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`Yu et al.
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`Under QbD, these goals can often be achieved by
`linking product quality to the desired clinical performance
`and then designing a robust formulation and manufactur(cid:173)
`ing process to consistently deliver the desired product
`quality.
`Since the initiation of pharmaceutical QbD, the FDA
`has made significant progress
`in achieving the first
`objective: performance-based quality specifications. Some
`examples of FDA policies include tablet scoring and bead
`sizes in capsules labeled for sprinkle (14,15). The recent
`FDA discussions on the assayed potency limits for narrow
`therapeutic index drugs and physical attributes of generic
`drug products reflect this
`trend (16). Nonetheless, it
`should be recognized that ICH documents (3-9) did not
`explicitly acknowledge clinical performance-based specifi(cid:173)
`cations as a QbD goal, although this was recognized in a
`recent scientific paper (10).
`The second objective of pharmaceutical QbD is to
`increase process capability and reduce product variability
`that often leads to product defects, rejections, and recalls.
`Achieving this objective requires robustly designed prod(cid:173)
`uct and process. In addition, an improved product and
`process understanding can facilitate the identification and
`control of factors influencing the drug product quality.
`After regulatory approval, effort should continue to
`improve the process to reduce product variability, defects,
`rejections, and recalls.
`QbD uses a systematic approach to product design and
`development. As such, it enhances development capability,
`speed, and formulation design. Furthermore, it transfers
`resources from a downstream corrective mode to an
`upstream proactive mode. It enhances the manufacturer's
`ability to
`identify the root causes of manufacturing
`failures. Hence, increasing product development and
`manufacturing efficiencies is the third objective of phar(cid:173)
`maceutical QbD.
`The final objective of QbD is to enhance root cause
`analysis and postapproval change management. Without good
`product and process understanding, the ability to efficiently
`scale-up and conduct root cause analysis is limited and
`requires the generation of additional data sets on the
`proposed larger scale. FDA's change guidances (17,18)
`provide a framework for postapproval changes. Recently,
`the FDA issued a guidance intended to reduce the regulatory
`filing requirements for specific low-risk chemistry,
`manufacturing, and control (CMC) postapproval manufactur(cid:173)
`ing changes (19).
`
`ELEMENTS OF PHARMACEUTICAL QUALITY
`BY DESIGN
`
`In a pharmaceutical QbD approach to product develop(cid:173)
`ment, an applicant identifies characteristics that are critical to
`quality from the patient's perspective, translates them into the
`drug product critical quality attributes (CQAs), and estab(cid:173)
`lishes the relationship between formulation/manufacturing
`variables and CQAs to consistently deliver a drug product
`with such CQAs to the patient. QbD consists of the following
`elements:
`
`1. A quality target product profile (QTPP) that identifies
`the critical quality attributes (CQAs) of the drug
`product
`2. Product design and understanding including the
`identification of critical material attributes (CMAs)
`3. Process design and understanding including the iden(cid:173)
`tification of critical process parameters (CPPs) and a
`thorough understanding of scale-up principles, linking
`CMAs and CPPs to CQAs
`4. A control strategy that includes specifications for the
`drug substance(s), excipient(s), and drug product as
`well as controls for each step of the manufacturing
`process
`5. Process capability and continual improvement
`
`Quality Target Product Profile that Identifies the Critical
`Quality Attributes of the Drug Product
`
`QTPP is a prospective summary of the quality charac(cid:173)
`teristics of a drug product that ideally will be achieved to
`ensure the desired quality, taking into account safety and
`efficacy of the drug product. QTPP forms the basis of design
`for the development of the product. Considerations for
`inclusion in the QTPP could include the following (3):
`
`• Intended use in a clinical setting, route of adminis-
`tration, dosage form, and delivery system(s)
`• Dosage strength(s)
`• Container closure system
`• Therapeutic moiety release or delivery and attributes
`affecting pharmacokinetic characteristics (e.g. , disso(cid:173)
`lution and aerodynamic performance) appropriate to
`the drug product dosage form being developed
`• Drug product quality criteria (e.g., sterility, purity,
`stability, and drug release) appropriate for the
`intended marketed product
`
`Identification of the CQAs of the drug product is the
`next step in drug product development. A CQA is a
`physical, chemical, biological, or microbiological property
`or characteristic of an output material including finished
`drug product that should be within an appropriate limit,
`range, or distribution to ensure the desired product
`quality (3). The quality attributes of a drug product may
`include identity, assay, content uniformity, degradation
`products, residual solvents, drug release or dissolution,
`moisture content, microbial limits, and physical attributes
`such as color, shape, size, odor, score configuration, and
`friability. These attributes can be critical or not critical.
