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POTENCY ASSAYS FOR PLASMIDBASED VACCINES AND THERAPEUTICS

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Title: POTENCY ASSAYS FOR PLASMIDBASED VACCINES AND THERAPEUTICS


1
POTENCY ASSAYS FOR PLASMID-BASED VACCINES AND
THERAPEUTICS
David C. Kaslow M.D.Chief Scientific
OfficerVical Incorporated
CTGTAC Meeting on Potency Assay 9 February 06
2
Outline
  • Context
  • Pre-biologics pDNA vaccines and therapeutics
  • Potency v strength
  • Potency assays of pre-biologics
  • Key assumptions
  • Potency assay evolution
  • Protein-based potency assays
  • Case study 1 Allovectin-7 FACS
  • Polynucleotide-based potency assays
  • Genetic stability
  • mRNA the immediate given result
  • RT-PCR
  • Case study 2 CMV In vitro In vivo correlate
  • Summary

3
Plasmid Vaccines and Therapeutics Pre-biologic
PRE-BIOLOGIC
Gene sequence Transcription Translation
Post-translational modification
mRNA
AAAAAAA
4
Plasmid Vaccines and Therapeutics Pre-biologic
Strength v Potency
  • Strength ? Potency
  • Strength
  • Determines dose
  • Based on DNA concentration
  • A260 (or equivalent)
  • Potency
  • Specific ability or capacity of the productto
    effect a given result
  • In vitro or in vivo demonstration of
    manufacturing and product consistency

5
Plasmid Vaccines and Therapeutics Pre-biologic
Strength v Potency
PRE-BIOLOGIC
Gene sequence Transcription Translation
Post-translational modification
Strength
mRNA
AAAAAAA
Potency
6
Plasmid Vaccines and Therapeutics Pre-biologic
Strength v Potency
PRE-BIOLOGIC
Strength
A260 (Genetic Stability)
mRNA
RT-PCR
AAAAAAA
Potency
IP/WB or WB ELISA FACS
7
Outline
  • Context
  • Pre-biologics pDNA vaccines and therapeutics
  • Potency v strength
  • Potency assays of pre-biologics
  • Key assumptions
  • Potency assay evolution
  • Protein-based potency assays
  • Case study 1 Allovectin-7 FACS
  • Polynucleotide-based potency assays
  • Genetic stability
  • mRNA the immediate given result
  • RT-PCR
  • Case study 2 CMV In vitro In vivo correlate
  • Summary

8
Key Assumptions-Part 1 of 3
  • The assay development focus should be on in vitro
    assays
  • In vitro responses are less variable than in vivo
    assays
  • In vitro responses have a greater dynamic range
    than in vivo assays

9
Key Assumptions-Part 2 of 3
  • If the immediate biological activity of a
    pre-biologic is to effect transcription of an
    immunogen or therapeutic protein, then the
    immediate biologic result of the product is mRNA.

10
Key Assumptions-Part 3 of 3
  • If a pre-biologic product is genetically stable,
    then
  • there will be no lot-to-lot variability of
    primary nucleotide sequence
  • there will be no lot-to-lot variability of
    primary, secondary or tertiary protein structure
  • the only potential lot-to-lot variability of the
    drug substance is
  • Strength
  • Higher order DNA structure

11
Outline
  • Context
  • Pre-biologics pDNA vaccines and therapeutics
  • Potency v strength
  • Potency assays of pre-biologics
  • Key assumptions
  • Potency assay evolution
  • Protein-based potency assays
  • Case study 1 Allovectin-7 FACS
  • Polynucleotide-based potency assays
  • Genetic stability
  • mRNA the immediate given result
  • RT-PCR
  • Case study 2 CMV In vitro in vivo correlate
  • Summary

12
Evolution in Approach to Vaccine Regulation Two
Paradigms
  • OLD Vaccine potency, as measured in the
    laboratory, is the most important characteristic
    to ensure human efficacy
  • NEW Vaccine potency is only one of the tools
    used to ensure that a manufacturing process
    yields immunobiologicals of quality consistent
    with that of lots proven efficacious
  • From Assays and laboratory markers of
    immunological importance
  • Bruce D. Meade Juan L. Arciniega
  • Laboratory of Methods Development and Quality
    Control
  • Office of Vaccines Research and Review, CBER,
    FDA
  • February 2001

13
Tools for Characterization and Release
  • Strength
  • Nucleic acid concentration (A260)
  • Identity
  • Total pDNA size
  • Restriction fragment length
  • Potency
  • Single point expression
  • Relative potency
  • RT-PCR
  • ELISA
  • FACS
  • IP/WB
  • Cell proliferation
  • In vivo immunogenicity

