge test

Retroviruses

Process ValidationVirus Clearance Validation

● Partitioning by selective absorption● Inactivation● Size Exclusion + Mechanical inactivation

Virus spike Quantify OutputOrthogonal Process Steps

Robust Clearance (LRV > 4 log TCID50/ml):Low pH (inactivation of acid labile model virus)Nanofiltration (removal of small non- enveloped viruses)

Additional Clearance (LRV > 1 log TCID50/ml):Column’s (partitioning based on charge or functional ligand)Ion Exchange Filter

StabilityStability

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Unstable

YeildRNA transcriptDNA

Non genetic Phenotypic drift?

rgDNA ClearancergDNA Clearance

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log10 Quantity (pg/ml)

Ct

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Process Step

rgD

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Batch 01Batch 03Batch 04Batch 05Batch 06Batch 07

1fg – 10ng

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Antibody conc [µg/mL]

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5h incubation 3h incubation

QPCR Bioassay for protein based products

• Candidate Biomarkers involved in intracellular pathways can be identified using Arrays

• RT-QPCR subsequently used to validate and quantify expression of the biomarkers for potency and stability indicating assessment.

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ng tranfected Plasmid

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A. Cell DNA compared to transfection load -10

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mRNA in cell

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QPCR Bioassay for DNA Vaccine

Real-time PCR in BPCEDD

Product Stability

• Potency (RT-QPCR)

Cell line Stability/Selection

• Quantitative Gene Expression

• DNA copy No.

Candidate Selection

• Potency of candidate vectors following optimisation

Process Validation

• Host cell DNA/RNA clearance

• Virus clearance

Master Cell Bank testing

• Virus

• Mycoplasma

Product issues

• Replication incompetent reversion

• Sterility

Tox

• Bio distribution

Late stage and beyondLate stage and beyondIn the Clinic● Transcriptomics to determine drug effects on gene regulation

After market● Companion Diagnostics – genetic profile to determine suitability

of a drug.● Health care costs will be driven down through improved prescribing and

compliance, and reduction in ADRs. ie. DxS:K-Ras, mutations in VKORC1, and warfarin.

Issues

StandardisationStandardisation

● Methods ● Sample preparation● Targets used in normalisation for relative expression● Absolute Quantitation- NO DNA Gold Standard!! OR

Standardised means to quantify the QPCR Reference!

● AnalysisData has to be comparable- it’s a regulatory must!

● Subjective threshold vs 2nd derivative maxima algorithm● Baseline normalisation● Algorithms/methods for relative quantitation● Realtime kinetic efficiency.

Sample preparationSample preparation

● Variable extraction efficiencies due to matrix● Variable extraction efficiencies due to load● NAT guidance 80% yield…relevance to QPCR?● Extraction technologies to standardise on % Yeild

as a measure of comparison

02468

1012141618202224

1 10 100

Log [Standard Copy Number]

Req

uire

d R

eplic

ates

ReplicatesReplicates

CopyNumber

ReplicatesRequired

1 21

2 11

5 5

10 3

50 1

100 1

Poisson Distribution Model

• Software ignores blank/negative data !

Raw dataRaw data

Start baselineStart baseline

BaseliningBaselining

BaseliningBaselining

Cp/Ct calling

•Threshold, Fit-Points/Threshold, 2nd der max.

•Marketing gimmick vs truth

Individual baselining

•Critical for high throughput!

Efficiency correction?Efficiency correction?

?

TrainingTraining

Std Curve

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log10 Quantity

Ct

Series1

-3.32

-2.25140 %

100 %

6 cycle difference 26 = 64

What’s missing?What’s missing?

• Currently most of the available data is ignored in the final analysis

• Currently most base PCR efficiencies according to separate reactions

• A lot of potential data is lost due to fluorescent noise.

• More investment into realtime kinetic algorithms for both efficiency determination, QC criteria, and non subjective Cycle calling.

• Base lining algorithms.

• Investment into gated detection and time resolved chemistries.

Please help!Please help!

Put individual baselining & truthful cycle calling at the top of the list

AcknowledgmentsAcknowledgments

NDA Analytics● Gerry Maxwell

GlaxoSmithKline● Jean Engela● Anja Grohnert● Phil Henwood● Mike Aylott

University of Sussex● Kyle Morris

Enigma Diagnostics● Martin Lee

BackupBackup

Technical InnovationTechnical Innovation

● Reagents●Enzymes etc- speed and utility are constantly

improving.● Time delay chemistries

● Instrumentation●Speed + combined sample prep. (<30min from raw

sample)●Gated/time resolved detection●Non-subjective software algorithms

Experimental vs PoissonExperimental vs Poisson

● Both models agree that as copy number per volume is decreased, so variation is increased. At the low end due to poisson distribution.

● Increasing replicates at the lower end brings the observed average values closer to the expected values

What I’m trying to get at…What I’m trying to get at…

Applicable well beyond the realms of real time – any assay using a standard curve for absolute quant.

Replication of standard curve points (and where possible samples)

should be increased at lower copy numbers.

Reliability of abs quant below 100 copies should be questioned.