QbD Understanding How Excipient Properties Influence Solid Oral Dosage Form Performance

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QbD – Understanding How Excipient Properties Influence Solid Oral Dosage Form Performance

Dr Amina Faham (Dow), Dr Liz Meehan (AstraZeneca)

ExcipientFest, Amsterdam NL June 24, 2014

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What do you understand by the term QbD, in particular applied to excipients?

AstraZeneca – Do not share without permission

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Traditional versus QbD approach

• In traditional approaches, industry focused on:

– Similar excipient lots are used during development and in commercial manufacturing (avoiding variation)

– Optimized, fixed formulation and fixed process parameters – Compliance with compendial specifications for excipients

• QbD approach encourages:

– Understanding variation of excipients properties as they relate to critical process parameters and product quality attributes – Building robustness and flexibility into manufacturing process – Excipient specifications appropriate to ensure product quality

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Product Quality Attributes – Source and Effect/s

API Variability

Excipient Variability

Process Variability

Product Variability

σ σ

σ

²^Product

^

²^API

^

²^Excipients

^

²^Process

^

²^Interactio^ns

Ref: C. Moreton

Understanding variability &

tolerating it

= Robustness

4

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Excipient functionality and performance

• Quantitative performance requirements (i.e. critical material attributes) of excipients

• Characterisation of excipients to determine their suitability for intended use

• Must be evaluated and controlled to ensure consistent

performance throughout the product life-cycle (e.g. changes in suppliers)

• Integral to the "Quality by Design" approach that should be employed in drug product development

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Quality by Design

API Excipients

Processing

Material attributes

Material attributes Intermediate

attributes Process

parameters

Drug product Product

attributes Safety and

efficacy

CMA CMA

CQA

CPP CMA

Spec range

MSA

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Quality by Design

CQA=Critical quality attributes of the product

CMA=Critical material attributes of all input raw materials CPP=Critical process parameters

MSA=measurement systems analysis

Target Drug Product Profile

CQA = f (CMA, CPP)

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Why QbD for excipients?

• Excipient properties can affect CQAs of drug product

– Manufacturability (e.g. flow, compaction) – Content uniformity (e.g. segregation)

– Bioavailability (e.g. disintegration, dissolution) – Purity

– Stability (e.g. chemical and physical incompatibilities)

• It is important to understand and control the effects of excipient variability

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Challenges

• Excipients developed and manufactured specifically for

pharmaceutical use are often available in a range of special grades (developed for specific formulation or process)

• There are multiple suppliers of nominally the same grade

– lot-to-lot/batch-to-batch/supplier inequivalence or variability – variability in excipient properties should be anticipated and

appropriate controls must be in place to ensure consistent performance

• Excipient applications for pharmaceutical development are many and varied

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Challenges

• Identification and control of critical material attributes may go beyond monograph specifications and require a thorough understanding of

– the formulation – the process

– the physical and chemical properties of each ingredient

• Critical material attributes should be evaluated and

controlled to ensure that consistent product performance is achieved throughout the product lifecycle

• Requires user/supplier collaboration

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Challenges

• An excipient may have very different functions in the formulation – e.g., diluent, lubricant, glidant

• It may require different performance characteristics

– e.g., particle size, size distribution, surface area depending on its use in a formulation, manufacturing process, and dosage form.

• The development, manufacture, and performance of

pharmaceutical dosage forms depend heavily upon the physical and chemical properties of the excipients

– Physical

• Particle morphology, powder property, polymorph, hygroscopicity, aqueous solubility, pKa, and density

– Chemical

• Identity, purity, incompatibility with drug substance or other excipients

– Mechanical

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USP versus PhEur : different approach

USP Information Chapter <1059> Excipient Performance

• Overview of the key functional categories of excipients identified in USP–NF.

• Guidance as to which properties might be important for a particular material in a particular application.

• Cross-references to standard methods that can be used by both manufacturers and users:

– Makes communication more straightforward

– Avoids an unnecessary plethora of test variations for a particular parameter.

• Keeping the tests non-mandatory.

• Avoiding confusion with mandatory tests and labelling tests.

