Analytical Control Strategy for robust vaccine …...Strategy for robust vaccine development Cristiana Campa WCBP, January 2016 Key elements for a robust Analytical Control Strategy

Analytical Control Strategy for robust vaccine development

Cristiana CampaWCBP, January 2016

Key elements for a robust Analytical Control StrategyBuild strong analytical knowledge beginning with early development, leading to a systematic increase of product and process understanding during life cycle

Refine

Testing

Strategy

during life cycle

Execute method development/ performance

verification

Screen and select analytical technology

Ensure compliance of analytical methods with current product and process requirements

(Analytical Target Profile)

2

Management of product & process expectation through Analytical Target Profile

• Well- defined (possibly fixed) methods are desired since early development to ensure visibility of changes induced during product & process development/ life cycle

Product & Process«clients» expectation

• Minimal change of methods occur during all life cycle, with some resistance to changes or improvementsConsequences

• Product and process requirements are built over time (platform concept is not fully in place for vaccines)

• Always updated analytical technologies are neededgiven vaccines complexity

Challenges for vaccines

• Analytical Target Profile (ATP) is defined with clients since early development, including ideal performances of the analytical methods based on current product and process requirements

Solution

3

Input for ATP- product understanding

Serotype III

Risk assessment for identification of CQAs is important to ensure prioritization of analytical activities

Sialic acid residue is susceptible to hydrolysis; hydrolysis rate depends on temperature and conditions (e.g. pH) sialic acid cleavage changes immunological epitope

Case study Group B Streptococcus glycoconjugate

Focus analytical effort on relevant aspectsExample: for product analytics the input for ATP is Quality Target Product Profile

(Critical Quality Attributes (CQAs) and ranges as applicable)

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Section 1. General Information

Sample Intended Purposes of Measurement Scope Category Output

Drug Product

Measure free sialic acid as CQA and

stability indicator to be monitored in

stability studies

1. Measure a CQA

2. Stability

Quantitative test for a product

related impurity

Section 2. Performance Requirements (related to the most challenging purpose)

SpecificityAccuracy

(meaning of)Accuracy Rationale Precision Rationale

Able to

discriminate

analyte from

matrix signals

Concordance with

the true value80-120%

Adequate to current

knowledge about

effect of sialic acid

cleavage on

immunogenicity

CV≤10%

Adequate for a

stability indicator

method considering

current specs limit

A practical example of specifications settingExtract from ATP

Case study: Group B Streptococcus glycoconjugate- free sialic acid in DP

Note: Business considerations (eg throughput, cycle time, ...) are also included in ATP, but they are not shown here

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Example of analytical technology selection

• 1H-NMR: sialicacid retention in release

Polysaccharide

• Sialic acid not in release specification panel but is a characterization assay; it has been demonstrated that process steps do not alter sialic acid retention attribute

Drug Substance

• HPAEC-PAD: free sialic acid at release and in stability

• Potency assay sensitive to sialic acid loss

Drug Product

Sialic acid

Standard)

Sample

HPAEC-PAD

V. Pinto; F. Berti;

Biomed. Anal. 98

(2014);9-15

Case study: Group B Streptococcus glycoconjugate- free sialic acid

Carefully define methods application/ purposebased on product characteristics and ability to control CQAs from process

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Case study: characterization of Rotavirus

Thorough characterization can be used for methods selection but also to confirm structural features to be monitored -this may need more than one method

•Low resolution of DLS makes it not applicable for real samples with mixed DLP/TLP •EM can discriminate DLP and TLP, and also detect damaged/empty particles, but high number of particles should be observed and sized to get accurate relative abundances •DC and CE are medium throughput techniques suitable for quantitative assay, and able to baseline resolve DLP from TLP

Triple-layered particles containing all 3 protein layers (TLP), as well as smaller, double-layered particles lacking outer capsid proteins VP4 and VP7 (DLP), are detected in preparations of live attenuated rotavirus for vaccination.

Example of analytical technology selection

DLP are non-infectious and it may therefore be of importance to address their abundance vs. TLP in vaccine preparations.

White arrow: full particle; black arrow: damagedparticle; white-dot arrow: whole empty particle.

Negative Staining Electron Microscopyof Rotavirus

DLP TLP

Diameter of Rotavirus double- and triple-layered particles measured by Electron Microscopy, Dynamic Light Scattering, Disc Centrifuge, Capillary Electrophoresis.