`Criticality of an attribute is primarily based upon the
`severity of harm to the patient should the product fall
`outside the acceptable range for that attribute. Probability
`of occurrence, detectability, or controllability does not
`impact criticality of an attribute.
`It seems obvious that a new product should be ade(cid:173)
`quately defined before any development work commences.
`However, over the years, the value of predefining the target
`characteristics of the drug product is often underestimated.
`Consequently, the lack of a well-defined QTPP has resulted in
`wasted time and valuable resources. A recent paper by Raw
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`et al. (12) illustrates the significance of defining the correct
`QTPP before conducting any development. Also, QbD exam(cid:173)
`ples exemplify the identification and use of QTPPs (20-22).
`
`Product Design and Understanding
`
`Over the years, QbD's focus has been on the process
`design, understanding, and control, as discussed in the ICH
`Q8 (R2) guidance (3). It should be emphasized that product
`design, understanding, and control are equally important.
`Product design determines whether the product is able to
`meet patients' needs, which is confirmed with clinical studies.
`Product design also determines whether the product is able to
`maintain its performance through its shelf life, which is
`confirmed with stability studies. This type of product under(cid:173)
`standing could have prevented some historical stability
`failures.
`The key objective of product design and understanding is
`to develop a robust product that can deliver the desired
`QTPP over the product shelf life. Product design is open(cid:173)
`ended and may allow for many design pathways. Key
`elements of product design and understanding include the
`following:
`
`• Physical, chemical, and biological characterization of
`the drug substance(s)
`• Identification and selection of excipient type and
`grade, and knowledge of intrinsic excipient variability
`• Interactions of drug and excipients
`• Optimization of formulation and identification of
`CMAs of both excipients and drug substance
`
`To design and develop a robust drug product that has the
`intended CQAs, a product development scientist must give
`serious consideration to the physical, chemical, and biological
`properties of the drug substance. Physical properties include
`physical description (particle size distribution and particle
`morphology), polymorphism and form transformation, aqueous
`solubility as a function of pH, intrinsic dissolution rate,
`hygroscopicity, and melting point(s). Pharmaceutical solid
`polymorphism, for example, has received much attention
`recently since it can impact solubility, dissolution, stability, and
`manufacturability. Chemical properties include pKa, chemical
`stability in solid state and in solution, as well as photolytic and
`oxidative stability. Biological properties include partition coef(cid:173)
`ficient, membrane permeability, and bioavailability.
`Pharmaceutical excipients are components of a drug
`product other than the active pharmaceutical ingredient.
`Excipients can (1) aid in the processing of the dosage
`form during its manufacture; (2) protect, support, or
`enhance stability, bioavailability, or patient acceptability;
`(3) assist in product identification; or ( 4) enhance any
`other attribute of the overall safety, effectiveness, or
`delivery of the drug during storage or use (23). They
`are ~lassified by the functions they perform in a pharma(cid:173)
`ceutical dosage form. Among 42 functional excipient
`categ?ries list~d in USt(NF (24), commonly used excipi(cid:173)
`ents mcl~de bmders, d1smtegrants, fillers (diluents), lubri(cid:173)
`cants, ghdants (flow enhancers), compression aids, colors,
`sweeten~rs, preservative_s,_ suspending/dispersing agents,
`pH modtfiers/b~ff~rs, _tomc1ty agents, film formers/coatings,
`flavors, and prmtmg mks. The FDA's inactive ingredients
`
`database (25) lists the safety limits of excipients based on
`prior use in FDA-approved drug products.