• Not imposing limits/specifications.

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Extract from USP <1059>

“Not all critical material attributes of an excipient may be

identified or evaluated by tests, procedures, and acceptance criteria in NF monographs. Excipient suppliers and users therefore at times may wish to identify and control critical excipient attributes that go beyond monograph

specifications.”

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USP versus PhEur : different approach

PhEur

• Within each individual excipient monograph a section exists for non-mandatory Functionality Related Characteristics (FRCs) that should be considered

 e.g. Croscarmellose sodium

 Settling volume

 Degree of substitution

 Particle size distribution

 Hausner ratio

 e.g. Dibasic Calcium Phosphate

 Particle size distribution

 Bulk and tapped density

 Powder flow

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Excipient variability – how much do you need to do?

• A risk based approach benefits both the patient and the business

– Not all excipients have an impact on product quality or safety – Not all properties of an excipient are equally important

– In many cases normal excipient variation does not negatively impact the quality and safety of the product

• The way forward

– Comprehensive studies of excipient properties are only needed when the excipient properties are expected to impact the critical quality

attributes (CQAs) of the drug product

– The goal is to define control strategy for excipients

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Case study to exemplify the approach

Microcrystalline cellulose

Degree of polymerisation pH

Bulk density Loss on drying Residue on ignition Conductivity

Ether soluble substances Water soluble substances Impurities

Particle size distribution

Mannitol

Conductivity Loss on drying Reducing sugars Assay

Particle size distribution Porosity/Specific surface area

Bulk density Polymorphic form Impurities

Sodium starch glycolate

pH

Loss on drying Sodium chloride Sodium glycolate Assay (Na)

Bulk density Rate/degree of swelling

Magnesium stearate

Particle size

Specific surface area Loss on drying

Stearic/palmitic acid level

Assay (Mg)

•To explore every material attribute would require many thousands of experiments

•Risk assessment is required to focus the experimental programme

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Assessing the risk of excipient variability

• Collect existing data/information on the raw materials

– Excipient monographs, literature examples, Handbook of

Pharmaceutical Excipients, supplier certificates of analysis, supplier databases, etc

• Refer to target product profile

– target patient populations, geographical markets, etc

• For each excipient in the formulation, identify potential critical

material attributes (functionality) and potential risk factors (security of supply, commercial and regulatory considerations)

• Score the potential risk for each material attribute and risk factor

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Possible outcome after risk assessment

Microcrystalline cellulose

Degree of polymerisation pH

Bulk density Loss on drying Residue on ignition Conductivity

Ether soluble substances Water soluble substances Impurities

Particle size distribution

Mannitol

Conductivity Loss on drying Reducing sugars Assay

Particle size distribution Porosity/Specific

surface area Bulk density Polymorphic form Impurities

Sodium starch glycolate

pH

Loss on drying Sodium chloride Sodium glycolate Assay (Na)

Bulk density Rate/degree of swelling

Magnesium stearate

Particle size

Specific surface area Loss on drying

Stearic/palmitic acid level

Assay (Mg)

•Risk assessment reduces the number of potential CMAs to consider for experimental work

•Some material attributes could be confounded providing further simplification

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Next steps

• Risk assessment scores identify the highest risks excipient attributes

• Select/source excipient variants

– Batch select from a particular supplier and within grade (QbD sample sets)

– From one supplier use different grades (more extreme variation)

– From multiple suppliers (different ranges of variation)

• Perform risk mitigation work to study effect of excipient variability (on process and/or product performance)

• Use outputs to define excipient control strategy

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Excipient supplier-user collaboration

• Exchange of information between excipient supplier and user is invaluable

• Provides benefits to both supplier and user

• IPEC QbD checklists developed to help facilitate this

• Available to IPEC Europe members as downloads from the website

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IPEC QbD checklists

• For suppliers • For Users

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How HPMC Physicochemical Properties Impact Matrix Tablet Performance

ExcipientFest, Amsterdam NL June 24, 2014

DOW CONFIDENTIAL - Do not share without permission

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Outline

• Background and HPMC materials

• HPMC physical properties and how they impact matrix tablet performance

• HPMC chemical properties and how they impact matrix tablet performance

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Quality by Design (QbD) Means Design the Product And The Process

• Design the product to meet patient requirements

• Design the process to consistently meet product critical quality attributes

• Understand the impact of starting materials and process parameters on product quality

• Identify and control the source of process variation

• Continually monitor and update the process to allow a consistent quality over time

Dr A.Faham

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Quality by Design (QbD)

• The drug product must be safe and efficacious for the patient.

