quality by design - qbd model for "tablets" © by shivang chaudhary
TRANSCRIPT
QUALITY BY DESIGN FOR FORMULATON DEVELOPMENT & PROCESS OPTIMIZATION OF COMPRESSED SOLID ORAL DOSAGE FORM-TABLETs
A MODEL
© Created & Copyrighted by Shivang Chaudhary
© Copyrighted by Shivang Chaudhary
Formulation Engineer (QbD/PAT System Developer & Implementer) MS (Pharmaceutics)- National Institute of Pharmaceutical Education & Research (NIPER), INDIA
PGD (Patents Law)- National academy of Legal Studies & Research (NALSAR), INDIA
+91 -9904474045, +91-7567297579 [email protected]
https://in.linkedin.com/in/shivangchaudhary
facebook.com/QbD.PAT.Pharmaceutical.Development
Designed & Developed by
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
© Created & Copyrighted by Shivang Chaudhary
Aim
• Stable & Therapeutic Equivalent (Pharmaceutical Equivalent + Bioequivalent) IR Generic Tablet Formulation
• Robust & Rugged Reproducible Manufacturing Process
• with a Control Strategy that ensures the quality & performance of the drug product as per Quality by Design
To Develop :
Project
Goal
QbD & Its Elements
Definition of QTPP
Determination of CQAs
Quality Risk Assessment of CMAs & CPPs
DoE & Development of Design Space
PAT & Development of Feedback Controls
Implementation of Control Strategy
© Created & Copyrighted by Shivang Chaudhary
© Created & Copyrighted by Shivang Chaudhary
iNSIDES
Targeting
Bullets
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
© Created & Copyrighted by Shivang Chaudhary
Quality by Design (QbD) A SYSTEMATIC approach • to development • that begins with predefined objectives and • emphasizes product and process understanding • and process control,
• based on sound science and quality risk management.
Quality The suitability of either a drug substance or a drug product for its intended use.
What is QbD?
Note: “Quality doesn’t costs, it always pays” & “Quality does not happen accidently, Quality must be designed in by planning, not tested in afterwards.“
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Define QTPP (Quality Target Product Profile) On the basis of THERAPEUTIC EQUIVALENCE for Generic Drug Product = PHARMACEUTICAL EQUIVALENCE (same dosage form, route of administration, strength & same quality) + BIO-EQUIVALENCE (same pharmacokinetics in terms of Cmax, AUC to reference product)
Determine CQAs (Critical Quality Attributes) Considering QUALITY [Assay, Uniformity of Dosage units,], SAFETY [Impurities (Related substances), Residual Solvents, Microbiological limits], EFFICACY [Dissolution & Absorption] & MULTIDISCIPLINARY [Patient Acceptance & Compliance]
Designing of Experiments (DoE) & Design Space For SCREENING & OPTIMIZATION of CMAs & CPPs with respect to CQAs by superimposing contour plot to generate OVERLAY PLOT (Proven acceptable Ranges & Edges of failure ) based upon desired ranges of Responses
Process Analytical Technology (PAT) For continuous automatic IN LINE analyzing & FEED BACK controlling critical processing through timely measurements of CMA & CPAS by INLINE ANALYZERS WITH AUTO SENSORS with the ultimate goal of consistently ensuring finished product quality with respect to desired CQAs
Implementation of Control Strategy For CONTROLS OF CMAs, CPPs within Specifications, by Real Time Release Testing, Online Monitoring System, Inline PAT Analyzers based upon previous results on development, Scale Up. Exhibit/ Validation batches.
Quality Risk Assessment of CMAs & CPPs with CQAs (1) RISK IDENTIFICATION: by Ishikawa Fishbone (2) RISK ANALYSIS by Relative Risk based Matrix Analysis (3) RISK EVALUATION by Failure Mode Effective Analysis
© Created & Copyrighted by Shivang Chaudhary
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
QUALITY TARGET PRODUCT PROFILE (QTPP) A Prospective Summary of • the quality characteristics of a drug product • that IDEALLY will be achieved to ensure the desired quality,
• taking into account Safety & Efficacy of the drug product. Note: QTPP will be finalized - • On the basis of Therapeutic Equivalence for Pharmaceutical Abbreviated New Drug Application (ANDA- Generics)=
Pharmaceutical Equivalence (same dosage form, route of administration, strength & same quality) + Bio-Equivalence (same pharmacokinetics in terms of Cmax, AUC;
• On the basis of Therapeutic Safety & Efficacy for Pharmaceutical New Chemical Entities (NCE-Innovator) / New Drug Applications (NDA-Novel Drug Delivery Systems as compared to already approved & available conventional dosage forms)
What is QTPP?
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Pharmaco-KINETICS
Fasting Study and/or Fed BE Study 90 % confidence interval of the PK parameters, AUC0-t, ,
AUC0-∞ and Cmax, should fall within bioequivalence limits of 80-125 with reference product
Bioequivalence requirement needed
to meet required rate & extent of drug absorption
EASE OF STORAGE & DISTRIBUTION
Can be stored at real time storage condition as a normal practice with desired stability & can be distributed
from the manufacturer to end user same as per Reference Product.
Required to handle the product easily with suitable accessibility
STABILITY & SHELF LIFE Should be stable against hydrolysis, oxidation, photo degradation & microbial growth. At least 24-month
shelf-life is required at room temperature
Equivalent to or better than Reference Product shelf-life
PATIENT ACCEPTANCE & PATIENT COMPLIANCE
Should be suitably flavored & colored for possessing acceptable taste ( in case of soluble/ dispersible/
effervescent tablet) similar with Reference Product. Can be easily administered/used similar with
Reference Product labeling
Required to achieve the desired patient acceptability & suitable compliance
QTPP Element Target Justification
Dosage FORM Tablets Pharmaceutical equivalence requirement:
same dosage form
Dosage DESIGN Immediate Release / Modified Release
Formulation with/ without Coating Immediate release design needed to meet
label claims
ROUTE of Administration Oral Pharmaceutical equivalence requirement:
same route of administration
Dosage STRENGTH x mg Pharmaceutical equivalence requirement:
same strength
Drug Product QUALITY
ATTRIBUTES
Description
Pharmaceutical equivalence requirement: Must meet the same compendia or other applicable reference standards (i.e., identity, assay, purity & quality).
Assay Uniformity Impurities Dissolution Microbiological Limits Water Content Residual Solvents
PRIMARY PACKAGING
Plastic Container & Closure/ Metal Blister system should be qualified as suitable for drug product with desired
appropriate compatibility & stability. Should protect product from heat, moisture,
oxygen, light & microbial attack.
Required to achieve the target shelf-life and to ensure product integrity during transportation, storage
& during routine-use
PATIENT’S POINT OF VIEW
PHYSICIAN”s POINT OF VIEW
PHARMACIST’s POINT OF VIEW
Quality Target Product Profile (QTPP) of Tablets
© Created & Copyrighted by Shivang Chaudhary
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Critical Quality Attribute (CQA) A CQA is a • Physical, • Chemical, • Biological, or • Microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality. Note: CQAs are generally associated with the drug substance, excipients, intermediates (in-process materials) & Finished drug product. On the basis of Quality [Assay, Uniformity of Dosage units, Redispersibility, Reconstitution time, Aerodynamic property], Safety [Impurities (Related substances), Residual Solvents, Osmolarity & Isotonicity, Microbiological limits, Sterility & Particulate matter], Efficacy [Diffusion, Dissolution & Permeation] & Multidisciplinary [Patient Acceptance & Compliance].