`It is well recognized that excipients can be a major
`source of variability. Despite the fact that excipients can alter
`the stability, manufacturability, and bioavailability of drug
`products, the general principles of excipient selection are not
`well-defined, and excipients are often selected ad hoc without
`systematic drug-excipient compatibility testing. To avoid
`costly material wastage and time delays, ICH Q8 (R2)
`recommends drug-excipient compatibility studies to facilitate
`the early prediction of compatibility (3). Systematic drug(cid:173)
`excipient compatibility studies offer several advantages as
`follows: minimizing unexpected stability failures which usual(cid:173)
`ly lead to increased development time and cost, maximizing
`the stability of a formulation and hence the shelf life of the
`drug product, and enhancing the understanding of drug(cid:173)
`excipient interactions that can help with root cause analysis
`should stability problems occur.
`Formulation optimization studies are essential in developing a
`robust formulation that is not on the edge of failure. Without
`optimization studies, a formulation is more likely to be high risk
`because it is unknown whether any changes in the formulation itself
`or in the raw material properties would significantly impact the
`quality and performance of the drug product, as shown in recent
`examples (26,27). Formulation optimization studies provide impor(cid:173)
`tant information on the following:
`
`• Robustness of the formulation including establishing
`functional relationships between CQAs and CMAs
`• Identification of CMAs of drug substance, excipients,
`and in-process materials
`• Development of control strategies for drug substance
`and excipients
`
`In a QbD approach, it is not the number of optimization
`studies conducted but rather the relevance of the studies and
`the utility of the knowledge gained for designing a quality
`drug product that is paramount. As such, the QbD does not
`equal design of experiments (DoE), but the latter could be an
`important component of QbD.
`Drug substance, excipients, and in-process materials may
`have many CMAs. A CMA is a physical, chemical, biological,
`or microbiological property or characteristic of an input
`material that should be within an appropriate limit, range,
`or distribution to ensure the desired quality of that drug
`substance, excipient, or in-process material. For the purpose
`of this paper, CMAs are considered different from CQAs in
`that CQAs are for output materials including product
`intermediates and finished drug product while CMAs are for
`input materials including drug substance and excipients. The
`CQA of an intermediate may become a CMA of that same
`intermediate for a downstream manufacturing step.
`Since there are many attributes of the drug substance
`and excipients that could potentially impact the CQAs of the
`intermediates and finished drug product, it is unrealistic that a
`formulation scientist investigate all the identified material
`attributes during the formulation optimization studies. There(cid:173)
`fore, a risk assessment would be valuable in prioritizing which
`material attributes warrant further study. The assessment
`should leverage common scientific knowledge and the
`formulator's expertise. A material attribute is critical when a
`realistic change in that material attribute can have a
