- 1 - a roadmap for pat implementation in pharmaceutical manufacturing robert m. leasure principal...

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A Roadmap forPAT Implementation in

Pharmaceutical Manufacturing

Robert M. LeasurePrincipal ScientistSite PAT Champion

Pfizer Global Manufacturing7000 Portage Road, PORT-91-201Kalamazoo, MI 49001(269) 833-6198

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Presentation Outline Provide some Definitions about PAT

• But in the process more Questions will be asked than definitions provided.

• Asking the right Questions provides the framework for successful implementations.

Site perspective of a PAT program• Project Selection

• Resource Allocation – from site and center support

• Steps for Implementation

Examples of PAT Implementations in Kalamazoo Manufacturing Ops• Drug Product

Parental Sterile Suspension - improved content uniformity

• Drug ProductDissolution Monitoring of Active during pH adjustment

• API OperationsSolvent Recovery – improved yield from timely fraction determination.

- 3 -

Definitions

What is PAT?Process Analytical Technologies

Probes in TanksAnalyzers in Plant

Automation

Process Data (lots of it)

Things that come to mind…..

Where are you going to stick that probe?

How are you going to validate that system?

What are you going to do with that data?

Questions that come to mind…..

and Questions

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The answer is multivariate and transient.

It depends on who is asking the question,and who is giving the answer.

Technologists

Managers $$$

Quality andRegulatory Groups

Support Groups

IT,Engineering, Maintenance

What is PAT?

- 5 -

Spectrometer

Automation

Reactor

Control Room

Probe

AnalyticalInstrument

Automation

Reactor

Control Room

Probe

AnalyticalInstrument

Automation

Fiber-Optic Probe

FeedbackControl

Bona fideOn-line

PAT SystemNear-Infrared

Analog RecorderpH Probe

At-line

Reactor In-Plant Laboratory

SampleValve

Pfizer

Reactor In-Plant Laboratory

SampleValve

Pfizer

On-line

vs.

Off-line

What is PAT?(a)

- 6 -

FDA Guidance on PAT

Ajaz S. Hussain, Ph.D.Previously Deputy Directory Office ofPharmaceutical Science, CDER, FDA

FDA Guidance Document on PATReleased in September 2004.

http://www.fda.gov/cder/guidance/6419fnl.htm

Key proponent for the use of PAT inthe pharmaceutical industry.

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FDA Definition of PAT

FDA Guidance – September 2004PAT – A Framework for Innovative Pharmaceutical Manufacturing and Quality Assurance

Line 158:“For the purposes of this guidance document, PAT is considered to be a system for designing, analyzing, and controlling manufacturing through timely measurements (i.e., during processing) of critical quality and performance attributes of raw and in-process materials and processes with the goal of ensuring final product quality.”

Line 158:“For the purposes of this guidance document, PAT is considered to be a system for designing, analyzing, and controlling manufacturing through timely measurements (i.e., during processing) of critical quality and performance attributes of raw and in-process materials and processes with the goal of ensuring final product quality.”

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Who benefits from (a) PAT?

The Users

Technologists

Managers $$$

Quality andRegulatory Groups

Support Groups

IT,Engineering, Maintenance

What is (a) PAT?

1. Manufacturing Operations

2. R&D or Process Scientists

- 9 -

Where does PAT begin (and end)?Co-development or

Continuous Improvement Activities

ManufacturingOperations

PAT Project Progression

Invo

lve

men

t

"Early PAT" Used to determine

Critical Process Parameters

"Late PAT" Used to control the process

Requires formal validation Low cost / benefit ratio

R&D or

Process Support * Proceed with PATs

in development?

- 11 -

Improved quality. Improved safety.

Cost savings.

Why do PAT?

Process Control

Process Knowledge


Cost savings.


Cost savings.Fundamental Goals

Well Controlled Process

RFTRFT

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Continuous Quality Verification

Process

What is done on the plant floor.