What is CQA?
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Assay 90.0 to 110.0 % of
labeled claim. Yes
Assay variability will affect SAFETY AND EFFICACY. Process variables may affect the assay of the drug product. Thus, assay will be evaluated
throughout formulation and process development.
Weight Variation/ Content Uniformity
Conforms to USP <905> Uniformity of Dosage Units: 90.0-110.0 % of
labeled claim with AV: NMT 15.0; RSD : NMT 5.0%
Yes Variability in content uniformity will affect SAFETY AND EFFICACY.
Both formulation and process variables may impact content uniformity, so this CQA will be evaluated throughout formulation and process development.
Water Content As per In house specification according to stability data
Yes If drug is sensitive to moisture, it will impact stability & ultimately SAFETY &
EFFICACY. If drug is not sensitive to moisture, it will not impact stability
Impurities As per
ICH Q3A& Q3B
Yes
Degradation products can impact SAFETY and must be controlled based on compendia/ICH requirements or reference product characterization to limit patient exposure. Formulation and process variables may impact degradation products. Therefore, degradation products will be assessed
during product and process development.
Residual Solvents
Conforms to USP <467> option 1
Yes* Residual solvents can impact SAFETY, but as it will be primarily
controlled during drug substance & drug product manufacturing by drying, Therefore, Formulation and Process variables are unlikely to impact this CQA.
Microbiological Limits
Conforms to USP <61 & 62>
Yes* Microbial Load will impact patient SAFETY, but as it will be primarily
controlled during drug substance & drug product manufacturing, Therefore, Formulation and Process variables are unlikely to impact this CQA.
Dissolution
NLT X % (Q) of labeled amount of drug is dissolved in y Minutes in
pH Z buffer, 900 ml, Apparatus I/II, 50/100 rpm.
Yes Failure to meet the dissolution specification can impact bioavailability
(EFFICACY). Both formulation and process variables affect the dissolution profile. This CQA will be investigated throughout formulation and process development.
Quality Attributes of Drug Product
Target Is this a CQA?
Justification
Physical Attributes
Color and shape should acceptable to the patient. No visual tablet
defects should be observed. Yes To ensure PATIENT ACCEPTABILITY comparable to reference product
Size Similar to reference product No To ensure PATIENT COMPLIANCE with treatment regimens &
for comparable EASE OF SWALLOWING Score Configuration Similar to
reference product Yes*
To ensure PATIENT COMPLIANCE for half dosing & for comparable EASE OF SPLITTING
Identification Positive for Drug Substance Yes* Though identification is critical for SAFETY AND EFFICACY, this CQA can be
effectively controlled & monitored at drug substance release.
Critical Quality Attributes (CQA) of Tablets
EFFICACY SAFETY QUALITY MULTI DISCIPLINARY
© Created & Copyrighted by Shivang Chaudhary
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Critical Material Attribute (CMA) Independent formulation variables i.e. physicochemical properties
of active(drug substance) & inactive ingredients(excipients)
• affecting CQAs of semi-finished and/or finished drug product
Critical Process Parameter (CPP) Independent process parameters
• most likely to affect the CQAs of an intermediate or finished drug
product & therefore should be monitored or controlled
• to ensure the process produces the desired quality product.
Note: Risk related to individual CMAs &/or CPPs will be identified, analyzed qualitatively & then evaluated
quantitatively in order to reduce the probability of risk through optimization by DoE &/or inline detection by PAT.
What is CMA & CPP?
SCREENING
DRY MIXING
COMPRESSION
Screen Type & Size Mill Type (cone mill)
Mill Speed
Blender Type & Fill level Order of Addition
Rotation speed & Time Number of Revolutions
Powder PSD Powder Flow ability Powder Bulk Density
Blend Assay Blend Uniformity
Blend BD/TD Blend Flow ability
Blend Compressibility
Powder PSD & Flow ability Powder Bulk Density
Blend Assay Blend Uniformity
Filing speed (RPM/SPM) Feed Frame paddle speed
Feeder Fill depth Pre Compression Force
Main Compression Force Hopper Design & Run Time
Appearance, Dimensions, Weight variation,
Hardness, Friability, Assay, Impurities, CU
Disintegration, Dissolution
Processing Parameters
Input Materials’ Attributes
Manufacturing Process Steps
Quality Attributes of Output Materials
Drug PSD & Flow ability Excipient PSD & Flow ability Excipient BD TD Moisture
Excipient lot to lot variability
LUBRICATION Blender Type & Fill level
Order of Addition Rotation Speed & Time Number of Revolution
WET GRANULATION Impeller/ Chopper Speed Powder Dry Mixing time
Granulation Kneading time Solution Addition/ Spraying rate
Granulation Fluid Quantity
Blend Assay Blend Uniformity
Granule PSD Granule Flow ability
DRYING Inlet air volume Inlet air temperature
Capacity utilized Filter type/ shake interval
Granule LOD Granule PSD
SIZING Mill type
Blade type/ orientation/ Oscillation degree / speed Screen type/ Screen size
Number of recycles
Granule PSD Granule Flow ability
Granule Assay Granule Uniformity
Granule PSD Granule Flow ability
Granule LOD Granule PSD
Granule PSD & Flow ability Granule Assay & Uniformity
Flow promoters PSD & Specific Surface area
Blend Assay, Blend Uniformity
Blend BD/TD & Flow ability Blend Compressibility
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
RISK ASSESSMENT
RISK EVALUATION
RISK ANALYSIS
RISK IDENTIFICATION
Identification of Factors involved in
High Shear Wet Granulation Process Map
Environment (Temperature & RH)
COATING
Spraying Rate, Atomization Pressure, No. of Guns, Nozzle
Diameter, Gun to Bed Distance, % Load, Coating Pan Speed,
Inlet Air Temperature
Appearance, Dimensions, Weight variation, Hardness, Friability, Assay, Impurities,
Content Uniformity, Disintegration, Dissolution
Appearance, Dimensions, Weight variation (individual/composite), Hardness, Friability, Assay, Impurities, CU
Disintegration ,Dissolution
RISK ASSESSMENT
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
RISK EVALUATION
RISK ANALYSIS
RISK IDENTIFICATION
Identification of Risk Factors by
Ishikawa Fishbone Diagram
© Created & Copyrighted by Shivang Chaudhary
MILLING SCREEN SIZE
BLENDER SPEED-RPM ATOMIZATION PRESSURE
INLET AIR TEMPERATURE
RAW MATERIAL
DILUENT PSD & WATER
BINDER TYPE & CONC.
DISINTEGRANT CONC.
LUBRICANT CONC.