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`Table I. Typical Input Material Attributes, Process Parameters, and Quality Attributes of Pharmaceutical Unit Operations
`
`Pharmaceutical unit operation
`
`Input material attributes
`
`Process parameters
`
`Quality attributes
`
`• Particle size
`• Particle size distribution
`• Fines/oversize
`• Particle shape
`• Bulk/tapped/true density
`• ~p:qx!l1ie;
`• Electrostatic properties
`• Moisture content
`
`Blending/mixing
`• Type and geometry of mixer
`• Mixer load level
`• Order of addition
`• Number of revolutions (time and speed)
`• Agitating bar (on/off pattern)
`• Discharge method
`• Holding time
`• Environment temperature and RH
`
`• Particle/granule size
`• Particle/granule size
`distribution
`• Fines
`• Particle/granule shape
`• Bulk/tapped/true density
`• Adhesive properties
`• Electrostatic properties
`• Hardness/plasticity
`• Viscoelasticity
`• Brittleness
`• Elasticity
`• Solid form/polymorph
`• Moisture content
`• Granule porosity/density
`
`• Particle size distribution
`• Fines/Oversize
`• Particle shape
`• Bulk/tapped/true density
`• Cdm.e'adhelm p:qx!l1ie;
`• Electrostatic properties
`• Hardness/plasticity
`• Viscoelasticity
`• Brittleness
`• Elasticity
`• Solid form/polymorph
`• Moisture content
`
`Size reduction/comminution
`
`Ribbon milling
`• Ribbon dimensions
`• Ribbon density
`• Ribbon porosity/solid fraction
`
`Impact/cutting/screening mills
`• Mill type
`• Speed
`• Blade configuration, type, orientation
`• Screen size and type
`• Feeding rate
`
`Fluid energy mill
`• Number of grinding nozzles
`• Feed rate
`• Nozzle pressure
`• Classifier
`
`Granule/ribbon milling
`• Mill type
`• Speed
`• Blade configuration, type, orientation
`• Screen size and type
`• Feeding rate
`
`Wet granulation
`High/low shear granulation
`• Type of granulator (High/low shear, top/bottom drive)
`• Fill level
`• Pregranulation mix time
`• Granulating liquid or solvent quantity
`•
`Impeller speed, tip speed, configuration, location, power
`consumption/torque
`• Chopper speed, configuration, location, power consumption
`• Spray nozzle type and location
`• Method of binder excipient addition (dry/wet)
`• Method of granulating liquid addition (spray or pump)
`• granulating liquid temperature
`• granulating liquid addition rate and time
`• Wet massing time (post-granulation mix time)
`• Bowl temperature(jacket temperature)
`• Product temperature
`• Post mixing time
`• Pump Type: Peristaltic, Gear type
`• Granulating liquid vessel (e.g., pressurized, heated)
`
`Fluid bed granulation
`• Type of fluid bed
`•
`Inlet air distribution plate
`• Spray nozzle (tip size, type/quantity/ pattern/configuration/position)
`• Filter type and orifice size
`
`• Blend uniformity
`• Potency
`• Particle size
`• Particle size distribution
`• Bulk/tapped/true density
`• Moisture content
`• Flow properties
`• Cohesive/adhesive properties
`• Powder segregation
`• Electrostatic properties
`
`• Particle/granule size
`• Particle/granule size distribution
`• Particle/granule shape
`• Particle/granule shape factor
`(e.g., aspect ratio)
`• Particle/granule density/Porosity
`• Bulk/tapped/true density
`• Flow properties
`• API polymorphic form
`• API crystalline morphology
`• Cohesive/adhesive properties
`• Electrostatic properties
`• Hardness/Plasticity
`• Viscoelasticity
`• Brittleness
`• Elasticity
`
`• Endpoint measurement
`(e.g., power consumption, torque,
`etc.)