– I.e., Ensure the dosage form performs as expected.

• How robust is dosage form performance?

• How robust is the process to make the dosage form?

• How robust are the methods to characterize the dosage form?

• What is the impact of raw material variability? (API? Excipients?)

– Multiple suppliers?

– Lot-to-lot variability?

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Properties vs. Performance

• Raw material properties

– Physical – Chemical

• Process

– Processability

• E.g. Flowability

– Process steps and parameters which are critical to quality.

• Performance

– Dosage form physical properties – Achieving desired performance

• API release

– Is desired performance reproducible (e.g. from lot-to-lot, day-to-day)?

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Dr A.Faham

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HPMC Matrix Tablets for Modified-Release

• Hydrophilic matrix tablets are the most commonly utilized MR dosage form.

– Simplest.

– Fastest to develop.

– Least expensive to manufacture.

• Hypromellose 2208 is the most common rate-modifying excipient used in hydrophilic matrices.

O O HO

OCH₃

OCH O

O HO

OH

O O HO

OH O

O

HO O O

CH₃O

OCH₃ OCH₃ O

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HPMC Sustained Release Matrix Tablets

Key Hypromellose Formulation Variables

• Level

• Molecular weight/viscosity

• Substitution type

• Particle size distribution

 Actives and other excipients can cause the formulation to be more sensitive to HPMC properties

Dr A.Faham

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How HPMC Physical Properties

Impact Matrix Tablet Performance

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 For a selected hypromellose

product, polymer level is usually the major drug release rate

controlling factor

– Ford et al. 1985. IJP, 24:327- 338 and 339-350

 Drug release may be more sensitive to variations in hypromellose

properties at low hypromellose levels

(< 30%)

10% propranolol HCl, METHOCEL™ K4M

balance lactose, 0.5% mag stearate

Hypromellose Level

Dr A.Faham

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Particle Size

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30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

HPMC Particle Size (% thru 230 mesh)

Drug Released (%)

caffeine (50%), K15M (30%) - 6 hr

metoprolol tartrate (20%), K4M (30%) - 3 hr theophylline (50%), K4M (30%) - 6 hr

Particle Size

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Dr A.Faham

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30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

HPMC Particle Size (% thru 230 mesh)

Drug Released (%)

acetaminophen (50%), K100M (30%) - 6 hr hydrochlorothiazide (50%), K100 LV (30%) - 3 hr ketoprofen (20%), K4M (30%) - 12 hr

Particle Size

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METHOCEL™ K15M Premium CR

0 20 40 60 80 100

0 120 240 360 480 600 720

Time (min)

% PP dissolved

High % thru 230 mesh/ Low Level High % thru 230 mesh/ High Level Low % thru 230 mesh/ Low Level Low % thru 230 mesh/ High Level Center Point/ Low Level Center Point/ High Level

Propranolol HCl release: effect of particle size

f₂ = 48.23 f₂ = 94.14

• Higher polymer level slower drug release

• Higher polymer level  lower variability

• Drug release were significantly affected by coarser P/S for lower polymer level

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Dr A.Faham

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How HPMC Chemical Properties

Impact Matrix Tablet Performance

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Selection of Hypromellose substitution grade

 Hypromellose grade has a significant effect on dissolution

 Methylcellulose and Hypromellose 2906 (A and F Chemistry)

typically are not used for CR applications

Dr A.Faham

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METHOCEL™ K15M Premium CR

0 20 40 60 80 100

0 120 240 360 480 600 720

Time (min)

