Compliant Formulation Development – The Key to · PDF fileCompliant Formulation Development – The Key to Successful Pharma Development ... pre-process validation) ... •Capsule,

Compliant Formulation Development – The Key to Successful Pharma Development

Oberägeri, May 4th 2012Dr. R. Rogasch

2

Regulatory Requirements in Formulation Development

EU Scientifc Guidance Documents – EMA (Clinical, CMC, Procedural)

EP7 – General Chapters, Monographs

US FDA Guidance Documents – (Clinical, CMS, Procedural)

USP – General Chapters and Methods (Dissolution Method Development, IVIVC –requirements, Statistical Methodology)

ICH Q8/Q9/Q10

3


• EU Scientifc Guidance Documents – Formulation Development

IMP Procedure (pre-clinical data, dossier submission requirements, clinical studies)

CMC requirements (specifications, stability data, pre-process validation)

Bioequivalence or Biowaiver approach

4


• EU EP7 requirements – Generic Drug Development - Legal status of monographs

• Monographs are “official standards”

• The Convention on the Elaboration of a European Pharmacopoeia makes the texts of thePh. Eur. mandatory in all signatory parties

• The pharmaceutical legislation in the European Unionmakes monographs obligatory standards(2001/83/EC, 2001/81/EC)

• Monographs may be accepted as suitable standardseven when not obligatory

5


• EU EP7 requirements – Generic Drug Development - example

Do Ph. Eur. specifications apply throughout shelf-life?

• A: Yes, specifications apply until time of use for raw materials and throughout period of validity for preparations

• B: No, Ph. Eur. requirements are for release only

From ICH Quality Implementation Working Group - Integrated Implementation Training WorkshopBreakout D: Pharmacopoeial Requirements, Kuala Lumpur, July 2010

6

Regulatory Requirements in Formulation Development• EU EP7 requirements – Generic Drug Development - example

Do Ph. Eur. specifications apply throughout shelf-life?

• A: Yes, specifications apply until time of use forraw materials and throughout period of validity for Preparations (EP7, general notices)

• B: No, Ph. Eur. requirements are for release only.

Implications : EP7 mongraph specifications (impurities) are shelf life indicating !

From ICH Quality Implementation Working Group - Integrated Implementation Training WorkshopBreakout D: Pharmacopoeial Requirements, Kuala Lumpur, July 2010

7

ICHQ8/9/10 Paradigm in Formulation Development

Disclaimer

The information within this presentation is based on the ICH Q-IWG members expertise and experience, and represents the views of the ICH Q-IWG members for the purposes of a training workshop.

8

QRM as part of development

Ø To assess the critical attributes of § Raw materials§ Solvents§ Active Pharmaceutical Ingredient (API)§ Starting materials§ Excipients§ Packaging materials

Ø To establish appropriate specifications, identify critical process parameters and establish manufacturing controls

ICH Q9

9

II.3: QRM as part of development

Ø To decrease variability of quality attributes:§ reduce product and material defects§ reduce manufacturing defects

Ø To assess the need for additional studies (e.g., bioequivalence, stability) relating to scale up and technology transfer

Ø To make use of the “design space” concept (see ICH Q8)

ICH Q9

10

Key Steps for a product under Quality by Design (QbD)

Product/Process Development

Pharmaceutical Development

PQS & GMPLocal Environment

Commercial Manufacturing

Quality Unit (QP,..) level support by PQS

Manage product lifecycle, including continual improvement

Design Space (DS), RTR testing

Link raw material attributes and process parameters to CQAs and perform Risk Assessment Methodology

Potential CQA (Critical Quality Attribute) identified & CPP (Critical Process Parameters) determined

QTPP : Definition of intended use & productQuality TargetProduct Profile

CPP : CriticalProcess Parameter

CQA : CriticalQuality Attribute

Risk Management

Opportunities

Design to meet CQA using Risk Management & experimental studies (e.g. DOE)DOE : Design of Experiment

Control Strategy

Technology Transfer

Batch ReleaseStrategy

Prior Knowledge (science, GMP, regulations, ..)

Continualimprovement

Product/Process Understanding

QRM principle apply at any stage

Marketing Authorisation

Quality System PQS

11

P2 of CTD as part of a regulatory submission

In line with Quality Risk Management ?