`• Blend uniformity
`• Potency
`• Flow
`• Moisture content
`• Particle size and distribution
`• Granule size and distribution
`• Granule strength and uniformity
`• Bulk/tapped/true density
`• API polymorphic form
`• Cohesive/adhesive properties
`• Electrostatic properties
`• Granule brittleness
`• Granule elasticity
`• Solid form/polymorph
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`Pharmaceutical unit operation
`
`Table I. (continued)
`
`Input material attributes
`
`Process parameters
`
`Quality attributes
`
`• Fill level
`• Bottom screen size and type
`• Preheating temperature/time
`• Method of binder excipient addition (dry/wet)
`• Granulating liquid temperature
`• Granulating liquid quantity
`• Granulating liquid concentration/viscosity
`• Granulating liquid holding time
`• Granulating liquid delivery method
`• Granulating liquid spray rate
`•
`Inlet air, volume, temperature, dew point
`• Atomization air pressure
`• Product and filter pressure differentials
`• Product temperature
`• Exhaust air temperature, flow
`• Filter shaking interval and duration
`
`Drying
`
`• Particle size, distribution
`• Fines/oversize
`• Particle shape
`
`Fluidized bed
`•
`Inlet air volume, temperature, dew point
`• Product temperature
`
`. ~~ • Exhaust air temperature, flow
`
`• Electrostatic properties
`• Hardness/plasticity
`• Viscoelasticity
`• Brittleness
`• Elasticity
`• Solid form/polymorph
`• Moisture content
`
`• Filter type and orifice size
`• Shaking interval and duration
`• Total drying time
`
`Tray
`• Type of tray dryer
`• Bed thickness/tray depth (depth of product per tray)
`• Type of drying tray liner (e.g., paper, plastic,
`synthetic fiber, etc.)
`• Quantity carts and trays per chamber
`• Quantity of product per tray
`• Drying time and temperature
`• Air flow
`•
`Inlet dew point
`
`Vacuum/microwave
`•
`Jacket temperature
`• Condenser temperature
`•
`Impeller speed
`• Bleed air volume
`• Vacuum pressure
`• Microwave power
`• Electric field
`• Energy supplied
`• Product temperature
`• Bowl and lid temperature
`• Total drying time
`Roller compaction/chilsonation
`• Type of roller compactor
`• Auger (feed screw) type/design (horizontal,
`vertical or angular)
`
`• Auger (feed screw) speed
`• Roll shape (cylindrical or interlocking).
`• Roll surface design (smooth, knurled, serrated,
`or pocketed)
`• Roll gap width (e.g., flexible or fixed)
`• Roll speed
`• Roll pressure
`
`• Particle size, distribution
`• Fines/oversize
`• Particle shape
`
`• Electrostatic properties
`• Hardness/plasticity
`• Bulk/tapped/true density
`• Viscoelasticity
`• Brittleness
`• Elasticity
`
`. ~~ • Deaeration (e.g., vacuum)
`
`• Granule size and distribution
`• Granule strength, uniformity
`• Flow
`• Bulk/tapped/true density
`• Moisture content
`• Residual solvents
`• API polymorphic form or transition
`• Purity profile
`• Moisture profile (e.g . product
`temperature vs. LOD)
`• Potency
`• Cohesive/adhesive properties
`• Electrostatic properties
`
`• Ribbon appearance (edge attrition,
`splitting, lamination, color, etc.)
`• Ribbon thickness
`• Ribbon density (e.g., envelop
`density)
`• Ribbon porosity/solid fraction
`• Ribbon tensile strength/breaking
`force
`• Throughput rate
`• API polymorphic form and transition
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`Pharmaceutical unit operation
`
`Input material attributes
`
`Process parameters
`
`Quality attributes
`
`Table I. (continued)
`
`• Solid form/polymorph
`
`• Roller temperature
`• Fines recycled (yes or no, # of cycles)
`
`. ~ ~ • Screw blade configuration
`
`• Particle size, distribution
`• Fines/oversize
`• Particle shape
`
`• Electrostatic properties
`• Hardness/plasticity
`• Bulk/tapped/true density
`• Viscoelasticity
`• Brittleness
`• Elasticity
`• Solid fonn/polymorph
`
`Extrusion-Spheronization
`• Type of extruder (screw or basket)