SOLUTION SPRAYING RATE
COATING PAN SPEED
SOLUTION CONC/ VISCOSITY
GRANULATION & DRYING
LIQUID ADDITION RATE
ATOMIZATION AIR PRESSURE
INLET AIR TEMPERATURE
FLUIDIZATION AIR VELOCITY
IMPELLER/ MIXER SPEED
API PARTICLE SIZE
COMPRESSION FORCE
PRESS TURRET SPEED
FEEDER FILL DEPTH TEMPERATURE
RELATIVE HUMIDITY
COMPRESSION/ ENCAPSULATION
CHOPPER/GRANULATOR SPEED
TURRET & FEEDER SPEED
SIZING & BLENDING COATING
ENVIRONMENT
TOTAL GRANULATION TIME
MILLING SPEED
BLENDING TIME
BD/TD/ FLOW OF MATERIAL
TYPE OF TOOLING
FLOW PROMOTER CONC.
PRINCIPLE OF MILLING
PRINCIPLE OF BLENDING
API WATER CONTENT
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
FP CQAs Solid state
/Polymorph Particle size
Flow Properties
Moisture content
Residual Solvent
Solubility Process
Impurity Chemical Stability
Physical High Low Low Low Low Low Low Low Assay Low Low Low Low Low Low High High
Uniformity Low High High Low Low Low Low Low Impurities Low Medium Low Medium Medium Low High High Dissolution High* High* Low Low Low High* Low Low
Low Broadly acceptable risk. No further investigation is needed
Medium Risk is acceptable. Further investigation/justification may be needed in order to reduce the risk.
High Risk is unacceptable. Further investigation is needed to reduce the risk.
RISK ASSESSMENT
RISK EVALUATION
RISK IDENTIFICATION
RISK ANALYSIS
Qualitative Risk based Matrix Analysis of Active Pharmaceutical Ingredient’s (API) Attributes
© Created & Copyrighted by Shivang Chaudhary
RISK IDENTIFICATION
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Physico- Chemical Property of Actives
Critical Material Attribute (CMAs)
Failure Mode (Critical Event)
Effect on IP & FP CQAs with respect to QTPP (Justification of Failure Mode)
P S D RPN (=P*S*D)
Physical Property
Solid Sate Form
Different Polymorph/ form
Solubility of drug substance may get affected= >> Dissolution of drug product may get affected >> BIOAVAILABILITY-EFFICACY may get compromised
2 4 4 32
Particle Size Distribution (PSD)
Higher PSD BCS Class II/IV Low Solubility drug >> Dissolution of drug product may get affected >> BIOAVAILABILITY/EFFICACY may get compromised
4 4 3 48
Flow Properties
Poor flow Poor blend uniformity in simple dry mixing process= uncertainty in uniformity of dosage units due to possible segregation = Quality may got compromised
4 4 3 48
Moisture content High water content
Rate of degradation may get affected >> Impurity profile may get affected >> SAFETY of the product may get compromised
2 3 2 12
Residual Solvents High residual solvent
Residual solvents are likely to interact with drug substance >> Impurities profile may get affected >> SAFETY may get compromised
2 3 2 12
Chemical Property
Solubility Different Salt/ Form
Dissolution of the drug product may get affected >> BIOAVAILABILITY-EFFICACY may got compromised
2 3 4 24
Process Impurities
Less Purity Assay & impurity profile of drug product may be affected = >> Quality & SAFETY may got compromised
2 3 3 18
Chemical Stability
poor Susceptible to dry heat/oxidative/hydrolytic/UV light degradation- impurity profile may get affected >> Quality & SAFETY may got compromised
2 3 3 18
Probability* Severity** Detect ability*** Score Very Unlikely Minor Always Detected 01 Occasional Moderate Regularly Detected 02 Repeated Major Likely not Detected 03 Regular Extreme Normally not Detected 04
Total Risk Priority Number (RPN) more than 30 seek critical attention for DoE for possible failure.
Score based on
LIKELY SEVERITY IMPACT ON DRUG
PRODUCT CQA.
Score based on
PROBABILITY FOR OCCURANCE
OF FAILURE
Score based on
PROBABILITY OF FAILURE OF DETECTION.
RISK ASSESSMENT
RISK ANALYSIS
RISK EVALUATION
Quantitative Failure Mode Effect Analysis (FMEA) of Active Pharmaceutical Ingredient’s (API) Attributes
© Created & Copyrighted by Shivang Chaudhary
Probability of Risk can be Reduced through
DoE Optimization
Detectability of Risk can be increased through In Line PAT System
RISK IDENTIFICATION
RISK ANALYSIS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
C
B
A SOLID STATE FORM
FLOW PROPERTY
PARTICLE SIZE
RISK EVALUATION
RISK ASSESSMENT
CMAs of
API
© Created & Copyrighted by Shivang Chaudhary
CRITICAL
Active Pharmaceutical Ingredient’s (API) Attributes Required to be Optimized &/Or Controlled
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
FP CQAs Diluent Binder Granulating
Agent Disintegrant
Wetting Agent
Glidant Anti-
adherant Lubricant
Physical Low Low Low Low Low Low High High Assay Medium Low Low Low Low Low Low Low
Uniformity High Low Low Low Low High Low Low
Impurities Medium Low Low Low Medium Medium Low Low Dissolution Low High High High High Low High High
Low Broadly acceptable risk. No further investigation is needed
Medium Risk is acceptable. Further investigation/justification may be needed in order to reduce the risk.
High Risk is unacceptable. Further investigation is needed to reduce the risk.