EXAMPLE

12

Risk Review

Risk

Com

mun

icat

i on

Risk Assessment

Risk Evaluationunacceptable

Risk Control

Risk Analysis

Risk Reduction

Risk Identification

Review Events

Risk Acceptance

InitiateQuality Risk Management Process

Output / Result of theQuality Risk Management Process

Risk

Managem

entt ools

P2 of CTD as Quality Risk Management process ?

Process understanding

Formulation & Process design

Process control Concept

Product release Concept

Review the submission

Regulatory strategy

Manufacturing Concept

13

Target Product Profile

Drug substance properties; prior knowledge

Proposed formulation and manufacturing process

Determination of Cause – Effect relationships

(Risk Identification with subsequent Risk Analysis)

Risk-based classification (Risk Evaluation)

Parameters to investigate (e.g. by DOE)(Risk Reduction 1. proposal; 2. verified)

FORMULATION FORMULATION DESIGN SPACEDESIGN SPACE

PROCESS PROCESS DESIGN SPACE DESIGN SPACE

BY UNIT OPERATIONBY UNIT OPERATIONCONTROL CONTROL STRATEGYSTRATEGY

Formulation understanding

Formulation understanding

Proc

ess

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ationevaluation and confirm

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and

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Product and process characteristics on the

final drug product

Review events

DevelopmentDevelopm

.O

peration

Research

Phase 1

Phase 2Phase 3

Launch

14

Risk Review

Risk Assessment

Risk Evaluationunacceptable

Risk Control

Risk Analysis

Risk Reduction

Risk Identification

Review Events

Risk Acceptance

InitiateQuality Risk Management Process

Output / Result of theQuality Risk Management Process

Ris k

Man age m

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Com

mun

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Team

focu

sed

Inte

rnal

cons

ulta

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Stak

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vem

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Responsibilities in regulatory operationsIndustry

A) Reviewers

EXAMPLE

B) Inspectorates

15

Formulation Strategies for Phase I/II Clinical Programs –General Outline

The overall sequence for DP development for each phase/clinical trial can be summarized asfollows:

• Define the best formulation, with the choice of excipients based on maximizing the physicaland chemical stability of the API

• Ensure the formulation provides the desired in vitro release of drug

• Conduct pharmacokinetic studies in animals, if models are available that are known to predict clinical responses.

• Define the best manufacturing process for DP

• Place the final DP prototype on accelerated stability in intended packaging

• Conduct GMP manufacture and packaging of clinical DP

• Generate batch release data and certificate of analysis (CoA) for clinical DP

• Initiate an accelerated stability program for clinical DP (batch made at full scale)

• Submit supporting formulation and analytical data as part of the regulatory filing to requestapproval (i.e., from the FDA, EU, etc.) for using the DP in a clinical study

16

Formulation Strategies for Phase I/II Clinical Programs –General Considerations Oral Dosage Forms

•Material Property Assessment

•API (solubility, Polymorphism XRD etc.)•PSD (DLS, LLD)•Morphology (SEM)•Compound Dissolution•Flow/cohesion•Powder compaction•Hardness, tensile strength, brittel fracture index•Excipient/API interactions•Degradation Pathways

17

Formulation Strategies for Phase I/II Clinical Programs –General Considerations Oral Dosage Forms

•Bioavailability Enhancement

•API (solubility enhancement)

•PSD (micronization)

•Solubility Screening, w/o partition

•Precipitation inhibition (API/surfactant/polymer combinations)

•Amorphous Dispersions („solid“ solutions, dispersion in polymer matrix)

•Coatings (multi-particulates in capsules)

•Lipid Systems (fat-matrix, SEDDS, SMEDDS, liposomal carrier)

18

Formulation Strategies for Phase I/II Clinical Programs –IR-Oral Dosage Forms

•Capsule, Tablet (IR dosage forms)

•Direct compression

•Dry Granulation

•Wet Granulation

•Tabletting/Capsule Filling

•Film Coating

•Hot Melt Extrusion

19

Formulation Strategies for Phase I/II Clinical Programs –CR - Oral Dosage Forms

•Capsule, Tablet (CR dosage forms)

•Matrix

•Multiparticulates

•Soft Gel Capsules

•Liquid filled Capsules

•Fuctional Film Coating

•Hot Melt Extrusion

•Osmotic Systems

20

Formulation Strategies for Phase I/II Clinical Programs –Solid Orals - Excipients