`• Screw length, pitch, and diameter
`• Screw channel depth
`
`• Number of screws (single/dual)
`• Die or screen configuration (e.g., radial or axial)
`• Die length/diameter ratio
`• Roll diameter (mm)
`• Screen opening diameter (mm)
`• Screw speed (rpm)
`• Feeding rate (g/min)
`• Type and scale of spheronizer
`• Spheronizer load level
`• Plate geometry and speed
`• Plate groove design (spacing and pattern)
`• Air flow
`• Residence time
`
`• Extrudate
`• Density
`• Length/thickness/diameter
`• Moisture content
`• API polymorphic form and transition
`• Content uniformity
`• Throughput
`
`• Pellets after spheronization
`• Pellets size and distribution
`• Pellets shape factor (e.g. aspect
`ratio)
`• Bulk/Tapped density
`• Flow properties
`• Brittleness
`• Elasticity
`• Mechanical strength
`• Friability
`
`• Extrudate density
`• Length/thickness/diameter
`• Polymorphic form and transition
`• Content uniformity
`• Throughput
`
`• Particle size, distribution
`• Fines/oversize
`• Particle shape
`• Melting point
`• Density
`• Solid fonn/polymorph
`• Moisture content
`
`Hot melt extrusion
`• Screw design (twin/single)
`• Screw speed
`• Screw opening diameter (mm)
`• Solid and liquid feed rates
`• Feeder type/design
`• Feed rate
`• No. of zones
`• Zone temperatures
`• Chilling rate
`
`• Particle/granule size
`and distribution
`• Fines/oversize
`• Particle/granule shape
`• Cohesive/adhesive
`properties
`• Electrostatic properties
`• Hardness/plasticity
`• Bulk/tapped/true density
`• Viscoelasticity
`• Brittleness
`• Elasticity
`• Solid form/polymorph
`• Moisture
`
`• Particle/granule size and
`distribution
`• Fines/oversize
`• Particle/granule shape
`• Cooesive/ocloo;ive prq»1ies
`• Electrostatic properties
`• Hardness/plasticity
`• Bulk/tappeditrue density
`• Viscoelasticity
`• Brittleness
`
`Tabletting
`• Type of press (model, geometry, number of stations)
`• Hopper design, height, angle, vibration
`• Feeder mechanism (gravity/forced feed. shape of wheels,
`direction of rotation, number of bars)
`• Feed frame type and speed
`• Feeder fill depth
`• Tooling design (e.g., dimension, score configuration,
`quality of the metal)
`• Maximum punch load
`• Press speed/dwell time
`• Precompression force
`• Main compression force
`• Punch penetration depth
`• Ejection force
`• Dwell Time
`
`Encapsulation
`
`• Tablet appearance
`• Tablet weight
`• Weight uniformity
`• Content uniformity
`• Hardness/tablet breaking force/
`tensile strength
`• Thickness/dimensions
`• Tablet porosity/density/solid fraction
`• Friability
`• Tablet defects
`• Moisture content
`• Disintegration
`• Dissolution
`
`• Machine type
`• Machine fill speed
`• Tamping Force
`• No. of tamps
`• Auger screw design/speed
`• Powder bed height
`
`• Capsule appearance
`• Weight
`• Weight uniformity
`• Content uniformity
`• Moisture content
`• Slug tensile strength
`• Disintegration
`• Dissolution
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`Pharmaceutical unit operation
`
`Input material attributes
`
`Process parameters
`
`Quality attributes
`
`Table I. (continued)
`
`• Elasticity
`• Solid form/polymorph
`• Moisture
`
`• Tablet dimensions
`• Tablet defects
`• Hardness/plasticity
`• Density
`• Porosity
`• Moisture content
`
`• Tablet dimensions
`• Tablet defects
`• Hardness/plasticity
`• Density/porosity
`moisture content
`
`Pan coating
`• Type of pan coater (conventional or side-vented)
`• Pan (fully perforated or partial perforated)
`• Baffle (design, number, location)
`• Pan load level
`• Pan rotation speed
`• Spray nozzle (type, quantity, pattern, configuration,
`spray pattern)
`• Nozzle to bed distance
`• Distance between nozzles
`• Nozzle orientation
`• Total preheating time
`•
`Inlet air flow rate, volume, temperature, dew point
`• Product temperature
`•
`Individual nozzle spray rate
`• Total spray rate
`• Atomization air pressure