RISK ASSESSMENT
RISK EVALUATION
RISK IDENTIFICATION
RISK ANALYSIS
Qualitative Risk based Matrix Analysis of
Inactive Ingredients’ (Excipients’) Attributes
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Excipient (Inactive ingredient)
Critical Material Attribute (CMAs)
Failure Mode (Critical Event)
Effect on IP & FP CQAs with respect to QTPP (Justification of Failure Mode)
S P D RPN (=S*P*D)
Diluent
Particle Size Distribution
Uneven Flow properties of the blend may be affected (in dry mixing process) >> Uniformity of dosage units may be affected >> Quality/ Safety may got compromised
3 3 2 18
Moisture Content High Impurity profile may be affected (in case of moisture sensitive drugs) = Safety may got compromised
3 3 2 18
Amount of Binder
More than optimum
Produces hard granules= Produces tablet / capsule with greater disintegration time & retarded dissolution= Efficacy may got compromised
4 4 2 32 Binder/ Granulating agent Less than
optimum
Loose granules will be formed, which may produce friable Tablet = Patient acceptance/ Patient compliance got compromised
4 4 2 32
Disintegrant Amount of Disintegrant
Less than optimum
Desired Dissolution cannot be achieved (in case of immediate release product) = Efficacy may got compromised
4 4 2 32
Surfactant as a Wetting Agent
Amount of Surfactant
Less than optimum
Desired Dissolution cannot be achieved in case of hydrophobic drugs = Efficacy may got compromised
4 4 3 48
Glidant Concentration of Glidant
Less than optimum
Flow of granules or powder from hopper to die by reducing friction between particles may be affected = = Uniformity of dosage units may affected =Quality may got compromised
3 3 2 18
Anti-adherant Concentration of Anti-adherant
Less than optimum
Ejection of finished product from tooling may be difficult= Material get stuck to the surface of filling die >> STICKING may be observed = patient acceptance/ compliance may got compromised
3 3 2 18
Lubricant Concentration of Lubricant
Less than optimum
Material get stuck to the surface of punches/toolings >> PICKING may be observed >> Patient acceptance/ compliance may got compromised
3 3 2 18
Higher than Optimum
Hydrophobic lubricant may surface coat the drug particle >> Dissolution may got retarded = Efficacy may got compromised
3 3 3 27
Coloring/ Flavor/ Sweetener agent
Concentration
Lower than optimal
Shade variation/ Mottling may be observed = Patient compliance may got compromised
3 3 1 9
Higher than optimum
Safety may got compromised 3 3 3 27
RISK ASSESSMENT
RISK IDENTIFICATION
RISK ANALYSIS
RISK EVALUATION
Quantitative Failure Mode Effect Analysis (FMEA) of Inactive Ingredients’ (Excipients’) Attributes
© Created & Copyrighted by Shivang Chaudhary
RISK IDENTIFICATION
RISK ANALYSIS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
C
B
A BINDER (%w/w)
SURFACTANT (%w/w)
DISINTEGRANT (%w/w)
RISK EVALUATION
RISK ASSESSMENT
CMAs of
EXCIPIENTS
© Created & Copyrighted by Shivang Chaudhary
CRITICAL
Inactive Ingredients’ (Excipients’) Attributes Required to be Optimized &/Or Controlled
© Created & Copyrighted by Shivang Chaudhary
HIGH SHEAR WET GRANULATION
ROLLER COMPACTION DRY GRANULATION
FLUID BED GRANULATION
DRY MIXING-DIRECT COMPRESSION
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
FP CQAs Co-sifting Blending Roller
Compaction Sizing
Blending & Lubrication
Compression Film Coating
Description Low Low Low High High High High Assay Medium High Low Medium High Low Low
Impurities Low Low Low Low Low Low Medium Uniformity Medium High Low Medium High High Low Dissolution Low Low High Low High High High
FP CQAs Co-sifting Blending Rapid Mixing Granulation
Fluid Bed Drying
Sizing Blending & Lubrication
Compression Film Coating
Description Low Low Low Low High High High High Assay Medium High Medium Low Medium High Low Low
Impurities Low Low Low High Low Low Low Medium Uniformity Medium High Medium Low Medium High High Low Dissolution Low Low High Low Low High High High
FP CQAs Co-sifting Fluid Bed
Granulation Sizing
Blending & Lubrication
Compression Film Coating
Description Low Low High High High High Assay Medium High Medium High Low Low
Impurities Low High Low Low Low Medium Uniformity Medium High Medium High High Low Dissolution Low High Low High High High
FP CQAs Co-sifting Blending Lubrication Compression Film Coating Description Low Low High High High
Assay Medium High Low Low Low Impurities Low Low Low Low Medium Uniformity Medium High Low High Low Dissolution Low Low High High High
RISK ASSESSMENT
RISK EVALUATION
RISK IDENTIFICATION
RISK ANALYSIS
Qualitative Risk based Matrix Analysis of Tablet Manufacturing Processes
RISK IDENTIFICATION
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Unit Operations
Critical Process Parameter (CPPs)
Failure Mode (Critical Event)
Effect on IP & FP CQAs with respect to QTPP (Justification of Failure Mode)
P S D RPN
(=P*S*D)
Screening Sifting Larger Sieve size.
Uneven Particle Size Distribution>> Uncertainty in Uniformity >> SAFETY may get compromised
2 3 3 18
Granulation in Rapid Mixer Granulator
Dry Mixing Rate (No of RPM *Time)
Lower RPM & Shorter Time
Lesser No. of total Revolutions >> Uncertainty in Uniformity >> SAFETY may get compromised
2 3 3 18
Rate of Impeller / Mixer
High RPM & Longer Time Produce Larger granules (forms
agglomerate/lumps)>> Dissolution of Tablet / Capsule can be increased >> BIOAVAILABILITY-EFFICACY may get compromised
4 4 3 48
Rate of Chopper/ Granulator
Low RPM & Shorter Time
4 4 3 48
Binder-Granulating agent spraying rate
High RPM 4 4 3 48
Drying in Fluid Bed Drier
Inlet Temperature
Lower than optimum
Physical Appearance may get affected >> STICKING/ PICKING may be observed >> Patient ACCEPTANCE may get compromised
3 3 2 18
High Product Temperature
Rate of degradation & Impurity profile may be affected >> SAFETY may get compromised
3 3 3 27
Fluidizing Air Flow rate
Higher CFM Increased attrition & evaporation produces fines >> Process EFFICIENCY may get compromised
3 3 2 18
Sizing (Milling & Screening)
Comil Speed Increase Speed Fines may be generated >> Poor flow leads to uncertainty in uniformity of dosage units
3 3 3 27
Comil Screen Larger # Size Uneven PSD leads to uncertainty in Uniformity Larger granules >> Dissolution may be increased >> EFFICACY may get compromised
3 3 3 27
Dry Mixing (Blending) & Lubrication
Blending Rate (No of RPM *Time)
High RPM & High Time
Dissolution may get retarded >> EFFICACY may get compromised
3 3 4 36
Compression / Filling
Turret/ Feeder Speed
High Speed Appearance (LAMINATION), WEIGHT VARIATION may be observed= Uniformity of dosage units may get affected >> SAFETY & EFFICACY may get affected
4 4 3 48
Compression Force /Tamping force
High Force Appearance (CAPPING), HARDNESs of Tablet/ Slug may get affected >> Disintegration/ Dissolution may get affected >> EFFICACY may get compromised
4 4 3 48
Film Coating
Spraying rate Higher Rate Physical Appearance may get affected >> STICKING/ PICKING may be observed >> Patient ACCEPTANCE may get compromised
3 4 3 36 Atomizing Pressure Lower pressure 3 4 3 36 Pan Speed Very Low 3 4 3 36
Bed Temperature
Lower 3 4 3 36
High Temp.
Physical Appearance (BLISTERING/ WRINKLING/ BRIDGING/ ORANGE PEEL DEFECTS), Impurity profile may get affected >> Patient ACCEPTANCE & SAFETY may get compromised
3 3 3 27
RISK ASSESSMENT
RISK ANALYSIS
RISK EVALUATION
Quantitative Failure Mode Effect Analysis (FMEA) of Processing Parameters
© Created & Copyrighted by Shivang Chaudhary
RISK IDENTIFICATION
RISK ANALYSIS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
BINDER
DISINTEGRANT
KNEADING TIME C
B
A A
B BLENDING TIME
COMPRESSION FORCE
TURRET SPEED B
A
BLENDING SPEED
CMAs & CPPs of
WET GRANULATION CPPs of
DRY MIXING- BLENDING
CPPs of
TABLET COMPRESSION
RISK EVALUATION
RISK ASSESSMENT
© Created & Copyrighted by Shivang Chaudhary
CRITICAL
Processing Parameters Required to be Optimized &/Or Controlled
EXPOSURE TIME B
DRYING TEMPERATURE A
CPPs of
FLUID BED DRYING
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Design Space The Multidimensional Combination & Interaction of • Critical Material Attributes and • Critical Process Parameters that have been demonstrated to provide assurance of quality. Note: Working within the design space is not considered as a change. Movement out of the design space is considered to be a change
Design of Experiments (DoE) A Systematic Series of Experiments, • In which purposeful changes are made to input factors to identify
causes for significant changes in the output responses & • Determining the relationship between factors & responses to
evaluate all the potential factors simultaneously, systematically and speedily;
• With complete understanding of the process to assist in better product development & subsequent process scale-up With pretending the finished product quality & performance.