Analysis of Rotavirus DLP and TLP by Disc Centrifuge (A) and Capillary Electrophoresis (B)

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Analytical methods used for process understanding may have different requirementswith respect to those used for release/ stability testing,

although they can be applied to the same CQAs

For instance, process «screening» assesses the Process Parameters criticality (i.e., variation of CQA(s) upon changing PP value), not the evaluation of the impact of the change on product quality within specifications (which is the aim of «mapping» studies)

Therefore the typical desired features for methods used for screening studies are- High throughput (to support multivariate studies and to efficiently monitor process)- High precision (to ensure reliability of assessed CQA changes due to PP changes)- High selectivity for complex matrices (to execute testing as close as possible to the investigated step)

ATP for a CQA can incorporate different applications (release/ staibility or process testing),and can potentially be associated to more than one method, if the release/ stabilityapproach is not fully suited for all applications (worse case scenario)

Process Understanding and the ATP

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Method parameters (ATP

requirements for

performance)

Colorimetric sialic acid HPAEC-PAD with CarboPac PA1 HPAEC-PAD with CarboPac PA20Fast

Obtained value ATP requirement Obtained value ATP requirement Obtained valueATP

requirement

Selectivity / Specificity

(Able to discriminate

analyte from matrix

signals)

Analyte not separated

from other

components;

ultrafiltration needed

for complex matrix

phases

Met upon sample UF

Analyte peak

separated from the

other matrix

components

Fully met, no UF

Analyte peak

separated from the

other matrix

components

Fully met, no UF

Accuracy

(80-120%)

82-100%

(pre-validation data)Met

97-108% (pre-

validation data)Met

95-99%

(validation data)Met

Precision

(CV < 8%)

2-10%

Possible variability

between different lots

and analyses performed

in long different time

(pre-validation data)

Not fully metCV 3-10%

(pre-validation data)Not fully met

CV 3%

(validation data)Met

Cycle Time

(< 1 day )

2 hours (no

ultrafiltration)5 hours

(ultrafiltration required)

Met 10-12 hours Met 4-5 hours Met

Throughput

(NLT 8 samples)Up to 20 Met Up to 15 Met Up to 30 Met

Sample volume required

for the analysis1 ml - 20 µl - 5 µl -

Product development stages

Case study: Group B Streptococcus glycoconjugate- saccharide content

F. Merangolo, S. Giannini, M. Gavini, S. Ricci, C. Campa, LCGC Applications of Ion Chromatography (2015) 9

Process Understanding and the ATP


Refine

Testing

Strategy

during life cycle


verification




10

After analytical technology selection, risk of failure can be limited through:

Method development including QbD elements (eg applying a risk- basedapproach and, possibly, multi-variate studies), with final verification of performances, to be compliant with ATP

Establishment of a robust reference standard strategy (thoroughcharacterization, stability studies/ definition of storage conditions, use for method performance monitoring)

Note: these activities are critical also to ensure adequate bridging betweenmethods, if needed during life cycle management (eg for introduction of new technologies, or if ATP is refined after QTPP revision duringdevelopment)

Method development and reliability assessment

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Method development including QbD elements

S. Orlandini, S. Pinzauti, S. Furlanetto: Anal. Bioanal. Chem. 405 (2013) 443-450

Analytical Target Profile &

method selection

Quality Risk Assessment

Knowledge SpaceInvestigation by DoE

Design SpaceResponse Surface Metodology

Method Control

Working PointsRobustness

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Case study: Quality Risk Assessment (QRA) - UPLC for % adsorption of protein on an aluminum surface

Ishikawa diagram (fishbone) for screening the method parameters andfor identifying the critical process parameters (CPP) to be furtherstudied by DoE.

Screening study of the effects of chromatographic parameters onchromatographic performances


13

287-

953

Por

B

Por

A

936-

741

961c

AU

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

1,10

1,20

1,30

Minutes

3,00 3,10 3,20 3,30 3,40 3,50 3,60 3,70 3,80 3,90 4,00 4,10 4,20 4,30 4,40 4,50 4,60 4,70 4,80 4,90 5,00 5,10 5,20 5,30 5,40 5,50 5,60 5,70 5,80 5,90 6,00

Pro

tein

I

Pro

tein

II

Pro

tein

III

Pro

tein

V

Pro

tein

IV

Case study: knowledge space- UPLC for % adsorption of protein on an aluminum surface


Asymmetric matrix (based onFree-Wilson model) forinvestigation of the KnowledgeSpace (KS) and to obtainpreliminary information on theeffects of the factors on methodperformance (eg peakresolution and area).