`• Pattern air pressure
`• Exhaust air temperature, air flow
`• Total coating, curing time and drying time
`
`Fluid bed coating
`• Type of fluid bed coater
`• Fluid bed load level
`• Partition column diameter
`• Partition column height
`• Number of partition columns
`• Air distribution plate type and size
`• Filter type and orifice size
`• Filter differential pressure
`• Filter shaking interval and duration
`• Spray nozzle (type, quantity, pattern, configuration)
`• Nozzle port size
`• Total preheating time
`• Spray rate per nozzle
`• Total spray rate
`• Atomization air pressure
`•
`Inlet air flow rate, volume, temperature, dew point
`• Product temperature
`• Exhaust air temperature, air flow
`• Total coating, curing and drying time
`
`• Size/dimensions
`• Polymer type
`membrane thickness
`
`Laser drilling
`
`• Conveyor type
`• Conveyor speed
`• Laser power
`• Number of pulses
`• Type( s) of lens( es)
`• One or two sided
`• Number of holes
`
`• Coating efficiency
`• Core tablet weight before and after
`preheating
`• Moisture (gain/loss) during
`preheating
`• Environmental equivalency factor
`• Coated drug product (e.g., tablet or
`capsule) appearance
`• % weight gain
`• Film thickness
`• Coating (polymer and /or color)
`uniformity
`• Hardness/breaking force/Tensile
`strength
`• Friability
`• Moisture (gain/loss) during overall
`process
`• Residual solvent(s)
`• Disintegration
`• Dissolution
`• Tablet defects
`• Visual attributes
`
`• Coating efficiency
`• Core tablet weight before and after
`preheating
`• Moisture (gain/loss) during
`preheating
`• Environmental equivalency factor
`• Coated drug product (e.g., tablet or
`capsule) appearance
`• % weight gain
`• Film thickness
`• Coating (polymer and /or color)
`uniformity
`• Hardness/breaking force/tensile
`strength
`• Friability
`• Moisture (gain/loss) during overall
`process
`• Residual solvent(s)
`• Disintegration
`• Dissolution
`• Tablet defects
`• Visual attributes
`
`• Opening diameter (internal and
`external)
`• Depth
`• Shape of the opening
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`Understanding Pharmaceutical Quality by Design
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`• Improve or optimize the current process based upon
`data analysis using techniques such as design of
`experiments to create a new, future state process.
`Set up pilot runs to establish process capability.
`• Control the future state process to ensure that any
`deviations from target are corrected before they
`result in defects. Implement control systems such as
`statistical process control, production boards, visual
`workplaces, and continuously monitor the process.
`
`In addition, continuous improvement can apply to legacy
`products. Legacy products usually have a large amount of
`historical manufacturing data. Using multivariate analysis to
`examine the data could uncover major disturbances in the form
`of variability in raw materials and process parameters. Contin(cid:173)
`uous improvement could be achieved by reducing and control(cid:173)
`ling this variability. Newer processes associated with a design
`space facilitate continuous process improvement since appli(cid:173)
`cants will have regulatory flexibility to move within the design
`space (ICH QB).
`
`PHARMACEUTICAL QUALITY BY DESIGN TOOLS
`
`Prior Knowledge
`
`Although not officially defined, the term "prior knowl(cid:173)
`edge" has been extensively used in workshops, seminars,
`and presentations. In regulatory submissions, applicants
`often attempt to use prior knowledge as a "legitimate"
`reason for substitution of scientific justifications or
`conducting necessary scientific studies.
`Knowledge may be defined as a familiarity with someone
`or something, which can include information, facts, descrip(cid:173)
`tions, and/or skills acquired through experience or education.