What is DoE & DS?
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
DESIGN OF EXPERIMMENTS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
RISKS
LOWER HARDNESS INADEQUATE DISINTEGRATION
QUALITY COMPROMISED EFFICACY COMPROMISED
HIGH FRIABILITY INADEQUATE DISSOLUTION
SOFT GRANULES HARD GRANULES
BINDER
DISINTEGRANT
KNEADING TIME C
B
A
Optimization of CMAs & CPPs OF
HIGH SHEAR WET GRANULATION PROCESS
DoE For
WET GRANULATION (Contd…)
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
“High”
“Medium”
“Low”
C
NO. OF LEVELS
A BINDER
KN
EA
DIN
G T
IME
NO. OF FACTORS EXPERIMENTAL DESIGN SELECTED
TOTAL NO OF EXPERIMENTAL RUNS (TRIALS)
3
3
Face Centered CENTRAL COMPOSITE DESIGN
2f fp+ (2*f)sp + cp = (22 )+ (2*3) + (6) = 8+6+6 = 20
To Optimize CMAs & CPPs of HIGH SHEAR WET GRANULATION OBJECTIVE
• in wet granulation process binder, disintegrant & kneading time are 3 most critical parameters which are required to be optimized with respect to hardness, friability, disintegration & dissolution.
• Here, all three factors conveniently have only three levels with very narrow nearly same Region of Operability & Region of Interest.
• Thus, Face Centered central composite design with practical alpha value of ±1 has been selected for optimization of all three factors simultaneously having only three levels & nearly the same region of interest & region of operability with little co linearity, cuboidal rather than spherical., & missing data.
Factors (Variables) Levels of Factors Studied -α = -1 0 +α = +1
A Binder (%w/w) 4% 7% 10% B Disintegrant (%w/w) 1% 3% 5% C Kneading Time (min) 2 min 4 min 6 min
DoE For
WET GRANULATION (Contd…)
© Created & Copyrighted by Shivang Chaudhary
DEVELOPMENT OF DESIGN SPACE
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
DoE For
WET GRANULATION (Contd…)
© Created & Copyrighted by Shivang Chaudhary
CQAs CMAs CPP
PREDICTION EFFECT EQUATION OF EACH FACTOR BY QUADRATIC MODEL
HARDNESS =+75.16+25.00A-2.40B+8.00C-1.00AB-2.25AC-1.25BC-4.91A2+0.091B2-0.91C2
FRIABILITY=+0.11-0.071A+6.000E-003B-0.025C +0.000AB+ 7.500E-003AC+0.000BC+0.024A2-1.364E-003B2+3.636E-003C2
DISINTEGRATION TIME=+8.21+2.30A-2.90B+1.00C-0.62AB+0.13AC-0.37BC-0.27A2+3.73B2+0.23C2
DRUG DISSOLVED=+94.83-7.90A+3.70B-4.70C+ 0.88AB+2.38AC+0.38BC-6.82A2-1.82B2-3.82C2
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
DEVELOPMENT OF DESIGN SPACE
DoE For
WET GRANULATION (Contd…)
© Created & Copyrighted by Shivang Chaudhary
Responses (Effects) Goal for Individual Responses Y1 Hardness (n) To achieve tablet hardness in the range from 65 to 85N Y2 Friability (%) To achieve minimum friability i.e. NMT 0.15% Y3 Disintegration (min) To achieve tablet DT within 10 minutes Y4 Dissolution (%) To achieve maximum dissolution in 30 minutes i.e. NLT 90%
Factors (Variables) Knowledge Space Design Space Control Space A Binder (%) 4.00-10.00 5.75-7.75 6.00-7..50 B Disintegrant (%) 1.00-5.00 2.50-5.00 3.00-4.00 c Kneading Time (min) 2.00-6.00 2.50-5.50 2.50-4.50
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
DESIGN OF EXPERIMMENTS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DoE For
FLUID BED DRYING (Contd…)
© Created & Copyrighted by Shivang Chaudhary
INADEQUATE EXPOSURE HIGH TEMPERATURE
SAFETY COMPROMISED
MICROBIAL LOAD INPROCESS IMPURITIES
EXPOSURE TIME B
Optimization of CPPs of
FLUID BED DRYING PROCESS
DRYING TEMPERATURE A
RISKS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
© Created & Copyrighted by Shivang Chaudhary
DoE For
FLUID BED DRYING (Contd…)
Factors (Variables) Levels of Factors studied 0 1 2
A Drying Temperature 0.70 1.00 1.30 B Exposure Time 0.30 1.05 1.80
NO. OF FACTORS
NO. OF LEVELS
EXPERIMENTAL DESIGN SELECTED
ADD. CENTER POINTS
TOTAL NO OF EXPERIMENTAL RUNS (NO OF TRIALS)
2
3
32 FULL FACTORIAL DESIGN
0
32 FP =9
OBJECTIVE To Optimize Critical Processing Parameters of Fluid Bed Drying of HGC/Tablets.
A DRYING TEMPERATURE
B
EX
PO
SUR
E T
IME
DEVELOPMENT OF DESIGN SPACE
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
© Created & Copyrighted by Shivang Chaudhary
DoE For
FLUID BED DRYING (Contd…)
CQA CPPs
PREDICTION EFFECT EQUATION OF EACH FACTOR BY QUADRATIC MODEL
Loss on Drying =+1.12-0.32A-0.40B+0.000AB+0.22A2+0.17B2
Impurities=+1.42+0.28A+0.47B+1.000E-002AB +0.14A2+0.26B2
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
DEVELOPMENT OF DESIGN SPACE
© Created & Copyrighted by Shivang Chaudhary
DoE For
FLUID BED DRYING (Contd…)
Factors (Variables) Knowledge Space Design Space Control Space A Drying TEMPERATURE (C) 40.0-80.0 45.0-75.0 50.0-70.0 B Drying TIME (minutes) 30.0-90.0 35.0-70.0 40.0-60.0
Responses (Effects) Goals for Individual Responses Y1 LOD (%) To achieve loss on drying NMT 1.5%
Y2 Impurities(%) To achieve minimum in process impurities i.e. NMT 1.5%
By Overlaying contour maps from each responses on top of each other, RSM was used to find out the IDEAL “WINDOW” of operability-Design Space per proven acceptable ranges & Edges of Failure with respect to individual goals
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
DESIGN OF EXPERIMMENTS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
Optimization of CPPs of
DRY MIXING- BLENDING PROCESS
RISKS
INAPPROPRIATE BLENDING SPEED &/OR TIME
BLEND UNIFORMITY COMPROMISED
CONTENT UNIFORMITY COMPROMISED
BLENDING SPEED A
B BLENDING TIME
DoE For
DRY MIXING- BLENDING (Contd…)
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
Factors (Variables) Levels of Factors studied 0 1 2
A Blending Speed (in RPM) 8 10 12 B Blending Time (in minutes) 5 10 15
NO. OF FACTORS
NO. OF LEVELS
EXPERIMENTAL DESIGN SELECTED
TOTAL NO OF EXPERIMENTAL RUNS (NO OF TRIALS)
2
3
32 FULL FACTORIAL DESIGN
Lf = 32 FP = 9
To Optimize Critical Processing Parameters of Dry Mixing Process OBJECTIVE
A BLENDING SPEED
B
BLE
ND
ING
TIM
E
“High”
“Medium”
“Low”
• In Dry Mixing Process, 2 Processing Parameters were critical & required to be optimized
• Moreover, It was required to investigate interactive & quadratic relationship between factors & response to find out optimum ranges
• Thus, 3 Level FFD is a time & cost effective best option for optimization of 2 factors.