% PP dissolved

High Viscosity/ Low Level High Viscosity/ High Level

Low Viscosity/ Low Level Low Viscosity/ High Level

Center Point/ Low Level Center Point/ High Level

• Higher polymer level slower drug release

• Higher polymer level  lower variability

Propranolol HCl release: effect of viscosity

f₂ = 66.90

f₂ = 74.21

The similarity factor (f₂) was calculated by comparing high vs. low end of the selected physicochemical property

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40 50% diclofenac sodium, 40% METHOCEL™ K15M

9.5% lactose, 0.5% mag stearate

Hypromellose Substitution

40% salicylic acid, 30% METHOCEL™ K15M 29% lactose, 1% mag stearate

Dr A.Faham

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Paracetamol Model Example

Ingredient % w/w Weight per tablet (mg)

Paracetamol* 50 250

METHOCEL™ K4M or Pilot Plant HPMC 30 150

Lactose 18 90

Magnesium stearate 1 5

Talc 1 5

Total 100 500

Actual tablet weight: 502 ± 3 mg Hardness: 94 ± 8 N

* Paracetamol:

Analgesic

Aqueous solubility: 14 mg/mL

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Batch-to-Batch Consistency

• Batch-to-batch consistency with commercial METHOCEL™:

• Reproducible modified-release performance.

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0 20 40 60 80 100

0 200 400 600 800 1000 1200 1400

Paracetamol Released (%)

Time(min)

Batch no. 1 Batch no. 2 Batch no. 3 Batch no. 4 Batch no. 5 Batch no. 6 Batch no. 7 Batch no. 8 Batch no. 9 Batch no. 10 Batch no. 11 Batch no. 12 Batch no. 13 Batch no. 14 Batch no. 15 Batch no. 16 Batch no. 17 Batch no. 18 Batch no. 19 Batch no. 20

Commercial

Batch No. %Me %HP

50% Cumulative Volume Particle

Size (µm) %NaCl

2% Viscosity (mPa·s)

1 22.8 8.3 93.8 0.2 3711

2 23.1 8.7 91.9 0.3 4514

3 22.2 9.1 84.3 0.3 3638

4 22.6 8.4 88.7 0.1 4953

5 22.7 8.2 94.1 0.2 4015

6 23.0 8.5 97.8 0.2 4444

7 23.3 8.7 102.1 0.3 3506

8 23.2 8.8 110.8 0.3 3897

9 23.1 8.6 109.1 0.3 3615

10 23.1 8.6 103.7 0.3 3615

11 22.2 8.6 96.7 0.6 3756

12 23.0 8.8 107.9 0.3 3810

13 23.0 8.7 103.1 0.4 4325

14 23.3 8.7 99.3 0.3 3775

15 23.4 8.7 99.3 0.3 3849

16 22.9 8.5 98.8 0.4 4364

17 22.8 7.9 101.9 0.3 4562

18 23.6 8.4 104.3 0.3 4322

19 23.1 8.7 101.2 0.4 4057

20 23.0 8.7 100.8 0.4 3839

Average 23.0 8.6 99.2 0.3 3996

Std Deviation 0.4 0.3 6.6 0.1 414

Rogers TL, Petermann O, Adden R, and Knarr M (2011). Investigation and rank -ordering of hypromellose 2208 properties impacting modified release performance of a hydrophilic matrix tablet, Twenty-Sixth Annual Meeting, Proceedings of the American Association of Pharmaceutical Scientists, Washington DC, Poster no. R6168.

900 mL pH 5.7 phosphate buffer at 37 °C 50 rpm paddle speed

Tablets placed in sinkers

n=6 standard deviation was never more than 2%

Dr A.Faham

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METHOCEL™ FRCs Impacting Performance

• Based on this model, rank-order of METHOCEL FRC impact is as follows: %HP (p <

0.05) > 2% viscosity (p = 0.06) > particle size (p = 0.13) > %Me (p = 0.75).

• Correlations between paracetamol release and HP substitution vs. 2% viscosity reflect findings from the model.

• Paracetamol release increases with increasing HP content .

– Trend occurs over a narrow range of 79-86% paracetamol released at 22 hr, reflecting reproducible batch-to-batch modified-release performance.

