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Method SelectionHow does understanding ‘why’ measurements are made affect the process of analytical method development?


What is Quality by Design?

August 13, 2019Title of the presentation2

“A systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management…”ICH Q8 (R2)


What does Quality by Design avoid?



Applying QbD to drug product development

Define QTPP

Identify CQAs

Risk Assessment: define CMAs / CPPs

Design Space Definition

Control Strategy

Life Cycle Management

Patient NeedsQTTP: Quality Target Product Profile

CQA: Critical Quality Attributes

Drug Product ControlMaintain QTTP through continuous

assessment of CMAs / CPPs

Drug Product DesignCMA: Critical Material Attributes

CPP: Critical Process Parameters


Applying QbD to analytical method development

Define QTPP

Identify CQAs

Risk Assessment: define CMAs / CPPs

Design Space Definition

Control Strategy


Analytical Target Profile

Identify Critical Method Attributes

Risk Assessment

Method Design Space Definition

Control Strategy



Laser diffraction particle size analysis

August 13, 20196

Particle scattering pattern

• Wide measurement range• 10nm – 3.5mm

• Rapid data acquisition rate• Aids understanding of device operation• Provides a good screening technique

Emulsion, suspension and dry powder analysis


Step 1: Identify Analytical Target Profile


When is particle size considered a CMA?

No further action

Critical to dissolution, solubility or bioavailability?

Critical to product stability?

Critical to product content uniformity?If ‘yes’ to any of these, measure particle size.

Critical to drug product processability?

Solid dosage formor liquid suspension?

No

Yes

ICH Q6ADecision Tree 3

Critical to maintaining product appearance?



BCS Classification Scheme MCS Classification Scheme

Answers the question: do the physical properties of the API fit with bioavailability requirements.

Answers the question: do the physical properties of the API fit with process requirements

Particle size can be predictive within each classification scheme



• Focus on continuous manufacturing is increasing

• Move to continuous manufacturing changes the paradigm for OSD product development:

• Old approach: customised processes were designed to fit the specific product, as blockbuster model assumed capital costs for manufacturing system development could be written off over product lifetime

• New approach: standardised processes are applied as this enables lifecycle costs to be minimised.

• Outcome: candidate drug products will not proceed through development if the formulations do not fit available continuous processing methods

13 August 201910

Shift to continuous manufacturing for Oral solid dose products

ConsiGma™ Continuous Tableting Line

‘ConsiGma was developed in compliance with the FDA’s QbD initiative. It satisfies the

industry’s need for reduced risk and higher quality while avoiding lengthy and

costly validation and scale-up to bring products to market faster and cheaper.’


Step 2: Identify Critical Method Attributes



Dr. Henk Merkus, “Quality Assurance in Particle Size Measurement”

Sampling and Dispersion



Risk Assessment


Control Strategy



Critical Method AttributesSampling


Critical Method AttributesSampling: mass required for reproducible measurements

Particle size / m

0 500 1000 1500 2000 2500 3000

Min

imum

mas

s / g

0

20

40

60

80

100

density = 1.5g/cm3

Sample mass required to give 95% confidence in the Dv90

Method Estimated max error RSD

Cone & Quartering 22.7% 6.81%

Scoop Sampling 17.1% 5.14%

Table Sampling 7.0% 2.09%

Shute Riffler 3.4% 1.01%

Spinning Riffler 0.42% 0.146%

Random Variation 0.25% 0.075%

From: T. Allen. Particle Size Measurement. Chapman and Hall. 4th Edition, 1993, Page 39. Figures based on 60:40 coarse (420-500µm) : fine (120-250µm) sample mixture


Critical Method Attributes

Agglomerated Dispersed

Dispersion



• Step 1: Chose an appropriate dispersant• Must wet the particles being measured• May require the use of surfactants

• Step 2: Add energy to improve dispersion• Apply ultrasound energy• Use additives to prevent re-agglomeration

• Step 3: Confirm results using an orthogonal method • Image analysis provides a good reference for laser diffraction

Dispersion of samples in liquids



• Step 1: control the powder feed rate (concentration)

• Step 2: determine how energy input changes the particle size

• Step 3: Compare the results to an orthogonal technique• A liquid dispersion result or image analysis provides a good reference for

dry powder laser diffraction methods

Dry Powder Dispersion

Dry powder disperser


Step 3: Risk assessment and MODR definition


Risk assessment and design space definitionWhen is the performance of a method realistic?



Risk Assessment


Control Strategy


• General advice regarding method reproducibility:

• ISO13320:2009• Take at least 5 readings• Dv50: RSD < 3%• Dv10 and Dv90: RSD < 5%• Below 10 µm, double these values.

• USP <429> and EP 2.9.13• Take at least 6 readings• Dv50: RSD <10%• Dv10 and Dv90: RSD<15%• Below 10 µm, double these values.