Re

solu

tio

nP

rote

in I-

Pro

tein

II

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Case study: knowledge space - UPLC for % adsorption of protein on an aluminum surface


Investigated performance indicators

R1: Protein I – Protein II Resolution

R2: Protein II– Protein III Resolution

R3: Protein III – Protein IV Resolution

R4: Protein V – isoform Resolution

Study outcome:

Parameters impacting peak resolution and areas & best conditions found at this stage:

- Column type: C4 pore best column

- % start Acetonitrile: 34% best value based on screening studies (under verification -design space assessment)

- Ramp time: 4 or 6 min best values based on screening studies (under verification -design space assessment)

- Column temperature: 60°C best value based on screening studies (under verification –design space assessment)

A1: Protein II

A2: Protein III

A3: Protein IV

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Refine

Testing

Strategy

during life cycle


verification




16

Methods life cycle

Analytical testing strategy evolves with process and product knowledge,

and doesn’t stop with Regulatory Approval.

Post-Licensure changes in the analytics:

may be driven by several factors focused to maintain the best control on the product and process

must consider pros and cons for total impact on strategy

Pro

s • Performance improvement (robustness, cycle time, throughput, cost)

• Innovation advancing• Harmonization between

labs/sites• Ethical Change from in vivo to in

vitro• Deepening product Knowledge

Ch

alle

nges • Equivalence demonstration and

Impact on specification

• Regulatory variations required

• Alignment with OMCLs

• Internal resistances

• Bridging with historical data

• Use for stability studies

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– A test was required to assess carbohydrate content in polysaccharides.

– The Resorcinol assay is based on the acidic dehydration of monosaccharides (hexoses) to 5-HMF.

– 5-HMF reacts with Resorcinol to generate a chromophore whose concentration is determined using a UV-visible spectrometer (usually 430nm).

– In its apparent simplicity, this assay hides several drawbacks.

– The generation of 5-HMF is continuous until exhaustion of the carbohydrate => the signal evolves.

– The kinetic of a monosaccharide is not necessarily the same than a polysaccharide.

– It will have consequences on the accuracy and on the standard choice

– There are other methods allowing to achieve more information with respect to colorimetric approach

5-HMF

Resorcinol

Hexoses

Chromophore

NMR vs colorimetric – Pneumococcal polysaccharide 23F

Methods life cycle

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Easy sample preparation

Accurate

Specific

Precise

All in one

Easy Standard management

Inte

rna

l S

tan

da

rd

CPS

Acetate

Methyl

Pentose

EtOH

Silicon

Anomeric

RegionH

DO

Identity

Aromatic Amino Acid

R/DNA Base

Phenol

NMR vs colorimetricPro: innovation 1H Nuclear Magnetic ResonanceNMR vs colorimetric – Pneumococcal polysaccharide 23F

Methods life cycle

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Analytical Control Strategy & Life Cycle

Analytical Target Profile

Analytical Methods Screening/ Development/ Refinement (for release/ stability & characterization)

Ph IIIPh IIPh IDiscovery Preclinical Registr.Launch

Reference standard (selection, characterization and stability)

Analytical methods qualification/ validation

Criticality confirmation studies for quality attributes and Physico- chemical comparability

Analytical Methods Screening/ Development/ Refinement (for process understanding)

Refinement

QTPP & process

requirements

Analytical Methods Life cyclemanagement/ development continuity

Refinement

Characterization

efforts since

early

development

Final ATP Submission

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Challenges & Opportunities

For vaccines, product/ process requirements are defined/ refined over time with consequent need to change ATP and, potentially, selected methods

o Optimization is ensured through screening of orthogonal methods when product / process requirements are under assessment (this is also needed to minimize risks of undetected issues/ identify CQAs)

o Extensive characterization efforts are needed since early development. Apparent investment of time/ resources is compensated by robustunderstanding and control of manufacturing aimed at ensuring product quality.

After fixing product / process requirements (eg typically in late development/ commercial phase), with a final/fixed ATP, it is important to update analytical technologies, to ensure the best testing approach for vaccines at any stage of life cycle.

o Regulatory filing could be effected upon possibility to submit Analytical Target Profile.

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Acknowledgement

Amin KhanBill EganDominique LemoineDaniela StrangesGhislain DelpierreThomas JacquesLuca NompariAuthors of the mentioned publications

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Documents

Analytical Control Strategy for robust vaccine …...Strategy for robust vaccine development Cristiana Campa WCBP, January 2016 Key elements for a robust Analytical Control Strategy