14
EvolutionPotency Assay Development Stages
Timeline
Pre-clinical
Phase I
Phase II
Phase III
Commercial

Protein-based
or
mRNA-based
Development
Qualification
Pre-Validation
Validation
15
Outline
  • Context
  • Pre-biologics pDNA vaccines and therapeutics
  • Potency v strength
  • Potency assays of pre-biologics
  • Key assumptions
  • Potency assay evolution
  • Protein-based potency assays
  • Case study 1 Allovectin-7 FACS
  • Polynucleotide-based potency assays
  • Genetic stability
  • mRNA the immediate given result
  • RT-PCR
  • Case study 2 CMV In vitro in vivo correlate
  • Summary

16
Allovectin-7 Drug Product
Treatment of chemo-naive metastatic melanoma
patients who have at least one injectable
cutaneous, subcutaneous, or nodal lesion
Sterile liquid, single-vial product, 2 mg/mL,
stored at 2-8ºC Bicistronic HLA-B7 ?-2
microglobulin formulated with a cationic lipid
(DMRIEDOPE)
17
Development and Validation of a Potency Assay
for Lot Release
  • Key regulatory issues
  • HLA-B7 detectable and distinguishable
  • ß2M complexed with HLA-B7
  • HLA-B7 ß2M correct size
  • Development strategy
  • In vitro expression
  • Quantification
  • FACS (Fluorescence Activated Cell Sorting) RP
    (Relative Potency)
  • Identity
  • IP/WB (Immuno-Precipitation/Western Blot)

18
OverviewAllovectin-7 Potency AD Stages
Timeline
Pre-clinical
Phase I
Phase II
Phase III
Commercial
IP/WB
IP/WB
IP/WB
FACS Single point
FACS Single point
FACS Single point
FACS RP Dose response
FACS RP Dose response
Assay Development
Assay Qualification
Assay Pre-validation
Assay Validation
19
FACS RP Assay Qualification
20
Allovectin-7? FACS RP Assay Qualification
  • 8 dose transfection curves for HLA-B7 and ß2M
    each
  • HLA-B7 0, 0.16, 0.31, 0.63, 1.25, 2.50, 3.75,
    5.00 ug/mL
  • ß2M 0, 0.16, 0.31, 0.40, 0.63, 1.25, 2.50, 5.00
    ug/mL
  • Data used for statistical analysis
  • HLA-B7 43 reference curves, 32 pairs
  • ß2M 21 reference curves, 24 pairs
  • Statistical analysis based on
  • Finney, D.J. Statistical Method in Biological
    Assay. Second Edition. 1971. Griffin, London.

21
Typical Dose Response Reference Curves
?T - ?R ?
R 10
22
FACS RP Assay Validation
23
FACS Validation All Parameters Met Acceptance
Criteria
  • Accuracy
  • RP levels /- 35 of the expected recovery
  • Precision
  • Intra-assay 35 CV
  • Inter-assay 35 CV
  • Range
  • Measured vs expected slope for all five RP
    levels 0.70 Slope 1.30
  • Linearity
  • Meets pre-determined suitability criteria for
    slope, intercept, RMSE
  • Specificity
  • Data from precision runs meets suitability
    criteria for /- controls

24
Allovectin-7 CTMRP Results
25
Allovectin-7 IP/WB Assay
ß2M
HLA-B7
MW 1 2 MW 3
MW 1 2 MW
kDa 188 98 62 49 38 28 17 14 6 3
26
Allovectin-7 CTM IP/WB Assay Results
27
Case study 1 Allovectin-7 FACS Summary
  • FACS RP and IP/WB assays developed with FDA
    input
  • Both assays successfully validated and used to
    evaluate Phase 2 CTM retains
  • Phase 3 CTM to be evaluated against reference
    standard /- statistically determined reference
    variability
  • Phase 3 CTM and validation lots will be used to
    determine commercial specifications

28
Outline
  • Context
  • Pre-biologics pDNA vaccines and therapeutics
  • Potency v strength
  • Potency assays of pre-biologics
  • Key assumptions
  • Potency assay evolution
  • Protein-based potency assays
  • Case study 1 Allovectin-7 FACS
  • Polynucleotide-based potency assays
  • Genetic stability
  • mRNA the immediate given result
  • RT-PCR
  • Case study 2 CMV In vitro in vivo correlate
  • Summary

29
Genetic StabilityWhat How
  • Characterization (not release) assay
  • Determined once for a MCB/WCB
  • Stepwise approach completed as part of
    commercial-scale process validation
  • At IND
  • Sequence of MCB/WCB
  • Restriction fragment size pattern on drug
    substance
  • During clinical development
  • Intermediate analysis to identify risk
  • By commercial filing
  • Complete analysis of plasmid backbone at
    full-scale
  • Statistically significant GXP analysis of
    expression cassette at full-scale

30
Genetic StabilityProtocol Overview
Predicted pDNA sequence
MCB MWCB Fermentation Purify pDNA Transform
select colonies pDNA from colonies
Observed pDNA sequence
31
Genetic StabilityExample of Sample Size and
Confidence Level
  • There is a gt95 probability of detecting one or
    more mutations in a sample of 30 independent
    clones if the actual mutation prevalence is gt10.
  • A gt99 probability of detection for a mutation
    prevalence of gt1 would require 459 independent
    clones