Unit dose to contain powders or controlled release pellets

1%-5%GelatinHPMCPolysaccharides

Capsules

Improves powder flow and prevents static charging

Less than 1%Fumed silicaTalc

Glidants

Tailors drug release rate10%-95%HPMCPolyethylene oxidePolyvinylpyrrolidone (PVP)

Controlled release/matrix

Aids in breakup of tablets or granules in aqueous media

Less than 5%Sodium starch glycolateCroscarmellose sodium Crospovidone

Disintegrants

Prevents sticking of formulation to processing surfaces

Less than 2%Magnesium stearate Stearic acidGlyceryl behenate

Lubricants

Provides strength in dry and wet processing of powders

5%-10%Hydroxypropyl cellulose (HPC)HPMCPovidone

Binders

Imparts compressibility and tensile strength to tablets

10%-95%MannitolMicrocrystalline cellulose Starch

Ductile fillers

Imparts hardness and strength to tablets

10%-95%LactoseCalcium phosphate, dibasic

Brittle fillers

FunctionApproximate ranges (%)MaterialsExcipient type

Formulation ExcipientsSolid Orals

21


Cosmetic or controlled release coatings1%-30%HPMCCellulose acetate , Ethylcellulose, Polymeric acrylates

Coating ingredients Film polymers

Cosmetic appearance, marketingLess than 2%Titanium dioxide, Iron oxides, Dyes and lakes

Colorants

Hide unpleasant drug taste, essential for chewable formulations

1%-5%SucroseAspartameMannitolFlavors

Taste masking agents

Mitigate chemical degradation, oxidation

Less than 1%BHT/BHACitric acid

Chemical stabilizers

Improve solubility and wettability of hydrophobic drugs and improve bioavailability

0.5%-5%Poloxamer 407SLSCyclodextrinsHPMC and acid derivativesHPC

Solubilizers, dispersants, precipitation inhibitors

22


Improve processability, Prevent sticking

Less than 1% Less than 0.5%

Glycerol triacetate, Fatty acid salts, esters, Polyethylene glycol,Talc

Plasticizers, Anti-tack agent

23

Formulation Strategies for Phase I/II Clinical Programs –Parenteral Dosage Forms

•Parenteral/injectable Solutions (lyophilization)

•Colloidal Suspensions (peptides, proteins)

•Emulsions

•Liposomal Systems

•Suspensions

24

Formulation Strategies for Phase I/II Clinical Programs –Liquid Orals/Parenterals Excipients

Maintain osmolarity for parenterals, adjust viscosity, mechanical stability for lyophilized cakes

Less than 10%Sodium chloride Hydroxypropylmethylcellulose (HPMC)Mannitol Dextrose

Bulking agents

Maintain pH for optimum solubility, and comfort for injectableformulations

Enough for adjusting to desired pH

Sodium chloride Sodium acetate Sodium phosphate (and corresponding acids) Sodium hydroxide

Buffering agents

Helps with poorly aqueous soluble drugs

20%-50%EthanolPolyethylene glycol

Propylene glycol N-Methylpyrrolidone

Cosolvents

Main solubilizing/suspending vehicle for all components

50%-90%WaterVegetable oils

Polyethylene glycol Propylene glycol

Diluent

FunctionApproximate ranges (%)

MaterialsExcipient type

25

Formulation Strategies for Phase I/II Clinical Programs –Oral Liquid/Parenteral - Excipients

Sweeteners Masking of drug tast

Less than 2%

Sucrose, aspartame Peppermint oil, flavors

Flavoring/tastemasking

Antioxidants, free radical scavengers

Less than 2%

Butylatedhydroxytoluene/anisole(BHT/BHA)Citric acid/citrate

Chemical stabilizers

Prevent microbial growthLess than 2%

Benzyl alcohol Methyl/ propyl parabensBenzalkoniumchloride Thimerosal

Preservatives

Bind metal impurities to prevent complexation and reactions

Less than 1%

Edetate sodium (EDTA) Citric acid/citrate

Chelating agents

Improve drug solubility, emulsification, suspension of drug particles, prevent precipitation

Less than 5%

Hydroxypropyl-beta-cyclodextrinSulfobutylether-beta-cyclodextrin

HPMCPolaxamer 407Sodium lauryl sulfate

(SLS)PhospholipidsCremophorsLabrasolVitamin E TPGS

Solubilizers/surfactants

26

Project Case Study

The information within this presentation is based on the ICH Q-IWG members expertise and experience, and represents the views of the ICH Q-IWG members for the purposes of a training workshop.

