View
6
Download
0
Category
Preview:
Citation preview
Analytical Control Strategies: from molecular understanding to CQAs, specifications and lifecycle management.
Garry B. Takle, Ph.D.Biologics and Vaccines AnalyticsMerck Manufacturing Division: MSD
Presentation Outline
• Analytical Control Strategy Concepts• Molecular/biophysical/biochemical
understanding • CQAs• Analytical Specs• Potency Method examples• Analytical Lifecycle Strategy
ICH Q10 Pharmaceutical Quality System:Analytical aspects
• Objectives– Product realization– Control– Continual Improvement
• Product Lifecycle– Pharmaceutical Development
• Analytical method development– Tech transfer
• Development through to manufacturing• Transfer of analytical methods (AMT)
– Commercial• Control of Materials• QC/QA• Release
– Discontinuation
Control Strategy Definition• Definition: A planned set of controls,
derived from current product and process understanding, that assures process performance and product quality (ICH Q10)
– Parameters and attributes related to drug substance and drug product materials and components
– Facility and equipment operating conditions
– In-process controls– Finished product specifications– Associated methods and frequency of
monitoring and control• Control strategy development is
iterative; modified throughout product lifecycle, due to changes in:
– Process– Methods– Product Understanding
Target Product Profile
Critical Quality Attributes
Risk Assessment(quality risk
Management)
Design Space(product/processUnderstanding)
Control Strategy
ContinuousImprovement
Q8(R2) Pharmaceutical development
• QbD concepts– Quality Target Product Profile (QTPP)
• Analytical Target Profile– Critical Quality Attributes (CQAs)– Manufacturing process (assay)– Identify Manufacturing Process Parameters affecting
CQAs– Control strategy
IgG1 potential heterogeneity
Fabian Higel, Andreas Seidl, Fritz Sörgel, Wolfgang FriessN-glycosylation heterogeneity and the influence on structure, function and pharmacokinetics of monoclonal antibodies and Fc fusion proteinsEuropean Journal of Pharmaceutics and Biopharmaceutics, Volume 100, 2016, 94–100
Modification Example Likely source
Glycosylation site at Asn, glycoform variation (e.g.
sialylation)Occurs during fermentation
C terminus cleavageOccurs during fermentation,
catalyzed by carboxypeptidase
C-terminal α amidation Occurs during fermentation, catalyzed by PAM
N-terminal glutamate (LC) Sequence
N-terminal glutamine (HC) Sequence
N-terminal pyroglutamate (HC) Occurs during fermentation, downstream and/or storage
Oxidation of MetOccurs during fermentation,
downstream processing, and/or storage
Deamidation of: AsnOccurs during fermentation,
downstream processing, and/or storage
McAb Post-Translational Modifications Affecting Charge Distribution - Purity
Analytical Characterization Employs Multiple Orthogonal Techniques
Intact Mass
Peptide MapLC/MS/MS
NR PeptideDisulfide Map
Free Sulfhydryl
Far UV CD
FT-IR
Near UV CD
Fluorescence
DSC
CompetitiveBinding ELISA
Cell based Potency
Biacore Kinetics& Affinity
FcRn, FcGR
ADCC / CDC
37C
55C Stressed
Forced oxidation
pH shift
HP-SEC
NR CE-SDS
R CE-SDS
DLS
SV-AUC
Particle Count -Light Obscuration