• However 3 Level FFD facilitates investigation of interactive & quadratic relationship of factors & response in the terms of multiplied 2FI & squared main effects in the quadratic model equation
DoE For
DRY MIXING- BLENDING (Contd…)
© Created & Copyrighted by Shivang Chaudhary
DEVELOPMENT OF DESIGN SPACE
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
CPPs CQAs
Prediction Effect Equation On Individual Response by QUADRATIC MODEL
Average Assay of Blend Uniformity =+99.61 +0.78A+2.32B-0.95AB-1.52A2-2.22B2
RSD Of Blend Uniformity=+1.94-0.47A-1.45B+0.53AB+1.13A2+1.98B2
DoE For
DRY MIXING- BLENDING (Contd…)
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
DEVELOPMENT OF DESIGN SPACE
Factors (Variables) Knowledge Space Design Space Control Space A Blending Speed (RPM) 8.0-12.0 9.15-11.35 9.5-11.0 B Blending Time (minutes) 5.0-15.0 10.0-13.5 10.0-12.0
Responses (Effects) Goals for Individual Responses Y1 Avg. Assay of BU (%) To achieve average assay of BU in the range from 98 to 102%
Y2 RSD of BU(%) To achieve minimum variability in BU i.e. NMT2.0%
By Overlaying contour maps from each responses on top of each other, RSM was used to find out the IDEAL “WINDOW” of operability-Design Space per proven acceptable ranges & Edges of Failure with respect to individual goals
DoE For
DRY MIXING- BLENDING (Contd…)
© Created & Copyrighted by Shivang Chaudhary
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
DESIGN OF EXPERIMMENTS
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
Optimization of CPPs of
TABLET COMPRESSION PROCESS
LOWER HARDNESS INADEQUATE DISINTEGRATION
QUALITY COMPROMISED EFFICACY COMPROMISED
WEIGHT VARIATION
SAFETY COMPROMISED
HIGH FRIABILITY INADEQUATE DISSOLUTION CONTENT NONUNIFORMITY
RISKS
COMPRESSION FORCE
TURRET SPEED B
A
DoE For
TABLET COMPRESSION (Contd…)
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
DEVELOPMENT OF DESIGN SPACE
ANALYSIS OF RESPONSES
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
Factors (Variables) Levels of Factors studied -α -1 0 +1 +α
A COMPRESSION FORCE (kN) 1.17 2.00 4.00 6.00 6.83 B TURRET SPEED (RPM) 3.79 10.00 25.00 40.00 46.21
NO. OF FACTORS
NO. OF LEVELS
EXPERIMENTAL DESIGN SELECTED
TOTAL NO OF EXPERIMENTAL RUNS (TRIALS)
2
5
circumscribed CENTRAL COMPOSITE DESIGN (cCCD)
2fp + 2sp + cp = (22 )+ (2*2) + (5) = 4+4+5 = 13
To Optimize Critical Processing Parameters of Tablet Compression Process OBJECTIVE
A
B
• In Tablet Compression, 2 Processing Parameters were critical & required to be optimized
• Moreover, the region of operability should be greater than region of interest to achieve the maximum rate of productivity to get maximum daily output at commercial manufacturing scale
• Thus, 5 Level cCCD is a time & cost effective best alternative to 3 Level FFD for optimization.
• However in 5 level cCCD, region of operability was greater than region of interest to accommodate additional star points to study extreme levels (highest & lowest) of both factors.
“Highest”
“High”
“Medium”
“Low”
“Lowest”
TUR
RE
T SP
EE
D
COMPRESSON FORCE
DoE For
TABLET COMPRESSION (Contd…)
© Created & Copyrighted by Shivang Chaudhary
DEVELOPMENT OF DESIGN SPACE
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
CPPs
Prediction Effect Equation On Individual Response by QUADRATIC MODEL
CQAs
FRIABILITY =+0.15 -0.066A +0.026B
-7.500E-003AB +0.028A2
+0.021B2
DRUG DISSOLVED IN 30 MIN =+97.20 -8.37A +0.16B -1.75AB -5.73A2
-1.48B2
CONTENT UNIFORMITY =+4.15 -0.088A +1.45B
-0.08AB +0.13A2
+0.73B2
DoE For
TABLET COMPRESSION (Contd…)
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
IDENTIFICATION OF CMAs/CPPs
DESIGN OF EXPERIMMENTS
ANALYSIS OF RESPONSES
Factors (Variables) Knowledge Space Design Space Control Space A Compression Force (kn) 2.0-6.0 3.0-5.0 3.5-4.5 B Turret Speed (RPM) 10-40 10-30 15-25
Responses (Effects) Goal for Individual Responses Y1 Friability To achieve tablet friability NMT 0.2%w/w Y2 Dissolution Drug release should NLT 90% in 30 minutes Y3 Content uniformity Acceptance Value should in CU test should NMT 5.0
By Overlaying contour maps from each responses on top of each other, RSM was used to find out the IDEAL “WINDOW” of Operability-Design Space per proven acceptable ranges & Edges of Failure with respect to individual goals
DoE For
TABLET COMPRESSION (Contd…)
DEVELOPMENT OF DESIGN SPACE
© Created & Copyrighted by Shivang Chaudhary
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Process Analytical Technology (PAT) A System for- • Designing, • Analysing & • Controlling Manufacturing through Timely Measurements (i.e., during processing) of Critical Quality and Performance attributes of raw and in-process materials and processes with the goal of ensuring final product quality. Note: Through PAT, Online Feedback Controlling System for each & individual CMAs &/or CPPs will be developed through designing of controls by analysis at line/ on line/ in line analyser system
What is PAT?
