Sample Plan Justification and Control Strategy

Implementation for Continuous Manufacturing

Kelly A. Swinney, Ph.D.

Vertex Pharmaceuticals, Inc.

AAPS 2015

Vertex’s Commitment to CM

2

Drivers include: 1. High quality, consistent product

2. Early finalization of formulation/process on commercial scale

3. “Data rich” QbD commercial design space

Implementing CM across development

portfolio

CM Rig is a comprehensive

equipment train: blending to film

coating

CM Rig is designed with PAT to allow for

IPC and Real Time Release Testing

Continuous Manufacturing Control Strategy and PAT

3

Control strategy is based on a QbD approach to process development and design space definition at commercial scale

PAT can be employed for process control, in-process control measurements, monitoring of design space, and release (RTRT)

PAT includes spectroscopic and non-spectroscopic technology

©2012 Vertex Pharmaceuticals Incorporated 4 4 ©2012 Vertex Pharmaceuticals Incorporated .

Powder In

Day 1 AM

Day 1 AM Coated Tablets Out

Vertex’s Continuous

Manufacturing Rig

Much Smaller Footprint

• Smaller scale equipment

• All unit ops in one facility

PAT Based Control Strategy => IPCs + RTRT

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Tablet Press

PFLS

W Th H

PAT 5 b

Waste

STEP 6 , COMPRESSION

Fluid Bed Dryer

drying air in

drying air out

Granulation liquid 1

PAT 4 LHP

100 L

1000 L 1000 L 1000 L HC

10 L

Mill

PAT 3 b

PAT 3 a LHP 10 L

100 L 100 L

10 L

Deduster

MC

Bucket Lift

STEP 5 , FEEDER / BLENDER 2 STEP 1 , FEEDER / BLENDER 1

STEP 2 , TWIN SCREW GRANULATOR

PAT 1 NIR , measures material attributes during

screening of raw materials

PAT 2 , NIR , measures composition and BU

PAT 3 a , NIR , measures granule uniformity , LOD ,

solid state form and physical attributes of

granules

PAT 3 b , Laser Diffraction , measures particle size

distribution

PAT 4 , NIR , measures composition and BU

PAT 5 a , Raman , measures assay and CU

PAT 5 b , Weight , hardness , thickness

PAT 6 , Raman , measures coat thickness

STEP 7 , COATING

STEP 3 , FLUIDIZED BED DRYER

STEP 4 , MILLING

Coating Liquid

Finished Product

STEP 1 , FEEDER / BLENDER 1

PAT 5 a

• Tablet Tester

• Raman

• NIR

• Laser Diffraction

• NIR

PAT Locations Available for IPC and RTRT Measurements

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• Loss In Weight

Feeders

• Dryer Thermocouple

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Components of a Continuous Manufacturing Control Strategy

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P ro d u c t K e y

IP C L im it

IP C L im it

A c tio n L im it

A c tio n L im it

Process Control System for Comprehensive Process and

Product Monitoring

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• Control software displays all active unit operations and alarms on HMI

• IPCs, CPPs, and PPs with design space limits are monitored in real time

• Process control charts available for operator review

• Material is tracked through the system and segregated if manufactured outside of

the design space or if it does not conform to IPC acceptance criteria

• Batch summary reports: material tracking, alarms, IPCs, CPPs and PPs with

design spaces, etc. available for batch review

Example In-Process Controls for a Continuous Wet

Granulation Manufacturing Process

Step In-Process Control

IG Blending LIW feeder mass flow

Drying Granule water content

EG Blending LIW feeder mass flow

Final blend potency

Compression Core tablet weight, thickness, hardness

• IPCs: similar to what would be

expected for a batch process

• For CM: PAT employed for IPC

measurements in real time

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At what frequency should IPCs be assessed for CM?