Particle Size & Morphology- MFI
HP-IEX
cIEF
Peptide MapLC-MS
HILIC-HPLCGlycan mapGal, Man, Afuco
Peptide MapLC/MS/MSAglyco
HILIC-HPLC Glycan MapSialic Acid
Intact Mass
Photostability
HP-HIC
RP-HPLC
Thorough product characterization – including variants and impurities
• Isolation and Characterization HP-IEX Species
A typical chromatogram using the semi-preparative column and collection scheme
Q6B: Specifications
• Drug Substance– Appearance and
description– Identity– Purity and
Impurities• Process related• Product related
– Potency– Quantity
• Drug Product− Appearance and
description− Identity− Purity and
Impurities− Potency− Quantity− General tests− Unique tests
Virus-Like Particle(~20,000 kDa)
L1 Capsomere(Pentamer)(~280 kDa)
5 × L1
L1 protein(55 or 57 kDa)
(Crystal structure coordinatescourtesy of Prof. S. C. Harrison,
Harvard University)
~ 3 nm ~ 10 nm~ 60 nm
GARDASIL®9 Based on Human Papillomavirus (HPV) Virus-Like Particle (VLP)
~72 × L1Capsomeres
• Vaccine based on HPV major capsid protein, L1, self-assembled into virus-like particles (VLPs)
• Complex structure, but well characterized
Modern Vaccines Amenable to Characterization; Robust Control Strategy Achievable
Physicochemical Properties Biological ActivityIdentity
Purity Impurities Contaminants Quantity
Primary Structure• Peptide Map (Digestion,
MALDI-MS)• Deamidation (Isoquant)• Denatured Free Thiols
Secondary Structure• CD• FTIR
Tertiary - Quarternary Structure• Native Free Thiols• Thermal Unfolding (DSC)• Morphology (TEM, CryoEM,
AFM)• Monodispersity (TEM, SEC-
HPLC)• Aggregation (DLS, Cloud
Point, SPR)
Other• Aluminum• PS-80• pH• Completeness of adsorption
Antigenicity• In Vitro Relative
Potency (sandwich ELISA)
• Solution Antigenicity (competitive ELISA – IC50)
• Epitope Mapping (SPR)
• Epitope-specific antigenicity (SPR)
• In Vivo Potency (mouse ED50)
• Purity (SDS-PAGE)
Host-Cell• Protein
(Western Blot)• Nucleic acids
Product-Related• Resistance to
Proteolysis (SDS-PAGE)
Process-Related• Protease
• Sterility• Endotoxin
• Protein concentration
Primary and Secondary
Tertiary and Quarternary Alum AdsorbedC
ompl
ex S
truc
ture
http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Scientific_Discussion/human/000703/WC500021140.pdfZhao, et al (2013) Cell Press 31(11): 654-663; http://www.tandfonline.com/doi/pdf/10.4161/hv.27316
Blue text = select release CQA tests
Release testing: Drug Substance/ Drug Product
• Drug Substance• Protein Concentration• Percent Purity/Percent Intact
Monomer • SDS-HPSEC• RNA• DLS• IVRP• Identity• Sterility• Endotoxin• Aluminum• pH • Characteristics• Completeness of Adsorption
• Drug Product• IVRP• Identity• Sterility• Endotoxin• Aluminum• pH• Completeness of
Adsoprtion• Package Identity• Volume of Fill• Syringeability
• Life cycle of a product and analytical assays• Unlikely a single method assay platform could be used between
products or even between development phases for a single product• As products or assays are better understood, assays may be added,
removed, or refined to best demonstrate product quality, consistency, and potency. As product development proceeds, an improved or more relevant assay can be developed.