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
CONTROLLING PHASE
ANALYZING PHASE
DESIGNING PHASE
IDENTIFICATION OF CRITICAL STEPs
SIFTING DRYING GRANULATION SIZING COMPRESSION BLENDING COATING
SIFTER FOR
DELUMPING
RAPID MIXER
GRANULATOR FLUID BED
DRYER
BIN
BLENDER
COMPRESSION
MACHINE
COATING
MACHINE SIFTER CUM
MULTI MILL
A B C D E F G
CRITICAL PROCESSING STEPS
PAT For
TABLET MANUFACTURING (Contd…)
© Created & Copyrighted by Shivang Chaudhary
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
SIFTER FOR
DELUMPING
RAPID MIXER
GRANULATOR FLUID BED
DRYER
BIN
BLENDER
COMPRESSION
MACHINE
COATING
MACHINE
TEMPERATURE &
RELATIVE HUMIDITY
At Line
Thermo-hygrometer
GRANULE SIZE DISTRIBUTION
At line Malvern
Particle Size Analyzer OR
On line Sieve Shaker Analysis,
BD-TD Apparatus &
Reposiography
API / EXCIPIENT PURITY
At line UV/ HPLC/ GC,
On line LOD/ HMB or W/KF
API / EXCIPIENT PARTICLE
SIZE DISTRIBUTION
At line Malvern Particle
Size Analyzer OR On Line
Sieve Shaker Analysis
RESIDUAL MOISTURE
CONTENT
On Line LOD
Halogen Moisture Balance or
At Line Water by KF/ GC
BLEND UNIFORMITY
At line UV/HPLC
system; LUBRICATION
analyzed by on line BD-
TD & Reposiography
COMPRESSION
On Line
Weight variation,
Hardness, Friability &
Disintegration Test
Content Uniformity &
Dissolution profiling
analyzed by At line
UV/ HPLC systems
COATING
On Line
Weight variation,
Disintegration test,
CU & Dissolution profiling
by At Line UV/ HPLC;
Color shade variation by
At line Raman Pectrometer
PARTICLE SIZE
DISTRIBUTION
At Line Malvern PSA or
On Line Sieve Shaking
SIFTER CUM
MULTI MILL
Risk Analysis of CMAs & CPPs with respect to CQAs at Raw Scale Developmental level by ON LINE / AT LINE Analyzers for Prediction of Real Time Data &
Designing of Control Strategies at Commercial Scale
CONTROLLING PHASE
ANALYZING PHASE
IDENTIFICATION OF CRITICAL STEPs
DESIGNING PHASE
PAT For
TABLET MANUFACTURING (Contd…)
© Created & Copyrighted by Shivang Chaudhary
IDENTIFICATION OF CRITICAL STEPs
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
TEMPERATURE &
RELATIVE HUMIDITY
In Line
Thermo-hygrometer
GRANULE SIZE DISTRIBUTION
In Line Lasentec FBRM (Focused
Beam Reflectance Measurement)
or
PVM (Particle Video Monitoring)
&
AES (Acoustic Emission
Spectroscopy)
API / EXCIPIENT PURITY
In Line FT-NIR
API / EXCIPIENT PARTICLE
SIZE DISTRIBUTION
In line FBRM
RESIDUAL MOISTURE
CONTENT
In Line Bruker FT-NIR
BLEND UNIFORMITY
In Line FT-NIR
COMPRESSION
In Line Compression Force
Sensor with Servo motor for
Automatic control of
Weight/ Hardness &
Content Uniformity by
In Line FT-NIR
COATING
Color measurement by In
Line UV-Visible spectro
Shade Variation by
In Line Raman Spectro;
Coating Integrity/
thickness by In Line
Terahertz spectroscopy
PARTICLE SIZE
DISTRIBUTION
In Line FBRM
Real Time Data Analysis at Scale UP-Exhibit Manufacturing Scale by IN LINE analyzers with auto-sensors & Real time data comparison with Raw scale data
for Finalization of Control Strategies at Commercial Scale
CONTROLLING PHASE
DESIGNING PHASE
ANALYZING PHASE
PAT For
TABLET MANUFACTURING (Contd…)
SIFTER FOR
DELUMPING
RAPID MIXER
GRANULATOR FLUID BED
DRYER
BIN
BLENDER
COMPRESSION
MACHINE
COATING
MACHINE SIFTER CUM
MULTI MILL
© Created & Copyrighted by Shivang Chaudhary
IDENTIFICATION OF CRITICAL STEPs
DESIGNING PHASE
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Application of Auto-controllers at real time Manufacturing scale For Continuously attaining Acceptable ranges of CMAs & CPPs with respect to desired CQAs
Auto controlling of
GRANULE SIZE DISTRIBUTION
by adjusting
Impeller Speed
Chopper Speed
Granulation time
Solution spraying rate
Auto controlling of
RESIDUAL MOISTURE CONTENT
by adjusting Inlet air volume
Inlet air temperature
Auto controlling of
BLEND UNIFORMITY
by adjusting
Rotation speed *
Rotation Time =
Number of Revolutions
Auto-controlling of
TABLET WEIGHT &
HARDNESS by Adjusting
Filing Turret speed,
Feed Frame paddle speed
Feeder Fill depth
Pre Compression Force
Main Compression Force
Auto-controlling of
%WEIGHT GAIN/
COATING INTEGRITY
By adjusting
Spray rate per nozzle,
Atomization air pressure,
Pan Rotation Speed,
Inlet air temperature
Auto controlling of
PARTICLE SIZE DISTRIBUTION
by adjusting Milling Speed &
Number of recycles
Auto-controlling of
TEMPERATURE &
RELATIVE HUMIDITY
Air Handling Unit
(AHU)
A DEVELOPED PAT SYSTEM FOR CONTINUOS AUTOMATIC ANALYSING & CONTROLLING MANUFACTURING THROUGH TIMELY MEASUREMENTS OF CQA & CPPs WITH THE ULTIMATE GOAL OF CONSISTANTLY ENSURING FINISHED PRODUCT QUALITY AT REAL TIME COMMERCIAL SCALE
ANALYZING PHASE
CONTROLLING PHASE
PAT For
TABLET MANUFACTURING (Contd…)
SIFTER FOR
DELUMPING
RAPID MIXER
GRANULATOR FLUID BED
DRYER
BIN
BLENDER
COMPRESSION
MACHINE
COATING
MACHINE SIFTER CUM
MULTI MILL
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
Control Strategy A planned set of controls for CMAs & CPPs- derived from current product and process understanding • During Lab Scale Developmental Stage • Scaled Up Exhibit-Submission Stage that ensures process performance and product quality • During Commercial Stage
Note: For finalizing & implementation of Control Strategy for each & individual CMAs &/or CPPs; ranges studied at lab scale developmental stage will be compared with pilot plant scale up & pivotal scale exhibit batches to ensure consistent quality of finished product Thus, the control strategy is an integrated overview of how quality is assured based on current process and product knowledge.
What is Control Strategy?
© Created & Copyrighted by Shivang Chaudhary
CONTROL OF CPPs
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
FACTOR(s) CMAs Ranges studied at
LAB scale Actual data
for EXHIBIT batches Proposed range for
COMMERCIAL batch PURPOSE of Control
Active Pharmaceutical Ingredient (API) Critical Material Attributes Polymorphic
Form 2Ө values x, y, z x, y, z x, y, z
To ensure batch to batch consistency in Dissolution
Particle Size Distribution
(PSD)
D10: NMT x um NMT x um NMT x um To ensure batch to batch consistency in Blend Uniformity (BU), Content Uniformity (CU) & Dissolution
D50: NMT y um NMT y um NMT y um
D90: NMT z um NMT z um NMT z um
EXCIPIENT Critical Material Attributes
Microcrystalline Cellulose
(Avicel PH 102)
Particle Size Distribution D10: NMT 100 um D50: NMT 100 um D90:NMT 100 um To ensure batch to batch consistency in BU & CU during dry mixing for wet granulation
Moisture Content NMT 5.0% NMT 5.0% NMT 5.0%
Crospovidone (Polyplasdone
XL 10)
Level in Formulation 1-5%w/w 3.5%w/w 3-4%w/w To ensure batch to batch consistency in disintegration & dissolution
Specific surface area 1.2-1.4 m2/g 1.2-1.4 m2/g 1.2-1.4 m2/g
Polyvinylpyrolidone (Pladone
K 29/32)
Level in Formulation 4-10%w/w 7.5%w/w 6-8%w/w To give consistent binding functionality to granules to warrant hardness & friability
K Value 29-32 29-32 29-32
Colloidal Silicone Dioxide
(Aerosil 200 Pharma)
Level in Formulation 0.10-0.50 0.18-0.36 0.20-0.30 To promote consistent flow property of granules from hopper to die.
