QbD – Understanding How Excipient Properties Influence ... Workshop QbD.pdf · QbD –...

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

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


Product Quality Attributes –

Source and Effect/s

API

Variability Excipient

Variability

Process

Variability

Product

Variability

σσσσσ2

nsInteractio

2

Process

2

Excipients

2

API

2

Product

Ref: C. Moreton

Understanding

variability &

tolerating it

= Robustness

4 AstraZeneca – Do not share without permission

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


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


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)


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


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


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


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 • Flowability, compressibility


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.


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.”


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


Bulk and tapped density

Powder flow


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


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


Mannitol Conductivity

Loss on drying

Reducing sugars

Assay


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


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


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


Mannitol Conductivity

Loss on drying

Reducing sugars

Assay


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


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


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


IPEC QbD checklists

• For suppliers

• For Users


How HPMC Physicochemical Properties

Impact Matrix Tablet Performance

ExcipientFest, Amsterdam NL

June 24, 2014

DOW CONFIDENTIAL - Do not share without permission

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

23 DOW CONFIDENTIAL - Do not share without permission

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

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?


Dr A.Faham

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)?


Dr A.Faham

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.

29

R = CH3 OH OCH3

OOHO

OCH3

OCH3

OO

HO

OH

O

OO

HOOH

O

O

HO OO

CH3OOCH3

OCH3OCH3

O

R

OH


Dr A.Faham

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

How HPMC Physical Properties



Dr A.Faham

32

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

DOW CONFIDENTIAL - Do not share without permission Dr A.Faham

Particle Size


Dr A.Faham

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)

Dru

g R

ele

ased

(%

)

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

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

theophylline (50%), K4M (30%) - 6 hr

Particle Size


Dr A.Faham

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)

Dru

g R

ele

as

ed

(%

)

acetaminophen (50%), K100M (30%) - 6 hr

hydrochlorothiazide (50%), K100 LV (30%) - 3 hr

ketoprofen (20%), K4M (30%) - 12 hr

Particle Size

35


Dr A.Faham

METHOCEL™ K15M Premium CR

0

20

40

60

80

100

0 120 240 360 480 600 720

Time (min)

% P

P d

isso

lved

High % thru 230 mesh/ Low Level High % thru 230 mesh/ High LevelLow % thru 230 mesh/ Low Level Low % thru 230 mesh/ High LevelCenter 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

36


Dr A.Faham

How HPMC Chemical Properties



Dr A.Faham

38

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


METHOCEL™ K15M Premium CR

0

20

40

60

80

100

0 120 240 360 480 600 720Time (min)

% P

P d

iss

olv

ed

High Viscosity/ Low Level High Viscosity/ High Level

Low Viscosity/ Low Level Low Viscosity/ High LevelCenter Point/ Low Level Center Point/ High Level

• Higher polymer level slower drug release

• Higher polymer level lower variability

• Drug release were consistent across viscosity range

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


Dr A.Faham

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

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


Dr A.Faham

Batch-to-Batch Consistency

• Batch-to-batch consistency with commercial

METHOCEL™:

• Reproducible modified-release

performance.

42

0

20

40

60

80

100

0 200 400 600 800 1000 1200 1400

Para

ceta

mo

l Re

leas

ed

(%)

Time(min)

Batch no. 1 Batch no. 2










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 414Rogers 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%


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.

43

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.

ESTABLISHING THE PERFORMANCE DESIGN SPACE


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’?

44

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

Co

nte

nt (

%)

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).


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.

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.


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

Modified-Release Performance

• Only variable was the HPMC batch used.

– Same formulation composition.

– Tried to hold everything constant except HPMC batch.

47

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

substitution.

High risk of batch failure.

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

Ind

apam

ide

Re

leas

ed

(%)

Time (min)

% indapamide released at 17 hr

ranged from 60 to 90%

Breaking point in

modified release performance

Step-change increase in API

release


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

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

49 DOW CONFIDENTIAL - Do not share without permission Dr A.Faham

11/24/11

Questions?

Thank You!


Dr A.Faham

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