Sampling Plan for In-Process Controls

• Sampling plan should be defined for each IPC – Needs to take into account equipment capability

– Needs to take into account for short term & long term process variation

and process drift

– Minimum sampling that must be met for each IPC should be defined and

statistically justified

• Actual IPC sampling achieved: NLT minimum required sampling

• IPC sampling achieved >> than for typical batch process

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Things to Consider – Sampling and Process Control

• CM, in general, does not permit reprocessing

– Non-conformance to IPC acceptance criteria results in removal of the

material from the process

– Operator / control actions limits should be set within the IPC acceptance limit

range to ensure that IPC acceptance criteria are met

– Action limits should be taken into account in defining and justifying the

sampling plan

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Material Flow Rate (Line Rate/Throughput) and Sampling

Advantages to defining the sampling

plan as a function of mass

• Sampling frequency automatically

adjusts with material flow rate (line

rate)

• Regardless of mass flow, the same

number of samples/mass is targeted

– Sample frequency increases with

increasing material flow rate

– Sample frequency decreases with

decreasing material flow rate

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Sampling

Point

Line Rate 10 kg/hr

PK 1

PK 2

PK 4

PK 3

PK 1

PK 2

PK 4

PK 3

30 kg/hr

Time Triggered

Sampling Frequency

PK 1

PK 2

PK 4

PK 3

PK 1

PK 2

PK 4

PK 3

10 kg/hr 30 kg/hr

Mass Triggered

Product Key (PK): unit of mass manufactured (~1 kg) and tracked through the system

Statistical Analysis for Sampling Plan Definition and

Justification

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• How much material can be processed without exceeding a predefined

step change threshold ?

– Step change threshold change that is acceptable between IPC measurements

• Lag analysis of material attribute data generated during continuous

manufacture

– Capable of capturing short term variation, long term variation, and process drifts not

centered around target

– Calculate “Lag k Difference” for the material attribute for each of a select number of

continuously manufactured batches for lags ranging from k=1 to k=n

– The “Lag k Difference” is defined as the difference between the material attribute

results for PKs that are spaced k PKs apart

Lag k Difference Number of PKs Between the

Analyzed PKs

Lag 1 0

Lag 2 1

Lag 3 2

Lag 4 3

Lag 5 4

Lag 6 5

Lag 7 6

Statistical Analysis for Sampling Plan Definition and

Justification

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– Pool the “lag K difference” results for each k obtained from the batches

analyzed and calculate the lower and upper 95% limits

– Determine the number of consecutively manufactured PKs that can be

manufactured between sampling points without exceeding the step change

threshold

• Defines the minimum sampling frequency

• E.g. Step change threshold = 3.5; NMT 3 consecutively manufactured

PKs can exist between sampling points (PKs) without exceeding step

change threshold

Lag k Difference Number of PKs Between

the Analyzed PKs

Lower 95% Limit Upper 95% Limit

Lag 1 0 -1.74 1.38

Lag 2 1 -2.16 1.42

Lag 3 2 -2.62 1.57

Lag 4 3 -3.34 1.78

Lag 5 4 -3.84 1.68

Lag 6 5 -4.08 1.74

Lag 7 6 -4.09 1.65

Action Limits

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• Action Limits:

• Set inside the IPC limits and NLT the step change threshold from the IPC limit

• Used to alert the operator adjustment to the process is needed

• Ensures the process remains in control and that non-conforming PKs are

identified with NLT 97.5% confidence

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P ro d u c t K e y

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NLT step change threshold

NLT step change threshold

Things to Consider

• NIR systems used for IPCs

• The performance of the spectrometers should be routinely

verified during operation

– Measurement interface cleaned, the spectrometer re-zeroed, and

the baseline verified approximately every couple hours

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When an NIR system is undergoing its on-going performance

verification, it is not available to perform IPC measurements.

How can compliance with the sampling plan be ensured?

Redundancy

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• Engineering Definition

– The inclusion of extra components

that are not strictly necessary to

functioning, in case of failure in other

components

• Examples

– Back-up controls, radio links, engines

and power systems in airplanes

– Extra hard drives and power supplies

in computers used in datacenters

Example In-Process Controls for a Continuous Wet Granulation

Manufacturing Process - Redundant IPC measurements

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Step In-Process Control Method(s)

IG Blending LIW Feeder mass flow Gravimetric

Drying Granule water content Granule discharge temperature

NIR (milled granules)

EG Blending LIW Feeder mass flow Gravimetric

Final Blend Potency NIR (final blend)