Disclaimer

27

Outline of Presentation

Ø Key Steps for Quality by Design

Ø Case Study Organization

Ø Introducing API and Drug Product § Discussion of concepts of Quality Target Product Profile, processes, composition

Ø Description of API & Drug Product process development § Discussion of illustrative examples of detailed approaches from the case study

Ø Batch release

28

Purpose of Case Study

Ø Illustrative example§ Covers the concepts and integrated implementation of ICH Q8, 9 and

10§ Not the complete content for a regulatory filing

Note: this example is not intended to represent the preferred or required approach.

29

Case Study Organization

30

Basis for Development Information

Ø Fictional active pharmaceutical ingredient (API)

Ø Drug product information is based on the ‘Sakura’ Tablet case study§ Full Sakura case study can be found at

http://www.nihs.go.jp/drug/DrugDiv-E.html

Ø Alignment between API and drug product§ API Particle size and drug product dissolution§ Hydrolytic degradation and dry granulation /direct compression

http://www.nihs.go.jp/drug/DrugDiv-E.html

31

Organization of Content

Ø Quality Target Product Profile (QTPP)

Ø API properties and assumptions

Ø Process and Drug product composition overview

Ø Initial risk assessment of unit operations

Ø Quality by Design assessment of selected unit operations

32

Quality attribute focus

Technical Examples

Ø API

Ø Drug Product

CompressionReal Time

Release testing(Assay, CU, Dissolution)

BlendingAPICrystallization

- Final crystallization step

- Blending- Direct compression

- Particle size control

- Assay and content uniformity - Dissolution

Process focus

33

Process Step Analysis

Ø For each example§ Risk assessment§ Design of experiments

• Experimental planning, execution & data analysis§ Design space definition§ Control strategy§ Batch release

Design ofExperiments

Design Space

Control Strategy

Batch Release

QRM

34

QbD Story per Unit Operation

Process Variables

Design ofExperiments

QualityRisk Management

Illustrative Examples of Unit Operations:

QTPP & CQAs

Design Space

Control Strategy

Batch Release

CompressionReal Time

Release testing(Assay, CU, Dissolution)

BlendingAPICrystallization

35

Introducing API and Drug Product

36

Assumptions & Prior Knowledge

Ø API is designated as Amokinol§ Single, neutral polymorph§ Biopharmaceutical Classification System (BCS) class II – low solubility & high permeability§ API solubility (dissolution) affected by particle size

• Crystallization step impacts particle size§ Degrades by hydrolytic mechanism

• Higher water levels and elevated temperatures will increase degradation• Degradates are water soluble, so last processing removal point is the aqueous extraction step• Degradates are not rejected in the crystallization step

Ø In vitro-in vivo correlation (IVIVC) established – allows dissolution to be used as surrogate for clinical performance

Ø Drug product is oral immediate release tablet

37

Quality Target Product Profile (QTPP)Safety and Efficacy Requirements

Appearance, elegance, size, unit integrity and other characteristics

No off-taste, uniform color, and suitable for global marketSubjective Properties

Hydrolysis degradation & dissolution changes controlled by packaging

Degradates below ICH or to be qualified and no changes in bioperformance over expiry period

Chemical and Drug Product Stability: 2 year shelf life (worldwide = 30ºC)

Acceptable API PSDDissolution

PSD that does not impact bioperformance or pharmprocessing

Patient efficacy – Particle Size Distribution (PSD)

Acceptable hydrolysis degradate levels at release, appropriate manufacturing environment controls

Impurities and/or degradatesbelow ICH or to be qualifiedPatient Safety – chemical purity

Identity, Assay and Uniformity30 mgDose

Translation into Quality Target Product Profile (QTPP)Characteristics / RequirementsTablet

QTPP may evolve during lifecycle – during development and commercial manufacture - as new knowledge is gained e.g. new patient needs are identified, new technical information is obtained about the product etc.