• Actual limits should be set based on the requirements for control of the product’s critical quality attributes


Risk assessment and design space definition

Sampling method

Weighing method Laser alignment

Optical properties

Sonication power / time

Equilibration time following sonication

Measurement time

Humidity

Temperature

Sample transfer to instrument

Sample source / lot

Verification materials

Instrument model

Analysis range

Cleanliness

Sample quantityDispersant source

Particle Sizing

Method

Laser obscuration

Sample preparation

Pump / stirrer speedPre-dispersion method

Dispersant gradeOrthogonal method

Analysis settings

Define experimentallyControlNoise factor

Risk assessment for liquid dispersion methods


Risk assessment and design space definitionDispersion of samples in liquids: dispersion using ultrasound

after ultrasound


Risk assessment and design space definitionDispersion of samples in liquids: dispersion using ultrasound


4

5

6

7

8

9

20 30 40 50 60 70 80 90 100 110

Dv9

0 (µ

m)

Sonication time (sec)

Risk assessment and design space definitionLiquid dispersion: sonication power and time

UAL

LAL




Liquid dispersion: stirrer speed

60

80

100

120

140

160

500 1000 1500 2000 2500 3000 3500

Dv9

0 / µ

m

Stirrer Speed / rpm

UAL

LAL




Liquid dispersion: measurement duration

0

1

2

3

4

5

6

7

8

0 5 10 15 20 25

% R

SD (D

v50)

Measurement duration / s

UAL



Define experimentallyControlNoise factor

Risk assessment for dry powder dispersion methods

Sampling method

Weighing method

Laser alignment

Optical properties

Dispersion pressure

Feed rate

Measurement time

Extraction

Humidity

Temperature

Sample transfer to Instrument

Sample source / lot

Verification materials

Instrument model

Analysis range

Cleanliness

Air supply

Sample quantityAir quality

Particle Sizing

Method

Laser obscuration

Orthogonal method

Analysis settings


Risk assessment and design space definitionDry powder dispersion: standard disperser pressure titration

Pressure / bar

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

Size

/ µm

0

100

200

300

400

500

600Dv10Dv50Dv90

Orthogonal method Dv90


Step 4: Control


Method ControlUSP<429> guidance for methods validation



Risk Assessment


Control Strategy


• The system’s accuracy should be assessed using a certified reference material

• The precision and robustness of the method should be assessed

• Assurance should be provided that the data generated are reproducible and control the product’s quality.

• Method precision assessment from USP<429>• Take at least 6 readings• Dv50: RSD <10%• Dv10 and Dv90: RSD<15%• Below 10 µm, double these values.


Method controlUSP<1225> guidance for method validation

• USP<1225>: elements of validation for compendial procedures

Particle sizing methods


Method control

Sample Dv10 / µm Dv50 / µm Dv90 / µm1 1.22 23.68 63.23

2 1.17 23.77 60.02

3 1.09 22.79 56.59

4 1.16 23.63 62.55

5 1.11 22.26 59.68

6 1.18 22.78 65.36

7 1.12 23.41 61.47

Mean 1.15 23.19 61.27RSD (%) 3.95 2.50 4.63

Sample Dv10 / µm Dv50 / µm Dv90 / µm1 1.06 22.92 61.01

2 1.08 22.08 56.54

3 1.04 21.66 62.17

4 0.97 22.55 60.23

5 1.04 22.74 57.98

6 0.99 23.58 59.86

7 0.95 22.11 62.78

Mean 1.02 22.52 60.08RSD (%) 4.79 2.83 3.69

Control: precision for different operators

Pooled data Dv10 Dv50 Dv90Mean / µm 1.08 22.85 60.68

Standard Deviation 0.082 0.68 2.52RSD (%) 7.6% 3.0% 4.2%


Method controlSetting product control limits

How to Establish Manufacturing Specifications, Donald J. Wheeler, Statistical Process Controls Inc. Posted on spcpress.com

Particle SizeProduct Specification

Measurement Specification

Upper Product Acceptance Limit

Lower Product Acceptance Limit

Lower Measurement Limit

Upper Measurement Limit

σσσ = measurement error


Method control

• Must tighten specifications to account for measurement variation:

• USP<429>: 10% for any central value15% for any value at the distribution edges

• D[4,3]: (80 x 1.1 = 88) Spec > 88 microns• Dv10: (30 x 1.15 = 34.5) Spec > 34.5 microns• Dv90: (1000 x 0.85 = 850) Spec < 850 microns

Evolutions in Direct Compression, Douglas McCormick, Pharmaceutical Technology, April 2005. Pg 52-62

Setting product control limits


Summary

• Realistic method definition

• Improved method robustness

• Increased probability of method transfer success

• Ease of lifecycle management• Regulatory flexibility for method adjustments within

the Method Design space• Reduced risk of specification changes during

equipment upgrades

Benefits of applying AQbD



Risk Assessment


Control Strategy



References

• Quality by design in analytical method development and validation• Priyanka P. Pande et al, J Environ Life Sci. June 2017; Vol. 2 (Issue 2): 39-45.

• Using the Analytical Target Profile to Drive the Analytical Method Lifecycle• Phil Borman et al, Analytical Chemistry, January 2019

• Quality by Design Approaches to Analytical Methods - FDA Perspective • Yubing Tang, Ph.D., FDA/CDER/ONDQA. AAPS, Washington DC, October 25, 2011

• A Quality by Design Approach for Particle Size Analysis of an Active Pharmaceutical Ingredient• Julie T. Adamson, Ph.D., American Pharmaceutical Review, July 2, 2013.

• Analytical Quality by Design (AQbD) in Pharmaceutical Development• George L. Reid, Ph.D et al, American Pharmaceutical Review, August 27, 2013.

• Implementation of QbD Approach to the Analytical Method Development and Validation for the Estimation of Propafenone Hydrochloride in Tablet Dosage Form• Monika L. Jadhav and Santosh R. Tambe, Chromatography Research International Volume 2013, Article ID 676501


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