`The word "prior" in the term "prior knowledge" not only
`means "previous," but also associates with ownership and
`confidentiality, not available to the public. Thus, for the
`purpose of this paper, prior knowledge can only be obtained
`through experience, not education. Knowledge gained
`through education or public literature may be termed public
`knowledge. Prior knowledge in the QbD framework general(cid:173)
`ly refers to knowledge that stems from previous experience
`that is not in publically available literature. Prior knowledge
`may be the proprietary information, understanding, or skill
`that applicants acquire through previous studies.
`
`Risk Assessment
`
`ICH Q9 quality risk management indicates that "the
`manufacturing and use of a drug product, including its
`components, necessarily entail some degree of risk.... The
`evaluation of the risk to quality should be based on scientific
`knowledge and ultimately link to the protection of the patient
`and the level of effort, formality, and documentation of the
`quality risk management process should be commensurate with
`the level of risk (4)." The purpose of ICH Q9 is to offer a
`systematic approach to quality risk management and does not
`specifically address risk assessment in product development.
`However, the risk assessment tools identified in ICH Q9 are
`applicable to risk assessment in product development also.
`
`The purpose of risk assessment prior to development
`studies is to identify potentially high-risk formulation and
`process variables that could impact the quality of the drug
`product. It helps to prioritize which studies need to be conducted
`and is often driven by knowledge gaps or uncertainty. Study
`results determine which variables are critical and which are not,
`which facilitates the establishment of a control strategy. The
`outcome of the risk assessment is to identify the variables to be
`experimentally investigated. ICH Q9 (4) provides a
`nonexhaustive list of common risk assessment tools as follows:
`
`• Basic risk management facilitation methods (flow-
`charts, check sheets, etc.)
`• Fault tree analysis
`• Risk ranking and filtering
`• Preliminary hazard analysis
`• Hazard analysis and critical control points
`• Failure mode effects analysis
`• Failure mode, effects, and criticality analysis
`• Hazard operability analysis
`• Supporting statistical tools
`
`It might be appropriate to adapt these tools for use in specific
`areas pertaining to drug substance and drug product quality.
`
`Mechanistic Model, Design of Experiments, and Data
`Analysis
`
`Product and process understanding is a key element of
`QbD. To best achieve these objectives, in addition to mechanis(cid:173)
`tic models, DoE is an excellent tool that allows pharmaceutical
`scientists to systematically manipulate factors according to a
`prespecified design. The DoE also reveals relationships between
`input factors and output responses. A series of structured tests
`are designed in which planned changes are made to the input
`variables of a process or system. The effects of these changes on
`a predefined output are then assessed. The strength of DoE over
`the traditional univariate approach to development studies is the
`ability to properly uncover how factors jointly affect the output
`responses. DoE also allows us to quantify the interaction terms
`of the variables. DoE is important as a formal way of
`maximizing information gained while minimizing the resources
`required. DoE studies may be integrated with mechanism-based
`studies to maximize product and process understanding.
`When DoE is applied to formulation or process devel(cid:173)
`opment, input variables include the material attributes (e.g.,
`particle size) of raw material or excipients and process
`parameters (e.g., press speed or spray rate), while outputs
`are the critical quality attributes of the in-process materials or
`final drug product (e.g., blend uniformity, particle size or
`particle size distribution of the granules, tablet assay, content
`uniformity, or drug release). DoE can help identify optimal
`conditions, CMAs, CPPs, and, ultimately, the design space.
`FDA scientists have shown the use of DoE in product and
`process design in recent publications (33-39).
`
`Process Analytical Technology
`
`The application of PAT may be part of the control
`strategy (28). ICH Q8 (R2) identifies the use of PAT to
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`ensure that the process remains within an established design
`space (3). PAT can provide continuous monitoring of CPPs,
`CMAs, or CQAs to make go/no go decisions and to
`demonstrate that the process is maintained in the design
`space. In-process testing, CMAs, or CQAs can also be
`measured online or inline with PAT. Both of t