38

API Unit Operations

Coupling Reaction

Aqueous Extractions

DistillativeSolvent Switch

Semi ContinuousCrystallization

Centrifugal Filtration

Rotary Drying

Coupling of API Starting Materials

Removes water, prepares API for crystallization step

Addition of API in solution and anti-solvent to a seed slurry

Filtration and washing of API

Drying off crystallization solvents

Removes unreacted materials. Done cold to minimize risk of degradation

Understandformation

& removal of impurities

Example from Case Study

39

Tablet Formulation

Pharmacopoeialor other compendialspecification

40

Drug Product Process

Blending

Lubrication

Compression

Film coating

API and ExcipientsAmokinolD-mannitolCalcium hydrogen phosphate hydrateSodium starch glycolate

LubricantMagnesium Stearate

CoatingHPMC，Macrogol 6000titanium oxideiron sesquioxide

41

Overview of API and Drug Product Case Study Elements

Representative Examples from the full Case Study

42

Overall Risk Assessment for Process

Cou

plin

g R

eact

ion

Aqu

eous

Ex

tract

ions

Dis

tilla

tive

Solv

ent S

witc

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mi-

Con

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Cry

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lizat

ion

Cen

trifu

gal

Filtr

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Rot

ary

Dry

ing

Man

ufac

ture

M

oist

ure

Con

trol

Ble

ndin

g

Lubr

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ion

Com

pres

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Coa

ting

Pack

agin

g

in vivo performance*Dissolution

AssayDegradation

Content UniformityAppearance

FriabilityStability-chemicalStability-physical

Drug Substance Drug Product

* includes bioperformace of API, and safety(API purity)

• additional study required• known or potential impact to CQA

• known or potential impact to CQA• current controls mitigate risk

• no impact to CQA

Process Steps

CQA


43

Overall Risk Assessment for Process

Cou

plin

g R

eact

ion

Aqu

eous

Ex

tract

ions

Dis

tilla

tive

Solv

ent S

witc

hSe

mi-

Con

tinuo

us

Cry

stal

lizat

ion

Cen

trifu

gal

Filtr

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n

Rot

ary

Dry

ing

Man

ufac

ture

M

oist

ure

Con

trol

Ble

ndin

g

Lubr

icat

ion

Com

pres

sion

Coa

ting

Pack

agin

g

in vivo performance*Dissolution

AssayDegradation

Content UniformityAppearance

FriabilityStability-chemicalStability-physical

Drug Substance Drug Product

* includes bioperformace of API, and safety(API purity)

• additional study required• known or potential impact to CQA

• known or potential impact to CQA• current controls mitigate risk

• no impact to CQAProcess Steps

CQA

44

API Semi-Continuous CrystallizationØ Designed to minimize hydrolytic degradation (degradate below

qualified levels)§ Univariate experimentation example

• FMEA of crystallization process parameters– High risk for temperature, feed time, water level

• Test upper end of parameter ranges (represents worst case) with variation in water content only and monitor degradation

• Proven acceptable upper limits defined for above parametersNote that in this case study, the distillative solvent switch prior to crystallization and crystallization itself are conducted at lower temperatures and no degradation occurs in these steps

45

API Semi-Continuous CrystallizationØ Designed to control particle size

§ Multivariate DOE example leading to predictive model• FMEA of parameters using prior knowledge

– High risk for addition time, % seed, temperature, agitation• DOE: half fraction factorial using experimental ranges based on QTPP,

operational flexibility & prior knowledge• Design space based on predictive model obtained by statistical analysis of

DOE dataØ Particle size distribution (PSD) qualified in formulation DOE and

dissolution studies

46

Risk Assessment: Particle Size Distribution (PSD) Control

What is the Impact that ------------- will have on PSD? 1) minimal 5) moderate 9) significantWhat is the Probability that variations in ------------ will occur? 1) unlikely 5) moderately likely 9) highly likelyWhat is our Ability to Detect a meaningful variation in --------------- at a meaningful control point? 1) certain 5) moderate 9) unlikely

Unit Operation Parameter

IMPA

CTPR

OB.

Dete

ct

RPNComments

Crystallization Feed Temperature 1 5 1 5

Prior knowledge (slowness of crystallization kinetics) ensures that the hot crystallizer feed will be well dispersed and thermally equilibrated before crystallizing. Hence no impact of feed temp variation on crystal size.

Crystallization Water content of Feed 1 5 5 25 Prior knowledge (solubility data) shows that small variations in water do not affect crystalliation kinetics.

Crystallization Addition Time (Feed Rate) 9 5 9 405Fast addition could result in uncontrolled crystallization. Detection of short addition time could occur too late to prevent this uncontrolled crystallization, and thus impact final PSD.