NIR (milled granules) + EG LIW feeders

Compression Core tablet weight thickness, hardness PAT 5 (Kraemer)

• Method redundancy is built into the IPC strategy for CM

− However, only one method is required per IPC for manufacture

• Ensures continuous monitoring of the process

− Coverage when NIR systems are undergoing on-going performance verification

• Intention is to operate with both methods with a target sampling plan of every PK

− If discrepancies between results arise, the non-conforming result will be acted on

Decision Tree for IPC Test Results

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Decision Tree for IPC Test Results

Redundant

IPC Result 1

Redundant

IPC Result 2Conformance

Does not

Conform

Pass

Pass

Fail

Not

Available

or None

Identified

Fail

Not

Available

or None

Identified

Not

Available

Not

Available

or None

Identified

Investigate

Pass Pass

Conforms

Conforms

Does not

Conform

Things to Consider – Failure to Meet IPC Sampling

Criteria

• Need to have an system in place to identify in real time if

the sampling criteria has not been met

– This can be a combination of procedural controls and automated

processes

– Operator should be alerted

• Impacted material should be down streamed processed to a

segregation point and removed from the process

– Procedures should be in place to investigate the event and evaluate

the impacted material

Data used to define and justify the sampling plan can be

leveraged for assessing material with “no IPC data”

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Investigating material with “No IPC Data”

• “Lag k difference” analysis results can be leveraged during the

investigation to assess with high confidence whether or not the

material conforms to the IPC acceptance criteria

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Lag k Difference Number of PKs Between

the Analyzed PKs

Lower 95% Limit Upper 95% Limit

Lag 1 0 -1.74 1.38

Lag 2 1 -2.16 1.42

Lag 3 2 -2.62 1.57

Lag 4 3 -3.34 1.78

Lag 5 4 -3.84 1.68

Lag 6 5 -4.08 1.74

Lag 7 6 -4.09 1.65

Number of Contiguous PKs with No IPC Results Maximum 95% Limit

1 2.16

2 2.62

3 3.34

4 3.84

5 4.08

6 4.09

Investigating material with “No IPC Data”

• In the absence of an IPC result, evaluate the IPC data obtained before and after the

absence of data

• Use the “lag K difference” analysis results to determine with NLT 97.5% confidence whether

the material conforms or does not conform to the IPC acceptance criteria

• Downstream process the material if it is confirmed that the material also conforms to all other

IPC acceptance criteria and was manufactured within the design space

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Number of Contiguous PKs with No IPC Results Maximum 95% Limit

1 2.16

2 2.62

3 3.34

4 3.84

5 4.08

6 4.09

PK7 PK10

Example of RTRT for Continuous Manufacturing

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• A composite sample will be taken after tablet printing for retains, stability, and any

release testing not amenable to RTRT (e.g. appearance)

• Traditional end product testing performed for appearance

Critical Quality Attribute

PAT Technology RTRT Method Material

Identification Raman Confirm presence of API Core Tablet

Assay NIR

Weight

API Content

Tablet Weight

Final Blend

Core Tablet

Dissolution

Laser Diffraction

NIR

WTH

Granule Particle Size

API Content, Water Content

Tablet Weight, Hardness, Thickness

Milled Granules

Final Blend

Core Tablet

Water Content NIR Water Content Final Blend

Content Uniformity

NIR

Weight

Variance in API Content

Variance in Tablet weight

Final Blend

Core Tablet

Physical Form Raman API physical form Core Tablet

PAT Methods Sample a Large Percentage of the Batch

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Analysis of a hand full of tablets by Regulatory QC Methods

vs

PAT data collected repeatedly during manufacture

How much sampling is required for RTRT to appropriately

characterize the batch?