Specific surface area 175-225 m2/g 180-220 m2/g 185-215 m2/g
Magnesium Stearate
(Vegetable Grade)
Level in Formulation 0.50-2.00 0.70-1.30 0.80-1.20 To ensure consistent lubrication & smooth ejection of compressed tablet from die.
Specific surface area 10-20 m2/g 10-20 m2/g 10-20 m2/g
CONTROL OF CMAs
CONTROL STRATEGY For
Critical Material Attributes
© Created & Copyrighted by Shivang Chaudhary
Implementatn of
Control Strategy
PAT &Development
of Feedback Control system
DoE & Development of Design Space
Quality Risk Assessment of
CMAs & CPPs
Determination of CQAs
Definition of QTPP
FACTOR(s) CPPs Ranges studied at
LAB scale Actual data
for EXHIBIT batches Proposed range for
COMMERCIAL batch PURPOSE of Control
Co-Sifting Screen Mesh # Size 30# 30# 30# To ensure PSD consistency to prevent segregation
High Shear Wet GRANULATION
Pre-mixing time 10-20 min 12-18 min 13-17 min To ensure batch to batch consistency Particle Size Distribution (PSD), Bulk Density (BD) & Tapped Density (TD) in order to warrant Uniform Flow property & Disintegration of Granules
Binder addition rate 1.0-2.0 min 1.0-2.0 min 1.5-2.0 min
Rate of Wet Mass Kneading & Granulation
2-6 min (Impeller Speed: (50-100 RPM; Chopper Speed: 1500 RPM)
3.5 min (Impeller Speed: 60-90 RPM; Chopper Speed: 1500 rpm)
2.5-4.5 min (Impeller Speed: 70-80 RPM; Chopper Speed: 1500 RPM)
Fill Level (%v/v) 30-70% 40-60% 45-55%
Fluid Bed DRYING
Inlet Air Temperature 40.0-80.0 45.0-75.0 50.0-70.0 To ensure Low Water content in granules in order to prevent In Process impurity, Microbial growth & Compression defects (Sticking/ Picking)
Total Drying Time 30.0-90.0 35.0-70.0 40.0-60.0 Fluidization Air Velocity 50-100 CFM 55-85 CFM 60-80 CFM
Water Content 0.5-5.0% 1.5-3.0% 1.5-3.0%
Fill Level (%v/v) 30-70% 40-60% 45-55%
Milling/ SIZING
Milling Speed 800-1200 rpm 900-1100 rpm 950-1050 rpm To ensure consistency in PSD of granules Mill Screen Size 1-2 mm 1.5 mm 1.5 mm
Blending & LUBRICATION
Blending Speed 8.0-12.0 RPM 9.5-11.5 RPM 9.5-11.0 RPM To ensure batch to batch consistency in Blend Uniformity & Dissolution
Blending Time 5.0-15.0 Min 11.0 Min 10.0-12.0 Min
Fill Level (%v/v) 30-70% 40-60% 45-55%
Tablet COMPRESSION
Compression Force 2.0-6.0 kN 3.0-5.0 kN 3.5-4.5 kN To ensure batch to batch consistency in Hardness, Weight variation & Disintegration in order to ensure Friability, CU & Dissolution without any Compression defects (Capping/ Lamination)
Feeder Speed 2.5-10 RPM 2.5-7.5 RPM 3.5-6.5 RPM
Turret Speed 10-40 RPM 10-30 RPM 15-25 RPM
Film COATING
Liquid Spraying Rate X-Y gm/min X++
-Y++
gm/min X++
-Y++
gm/min To ensure batch to batch consistency in Physical Appearance, Weight variation & Disintegration
Atomization Pressure 1-4 bar 2-4 bar 2.5-3.5 bar
Pan Rotation Speed 3-10 RPM 3-8 RPM 4-7RPM
Bed Temperature 40-60°C 40-55°C 45-55°C
CONTROL OF CMAs
CONTROL OF CPPs
CONTROL STRATEGY For
Critical Processing Parameters
© Created & Copyrighted by Shivang Chaudhary
Conclusion
Detectability of Risk was increased by implementation of automatic inline
Process Analytical Technology (PAT)
RPN = Severity * Probability * Detectability
Severity of Risks could Not be reduced
Through QbD, Risk associated with each & every CMAs & CPPs with respect to CQAs identified from QTPP were effectively & extensively assessed
out by FMEA (Failure Mode Effective Analysis), which decided “which risk should get first priority?” based upon Severity * Probability * Detectability of individual risk.
Probability of Risk occurrence was reduced by systematic series of experiments through
Designing of Experiments (DoE)
which ensured timely measurement of critical quality and performance attributes of raw and
in-process materials or parameters to control the quality of finished product.
which generated safe & optimized ranges of CMAs & CPPs with respect to desired CQAs par overlaid DESIGN SPACE, where all the desired
in process & finished product CQAs are met simultaneously.
Justification for
Risk Reduction
During Routine Commercial Manufacturing Continual
Risk Review & Risk Communication between Stockholders of:
MANUFACTURING PLANT
QUALITY ASSUARANCE
QUALITY CONTROL
REGULATORY AFFAIRS
FORMULATION R&D
ANALYTICAL R&D
For continual assurance that the process remains in a state of control (the validated state) during commercial manufacture.
For Excellent Product
Lifecycle Management Management of
Product Life
Cycle
What is Continual Improvement?
© Created & Copyrighted by Shivang Chaudhary
Throughout the product lifecycle, the manufacturing process performance will be monitored to ensure that it is working as anticipated to deliver the product with desired quality attributes. Process stability and process capability
will be evaluated. If any unexpected process variability is detected, appropriate actions will be taken to correct, anticipate, and prevent future problems so that the process remains in control.
© Created & Copyrighted by Shivang Chaudhary
© Copyrighted by Shivang Chaudhary
Formulation Engineer (QbD/PAT System Developer & Implementer) MS (Pharmaceutics)- National Institute of Pharmaceutical Education & Research (NIPER), INDIA
PGD (Patents Law)- National academy of Legal Studies & Research (NALSAR), INDIA
+91 -9904474045, +91-7567297579 [email protected]
https://in.linkedin.com/in/shivangchaudhary
facebook.com/QbD.PAT.Pharmaceutical.Development
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“Quality doesn’t costs, it always pays”