Crystallization Seed wt percentage 9 5 5 225 Prior knowledge (Chemical Engineering theory) highlights seed wt percentage variations as a potential source of final PSD variation

Crystallization Antisolvent percentage 1 1 1 1Yield loss to crystallization already low (< 5%), so reasonable variations in antisolvent percentage (+/- 10%) will not affect the percent of batch crystallized, and will not affect PSD

Crystallization Temperature 9 5 9 405Change in crystallization temperature is easily detected, but rated high since no possible corrective action (such as, if seed has been dissolved)

Crystallization Agitation (tip speed) 9 5 5 225Prior knowledge indicates that final PSD highly sensitive to Agitation, thus requiring further study.

Crystallization Seed particle size distribution 9 1 1 9 Seed PSD controlled by release assay performed after air attrition milling.

Crystallization Feed Concentration 1 1 1 1 Same logic as for antisolvent percentage

To be investigatedin DOE

47

Options for Depicting a Design Space

Large square represents the ranges tested in the DOE.Red area represents points of failureGreen area represents points of success.

Ø Oval = full design space represented by equation

Ø Rectangle represent ranges§ Simple, but a portion of the design

space is not utilized§ Could use other rectangles within oval

Ø Exact choice of above options can be driven by business factors

Temperature

Pres

sure

Ø For purposes of this case study, an acceptable design space based on ranges was chosen

Seed

wt%

48

API Crystallization: Design Space & Control Strategy

ØControl Strategy should address:§ Parameter controls

• Distillative solvent switch achieves target water content• Crystallization parameters are within the design space

§ Testing• API feed solution tested for water content• Final API will be tested for hydrolysis degradate• Using the predictive model, PSD does not need to be routinely tested since it is

consistently controlled by the process parameters

49

Design Space / Control StrategyParameter controls & Testing

Particle Size Crystallization Temperature 20 to 30ºC Control between 23 and 27ºC

Particle Size Crystallization Feed Time 5 to 15 hours Control via flow rate settings

Particle Size Crystallization Agitation 1.1 to 2.5 m/sQuality system should ensure changes in agitator size result in change to speed setting

Particle Size Crystallization Seed Wt% 1 to 2 wt%Controlled through weigh scales and overcheck

Hydrolysis Degradate

Distillation / Crystallization

Water Content < 1 vol% Control via in-process assay

Particle size will be tested in this example, since the result is includedin the mathematical model used for dissolution.


50

Drug Product

Ø Immediate release tablet containing 30 mg Amokinol

Ø Rationale for formulation composition and process selection provided

Ø In vitro-in vivo correlation (IVIVC) determination§ Correlation shown between pharmacokinetic data and dissolution results§ Robust dissolution measurement needed

• For a low solubility drug, close monitoring is important

51

Drug Product Direct Compression Manufacturing Process

Focus of Story


Lubrication

52

Initial Quality Risk AssessmentØ Impact of Formulation and Process unit operations on Tablet CQAs

assessed using prior knowledge§ Also consider the impact of excipient characteristics on the CQAs

Drug substance

particle size

Moisturecontent in

manufactureBlending Lubrication Compression Coating Packaging

- Low risk - Medium risk - High risk

DegradationContent uniformityAppearanceFriabilityStability-chemicalStability-physical

in vivo performanceDissolutionAssay


53

Drug Product CQA – Dissolution Summary

Ø Quality risk assessment§ High impact risk for API particle size, filler, lubrication and compression

• Fillers selected based on experimental work to confirm compatibility with Amokinol and acceptable compression and product dissolution characteristics

§ API particle size affects both bioavailability & dissolutionØ Multivariate DOE to determine factors that affect dissolution and extent of their

impactØ Predictive mathematical model generated

§ Confirmed by comparison of results from model vs. actual dissolution testingØ Possible graphical representations of this design space

54

Predictive Model for DissolutionA mathematical representation of the design space

Batch 1 Batch 2 Batch 3

Model prediction 89.8 87.3 88.5

Dissolution testing result92.8

(88.4–94.2)90.3

(89.0-102.5)91.5

(90.5-93.5)

Prediction algorithm:Diss = 108.9 – 11.96 × API – 7.556×10-5 × MgSt – 0.1849 × LubT –3.783×10-2 × Hard – 2.557×10-5 × MgSt × LubT

Factors include: API PSD, lubricant (magnesium stearate) specific surface area, lubrication time, tablet hardness (via compression force)Confirmation of model


Continue model verification with dissolution testing of production material, as needed

55

Dissolution: Control StrategyØ Controls of input material CQAs

§ API particle size• Control of crystallisation step

§ Magnesium stearate specific surface area• Specification for incoming material

Ø Controls of process parameter CPPs§ Lubrication step blending time within design space§ Compression force (set for tablet hardness) within design space