32
Outline
  • Context
  • Pre-biologics pDNA vaccines and therapeutics
  • Potency v strength
  • Potency assays of pre-biologics
  • Key assumptions
  • Potency assay evolution
  • Protein-based potency assays
  • Case study 1 Allovectin-7 FACS
  • Polynucleotide-based potency assays
  • Genetic stability
  • mRNA the immediate given result
  • RT-PCR
  • Case study 2 CMV In vitro in vivo correlate
  • Summary

33
Plasmid Vaccines and Therapeutics Pre-biologic
Potency
PRE-BIOLOGIC
mRNA
RT-PCR
AAAAAAA
Potency
IP/WB or WB ELISA FACS
34
Potency AssayRT-PCR RP Assay Rationale
PROTEIN
plasmid
Drug Product
  • Pre-biologic
  • Prepro-biologic

35
Potency AssayRT-PCR Specificity of PCR Primer
In vivo
Transcription
In vitro
Reverse Transcription (RT)
mRNA
Gene-specific reverse primer
TaqMan PCR
36
Outline
  • Context
  • Pre-biologics pDNA vaccines and therapeutics
  • Potency v strength
  • Potency assays of pre-biologics
  • Key assumptions
  • Potency assay evolution
  • Protein-based potency assays
  • Case study 1 Allovectin-7 FACS
  • Polynucleotide-based potency assays
  • Genetic stability
  • mRNA the immediate given result
  • RT-PCR
  • Case study 2 CMV In vitro in vivo correlate
  • Summary

37
Potency AssayPoloxamer-formulated pDNA-based
Vaccine
  • DNA vaccine
  • hCMV gB
  • hCMV pp65
  • Plasmid backbone
  • Optimized Vical design
  • Tested in prior clinical trials
  • Formulation
  • 2 pDNAs (5mg/mL)
  • CRL1005 poloxamer (7.5mg/mL)
  • BAK (0.11 mg/mL)
  • PBS

Bivalent
Vaccine to protect against CMV-associated disease
38
Potency AssayTest Potency Samples
  • Evaluate sample potencies
  • Prepare samples of different potencies based on
    concentration
  • Examined potency ranges
  • 50 to 200
  • Observation model
  • Dose range plots for various potencies conform to
    parallel line model

39
In Vitro / In Vivo Correlation
  • Goal
  • Determine whether in vitro relative potency
    correlates to changes in the CMV pDNA
    vaccine-mediated immune response
  • In vitro Relative Potency (RP)
  • response relative to a reference, using RT-PCR
  • In vivo immune response in mice
  • Anti-gB antibodies by ELISA
  • pp65 T-cell responses using IFN-? ELISPOT

40
In Vitro / In Vivo Correlation
  • Method
  • Evaluate hypo-potent CMV vaccine (80?C
    heat-degraded) versus the 100 potent CMV vaccine
    within the linear range of the in vitro and in
    vivo assays dose-response curves

41
In Vitro / In Vivo Correlation
42
In Vitro / In Vivo Correlation
In Vivo Study Design VCL-CB01
Bilateral IM injection of rectus femoris
administered on Days 0 and 14 Blood collected
prior to 1st injection (Pre-bleed) and Day 26
43
In Vitro / In Vivo Correlation StudyAb Results
Normalized Antibody and Relative Potency Response

44
In Vitro / In Vivo Correlation StudyT-cell
Results
  • High variability
  • Low responses
  • Inconclusive results

45
Case Study 2 CMV In Vitro / In Vivo
Correlation Summary
  • Conclusions
  • Forced degradation of pDNA correlates with a drop
    in relative potency (RP) by RT-PCR
  • Drop in RP correlates to drop in CMV-mediated
    immune response
  • Antibody data appears to correlate best with RP
    and degradation
  • Slope analysis of downward trend statistically
    significant (p0.001)
  • ELISPOT assay - inconclusive
  • Variability too high
  • Response lower than historical data

46
Summary Potency AssayCharacterization Lot
Release
47
Acknowledgements
  • FACS RP Assay Development Team
  • Basil Jones
  • Lana Marjerison
  • Beth Feher
  • Robin Baptista
  • Martha Till
  • Kris Carner
  • RT-PCR RP Assay Development Team
  • Beth Feher
  • Lana Marjerison
  • Basil Jones
  • Mindy Sam
  • Rama Ghatti
  • Rohit Mahajan Ph.D.

Alain Rolland, SVP Prod Dev Jukka
Hartikka Ph.D. Keith Hall, Head QC/AD Mary
Wolch Ph.D. Peggy Lalor Ph.D. Andy Geall
Ph.D. Gretchen Jimenez Ph.D.
Laureen Little Ph.D. Consultant, BioAssays Jan
Callahan Ph.D. - Consultant, Statistics
formerly with Vical
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