ESTABLISHING THE PERFORMANCE DESIGN SPACE

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Pilot Plant HPMC vs. Commercial METHOCEL™

– Expanded design space boundaries with pilot plant HPMC.

• HP substitution was purposefully varied.

– Premise:

• There is ‘insufficient’ batch-to-batch variability in commercial METHOCEL to investigate performance design space proactively.

• We cannot explore the allowable pharmacopeial design space.

– Where are the boundaries of robustness?

– What if we miss optimal performance ‘sweet spots’?

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Rogers TL, Knarr M, Petermann O, and Adden R (2011). Expanding design space boundaries within pharmacopeial limits: Impact of atypical hydroxypropoxyl substitution on drug release from HPMC matrices, Twenty-Sixth Annual Meeting, Proceedings of the American Association of Pharmaceutical Scientists, Washington DC, Poster no. R6167.

Sample

identification %Me %HP

50% cumulative volume particle

size (µm) %NaCl

2% viscosity (mPa-s)

Prototype No. 1 24.2 8.6 78.5 0.1 4466

Prototype No. 2 23.0 11.4 72.0 0.1 4346

Prototype No. 3 24.0 9.1 64.6 0.1 2730

Prototype No. 4 24.4 6.0 84.8 < 0.1 5292

Prototype No. 5 23.1 11.2 70.3 0.1 3356

Prototype No. 6 24.4 6.6 66.8 < 0.1 5476

Prototype No. 7 23.3 7.8 70.5 < 0.1 5092

Prototype No. 8 23.4 9.5 66.1 < 0.1 4999

Prototype No. 9 23.7 10.2 52.4 < 0.1 5009

See previous section for FRCs of commercial batches investigated

4 5 6 7 8 9 10 11 12

HP Content (%)

Commercial Batches 1 through 21 Pilot Plant Batches 1 through 9 Breadth of minimum and maximum HP

content (4–12%) according to the harmonized pharmacopeia (USP, PhEur, and JP).

Dr A.Faham

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Modified-Release Performance

• Pilot plant HPMC data

“brackets” commercial METHOCEL data for HP

substitution and paracetamol release.

• Paracetamol release increases with increasing HP substitution.

• Efficiently determined that formulation is robust.

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Indapamide Example

Ingredient % w/w Weight per tablet (mg)

Indapamide* 2.5 5

Pilot Plant HPMC 40 80

Lactose 40 80

Microcrystalline cellulose 16.5 33

Magnesium stearate 0.5 1

Talc 0.5 1

Total 100 200

Actual tablet weight: 200 ± 3 mg Hardness: 83 ± 8 N

Friability: Weight loss ≤ 0.16%

* Indapamide:

Antihypertensive

Aqueous solubility: 75 µg/mL

Dr A.Faham

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Modified-Release Performance

• Only variable was the HPMC batch used.

– Same formulation composition.

– Tried to hold everything constant except HPMC batch.

Proactively determined that API and formulation are very sensitive to variation in %HP

0.1% SLS in 900 mL water at 37˚C 50 rpm paddle speed

Tablets placed in hanging baskets

n=6 standard deviation was never more than 5%

0 20 40 60 80 100

0 200 400 600 800 1000 1200 1400

Indapamide Released (%)

Time (min)

% indapamide released at 17 hr ranged from 60 to 90%

Breaking point in modified release

performance

Step-change increase in API

release

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Performance Design Space

Breaking point in modified

release performance

Above HP content of 7.8%

Step-change increase in API release

Modulation of API release spans

∆ of ~35%

Potential extent of variation unacceptable

Proactive exploration of design space identified

highly responsive API

HPMC specification recommended

Dr A.Faham

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Summary

• Modified release performance is most significantly impacted by HP substitution of METHOCEL™

– HP substitution is the primary factor modulating modified release

• Forced-variation prototypes enabled expansion of the design space boundaries of our model formulation

– APIs highly ‘responsive’ to METHOCEL™ FRCs

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11/24/11

Questions?

Thank You!

Dr A.Faham