Expectations for Potency Assays
14
• Potency method requirements – Reflect our understanding of MOA (binding in early stage, functional CBA in later
stages)– Specific to product– Robust, fit for intended use – Linear response for an appropriate range– Control of CQA
• Stability indicating (to relevant degradation pathways)
Potency method requirements
15
Three assays were developed to assess potency for an inhibitory immunomodulator based on the mechanism of action
• Competitive binding ELISA• CHO cell based competitive binding ELISA• T-cell/antigen presenting cell based Functional Assay
16
Competitive Binding ELISA
• Detection of bound ligand with biotinylated AB, SA HRP and Chemiluminescent substrate
• Inhibition curve• Sample vs reference• 4-PL1 fit and PLA2 analysis• Relative potency (% of reference)
17
Receptor
Ligand
Molecule
Plate Bound
ELISA detects the presence of bound ligand
14-PL: 4-parameter logistical fit2 PLA: Parallel Line Analysis
Cell Based Competitive Binding ELISA
• Receptor expressed on cell surface
• Molecule competes for binding in the presence ligand
• Detect bound ligand with biotinylated AB, SA HRP and Chemiluminescent substrate
• Inhibition curve• Sample vs reference• 4-PL fit and PLA analysis• Relative potency (% of reference)
18
Receptor
Ligand
Molecule
Cell surface
ELISA detects the presence of bound ligand
Functional Cell-based Assay
• Receptor/ligand interaction leads to inhibition of cytokine production
• Molecule blocks receptor/ligand engagements and removes inhibition of cytokine production and re-activates the T-cells
• Detection of cytokine by ELISA• Sample vs reference• 4-PL fit and PLA analysis• Relative potency (% of reference)
19
Receptor
T-Cell surface
Molecule
APC Cell surface
Ligandcascade of events lead to increased cytokine production that is quantified
□ Reference material, o isotype control, ∆ cell control
Establishment of System Suitability Acceptance Criteria
20
Upper Asymptote (UA)
Lower Asymptote (LA)
RS Slope
Control/Sample SlopeRoot Sum of SquaresError (RSSE)
UA/LA Ratio
Side-by-side release results, 3-way analysis
• Geometric mean potency +/- 95% confidence limits. • Similar results are obtained with all three assays and all geometric
mean potencies are within 80 to 120% of reference
Potency Assay lyo Reagent controlCritical reagent Time post
reconstitutionTime post initialreading (min)
Nominal/expected protein concentration (ug/mL)
Actual determined protein concentration
Assay pass rate (%)
Vial A 5 days0 100 66.6
34.527 100 88.431 100 94.2
Critical reagent Time post reconstitution
Time between readings (min)
Nominal/expected protein concentration (ug/mL)
Actual determined protein concentration
Assay pass rate (%)
Vial B1 day
0 100 73.8
0 and 33
2 100 79.66 100 53.28 100 41.410 100 53.7
2 days0 100 122.42 100 84.9
Assay Lifecycle Strategy
• Legacy Vaccines Panel• Phase 1: Scope Definition and General Assay Review
– Excel Workbook approach– 34 method attributes
• Phase 2: Method Improvement• Phase 3: Continuous Review
23
24
Phase 1 General Assay Review:Strategy & Outcomes
Strategy/Principles
• Definition of scope and timelines.• “Divide and Conquer” – define broad analytics commercialization team.• Collaboration with QC.• Comprehensive concurrent approach vs linear.• Standardized Numeric Output (Workbook).• Drop Down menus – Pre-populated – Simple.• Rapid Metrics Generation: brings reagent, personnel, equipment,
validation, performance monitoring etc. issues into focus.• Real-Time Status/Progress Report• Outcomes:
– Completed in 6 months – Completed Workbooks and Final Report archived.– Definition and prioritization of Phase 2 efforts
Phase 2• 2nd Gen methods
– Invalid rate reduction (potency method)– Lead time reduction (rapid micro method)
• Derisk reagents– Dual source– Reagent quality
• Instruments– Redundancy– Obsolescence– Replacement
• Method precision improvements– Reduce testing burden.
• Replace animal model based methods.• Industry and regulatory expectations
– Validation
Phase 3 Continuous Review
• Validation status• Assay performance monitoring• Regulatory strategy/change control• Process performance monitoring• Comparability
Opportunities – PAT/nRTRTUse of biomarkers for process optimization.
– Protein, nucleic acids, metabolites– Newer technologies and real time measurements– Numerical score associated with optimal
potency/yield– Increased process understanding and control– Higher yields
FDA Emerging Technology Draft Guidance (2015)
nRTRT
• Overall E2E release strategy.• MAMs • Longest lead time assays – DS.
– In vitro/in vivo assays– Mycoplasma/micro
Acknowledgements
• Athena Nagi• Peg Criswell• Jennifer Dashnau• Gargi Maheshwari• Parimal Desai• The entire Biologics and Vaccines Analytics
(BVA) team• Other MSD colleagues (too many to list)
Recommended