T im e

% T

arg

et

A P I C o n te n t - F in a l B le n d (% T a rg e t )

T a b le t W e ig h t (% T a rg e t )

U p p e r L im it

L o w e r L im it

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Target Sampling Rate Per PAT Measurement

• A target sampling rate is defined for each PAT measurement used in a

RTRT calculation for an end product CQA

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PAT Technology Material Measured Attribute Target Rate

NIR (PAT 3) Milled granules

Water content in granules

DS content in granules

Once per minute

Laser Diffraction (PAT 3) Milled granules Particle size distribution Once per minute

NIR (PAT 4) Final blend DS content

Water Content Once per minute

Raman (PAT 5) Core tablet DS identification

DS physical form Once per 2 minutes

WTH (PAT 5) Core tablet

Weight

Thickness

Hardness

Once per 2 minutes

Example RTRT Minimal Sample Size

• A minimum sample size is defined for each PAT point used in a RTRT calculation

• Achieved sample size is a metric that can be trended as a performance indicator

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Critical Quality Attribute

PAT Technology In-Process Material Attribute Minimum Sample Size

Identification Raman API identification in core tablets NLT 10 Tablets

Assay NIR Final blend API content NLT 50%*

Weight Core tablet weight NLT 50%*

Dissolution

Laser Diffraction Milled granule particle size distribution NLT 50%*

NIR Final blend API and water content NLT 50% *

WTH Core tablet weight, thickness, hardness NLT 50%*

Water Content NIR Final blend water content NLT 50%*

Content Uniformity

NIR Final blend API content NLT 50%*

Weight Core tablet weight NLT 50%*

Physical Form Raman API physical form in core tablets NLT 10 Tablets

NValid Results = Number of valid results obtained

NTarget Results = Theoretical number of results at the target measurement rate

𝐴𝑐𝑡𝑢𝑎𝑙 𝑆𝑎𝑚𝑝𝑙𝑒 𝑆𝑖𝑧𝑒 = 𝑁𝑉𝑎𝑙𝑖𝑑 𝑅𝑒𝑠𝑢𝑙𝑡𝑠

𝑁𝑇𝑎𝑟𝑔𝑒𝑡 𝑅𝑒𝑠𝑢𝑙𝑡𝑠× 100

Actual Sample Size for Assay, Dissolution, Water Content, and Content Uniformity

* NLT 50% target sample size achieved + NMT 15% in a contiguous segment not sampled

Statistical Analysis for Justifying Minimum Sample Size for

RTRT Calculation

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Bootstrap analysis to demonstrate that there is no appreciable difference in the attribute

result calculated when 100% target sampling is achieved versus the minimum

• Bootstrap Analysis • Randomly select a 15% contiguous segment and remove it

from the data set

• Randomly remove 35% of the remaining data

• Calculate the mean and standard deviation

• Repeat for 100,000 iterations

• Determine the mean and upper and lower 95% limits for both

the mean and standard deviation results

• Compare the bootstrapping results (mean and standard

deviation) with the results obtained with 100% sampling (true

mean)

• Demonstrate that the difference between the 95% limits and

the true mean is also acceptable

15% contiguous segment removed

35% of remaining data removed

Batch

Mean (% Target) Standard Deviation

(% Target)

True

Mean

Minimum

Sample

Size

Absolute

Difference

True Std

Dev

Minimum

Sample

Size

Absolute

Difference

1 97.23 97.22 0.010 0.79 0.78 0.016

2 96.99 97.00 0.009 0.74 0.74 0.002

3 98.78 98.77 0.007 1.22 1.21 0.007

4 101.07 101.01 0.058 1.29 1.27 0.020

5 101.12 101.12 0.002 0.61 0.62 0.005

6 102.96 102.95 0.014 0.79 0.77 0.018

Conclusions

• CM control strategy implementation requires a sophisticated process

control system

• In-process controls require real time PAT measurements (spectroscopic

and/or non-spectroscopic) that can be acted on in real time

• Redundancy in the IPC methodology ensures continuous monitoring of

the process and quality throughout the batch

– However, process control system must also be able to assess

conformance to the sampling plan in real time and take the appropriate

actions

• Definition and justification of the IPC sampling plan requires an

approach that takes into account short term and long term process

variation as well as process drift from target

• For RTRT, the minimum sample size required to appropriately calculate

the RTRT results should be understood

– Achieved sample size is a metric that can be trended as a performance

indicator

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Acknowledgements

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• Team at Vertex

– Pharmaceutical Development

– Technical Operations

– Supply Chain Management

– Quality

– CMC Regulatory

– Facilities

• Equipment manufacturers

• Our CMOs, suppliers, and research collaborators

• FDA, EMA, MHRA