• Tablet press force-feedback control system

Ø Prediction mathematical model§ Use in place of dissolution testing of finished drug product§ Potentially allows process to be adjusted for variation (e.g. in API particle size)

and still assure dissolution performance

56

Drug Product CQA -Assay & Content Uniformity Summary

Ø Quality risk assessment§ Potential impact for API particle size, moisture control, blending, and lubrication§ Moisture will be controlled in manufacturing environment

Ø Consider possible control strategy approaches§ Experimental plan to develop design space using input material and process factors§ In-process monitoring

Ø Assay assured by weight control of tablets made from uniform powder blend with acceptable API content by HPLC§ Blend homogeneity by on-line NIR to determine blending endpoint, includes feedback loop§ API assay in blend tested by HPLC§ Tablet weight by automatic weight control with feedback loop

57

Blending Process Control Options

Ø Decision on conventional vs. RTR testing


58

Process Control Option 2 Blend uniformity monitored using a process analyser

ØOn-line NIR spectrometer used to confirm scale up of blending

ØBlending operation complete when mean spectral std. dev. reaches plateau region§ Plateau may be detected using statistical

test or rules

ØFeedback control to turn off blenderØCompany verifies blend does not

segregate downstream§ Assays tablets to confirm uniformity§ Conducts studies to try to segregate API

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0 32 64 96 128Revolution (block number)

mea

n sp

ectr

al s

tand

ard

devi

atio

n

Pilot ScaleFull Scale

Plateau region

Number of Revolutions of Blender

Data analysis model will be providedPlan for updating of model available

Acknowledgement: adapted from ISPE PQLI Team


59

Batch Release Strategy

Ø Finished product not tested for assay, CU and dissolution Ø Input materials meet specifications and are tested

§ API particle size distribution§ Magnesium stearate specific surface area

Ø Assay calculation§ Verify (API assay of blend by HPLC) X (tablet weight)§ Tablet weight by automatic weight control (feedback loop), %RSD of 10 tablets

Ø Content Uniformity§ On-line NIR criteria met for end of blending (blend homogeneity)§ Tablet weight control results checked

Ø Dissolution§ Predictive model using input and process parameters calculates for each batch that dissolution meets

acceptance criteria§ Input and process parameters used are within the filed design space

• Compression force is monitored for tablet hardness

Ø Water content§ NMT 3% in finished product (not covered in this case study)

60

Drug Product Specifications

Ø Use for stability, regulatory testing, site change, whenever RTR testing is not possibleØ Input materials meet specifications and are tested

§ API PSD§ Magnesium stearate specific surface area

Ø Assay calculation (drug product acceptance criteria 95-105% by HPLC)§ Verify (API assay of blend by HPLC) X (tablet weight)§ Tablet weight by automatic weight control (feedback loop)

• For 10 tablets per sampling point, <2% RSD for weights

Ø Content Uniformity (drug product acceptance criteria meets compendia)§ On-line NIR criteria met for end of blending (blend homogeneity)§ Tablet weight control results checked

Ø Dissolution (drug product acceptance criteria min 85% in 30 minutes)§ Predictive model using input and process parameters for each batch calculates whether dissolution meets acceptance criteria§ Input and process parameters are all within the filed design space

• Compression force is controlled for tablet hardness

Ø Water content (drug product acceptance criteria NMT 3 wt% by KF)

61

Iterative risk assessments

Initial QRAPHA FMEA FMEA FMEA

API Crystallization

Blending

Lubrication

Compression

API PSD

Lubricant

Lubrication time

Hardness

Content uniformity

Beginning DesignSpace

Controlstrategy

Blending time

Lubricant amount

Lubrication time

Pressure

Tablet weight

API PSD model

Blending timeFeedback control

Mg stearate SSA

Lubrication time

Pressure

Automated Weight control

Blend homogeneity

High Risk Medium Risk Low Risk

API PSD

62

Conclusions

Ø Better process knowledge is the outcome of QbD development

Ø Provides the opportunity for flexible change management

Ø Use Quality Risk Management proactively

Ø Multiple approaches for experimental design are possible

Ø Multiple ways of presenting Design Space are acceptable§ Predictive models need to be confirmed and maintained

Ø Real Time Release Testing (RTRT) is an option§ Opportunity for efficiency and flexibility