Inputs Metrics

Dat

a

Evaluation

Requirements

Root CauseAnalysisAction

PeopleEquipmentProceduresMaterials

Cost

Schedule

Quality (Compliance)

Well Controlled Process Model

Process AnalyticsProcess Analytics

- 13 -

Use of PAT to Achieve RFT Benefits

Reduce/eliminate deviations

Improve customer service (product availability)

Reduce cycle times (operational efficiency)

Reduce inventory levels

Reduce costs (reworks, resample, retesting, etc)

Improve capacity utilization

Improve compliance (reduce deviation reports)

Improve assurance of quality

Reduced need for end product testing is a potential consequence of RFT performance, but is not the direct goal of Pfizer’s PAT strategy.

- 14 -

Six Questions

What do you want to measure?

How do you want to measure it?

Where do you want to measure?

When do you want to measure it?

Why do you want to measure it?

Who will look at the results??

?

?

?

?

?

Chemical or physical property.

Analytical technology.

Process Knowledge or Process Control?

Before, during, or after a process step?

Sampling frequency.

Validation…..

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Considerations for Project Identification Is the process “broken”?

Are there unknown or unmeasured critical process parameters?

How big is the problem?What are the risks of non-conformance?What is the cost of poor throughput?

Where should the measurement be made?At-line or On-line? (On-line is usually > 3x more $.)Are there area classification requirements? i.e., Class I Div I

How often should a measurement be made?What are the process and instrument limitations?

What decisions will be made with the data?Does Quality Operations want to intimately know the process? What are the Regulatory implications?

Will implementation affect other processes?What is the impact on Cleaning Validation and probematerial of construction compatibility?

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PAT System Qualification

PAT System Qualification and Method Validationshould be based on intended use of data.

Three Levels

1. Development or Proof of Concept

2. Information Only

3. Release Decisions

Quality Impact

No Impact

Indirect Impact

Direct Impact

Validation or Commissioning and Qualificationmust conform to applicable:

Corporate Quality Standards

Site Procedures

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Quality Impact Assessments Process Knowledge

• No Impact or Indirect Impact (validation perspective)

• Short term study used to assess process variability,and potential need for a permanent PAT

Process Monitoring• Indirect Impact, requiring “Commissioning of Equipment”

• More permanent implementation.

• Monitors process to assure RFT, but not used for decision making; i.e., registered or validated assay already exists.

Process Control• Direct Impact, requiring “Qualification of Equipment”

• Used for

- Material Release or Parametric Release

- GMP Decisions for Critical to Process Parameters (CPP)

- Advanced Process Control

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PAT Development Resources for Kalamazoo

Active Pharmaceutical Ingredients Drug Product

• Sterile Injectables• Non-sterile Fluids and Ointments

• Fermentation Operations• Chemical Operations

Two main manufacturing operations:

Site Technology Groups

Site PAT Group

Process AnalyticalSupport Group (PASG)

Right First Time (Black, Green, Yellow

Belts)

Center Function Support

Kalamazoo ProcessTechnology (KPT)

Product and ProcessTechnology (PPT)

- 20 -

Site Implementation Plan (SIMP) Updated annually, by PAT Champion. High level plan extending out 3 years. Approvals

• Site Leadership Team (KLT) and KPT &PPT Management

• US Area RFT Team Lead

• PASG Implementation Team Lead

Purpose

1. Track existing PAT projects

2. Identify potential new projects

3. Prioritize new and existing projects

4. Implementation Timing

5. Resource Allocation

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Project PrioritizationWeighting Factor:

2 2 3 3 1 1 1 3

Project

Bu

sin

ess

Are

a

Incr

ease

d P

roce

ss

Und

erst

andi

ng

Qua

lity

Impr

ovem

ent

Impr

oved

Eff

icie

ncy

or

Pro

cess

Im

prov

emen

t

EH

S Im

prov

emen

t

Pro

ject

Com

plex

ity

(dif

ficu

lt =

1, s

imp

le =

10)

Impl

emen

tato

in C

ost

(>$3

00K

= 1

, <$1

0K =

10)

Reg

ulat

ory

Con

stra

ints

(h

igh

er is

less

con

stra

ign

ed)

Site

Spe

cifi

c C

rite

rion

Ran

k as

a P

erce

ntag

e

Raman ID of Incoming Raw Materials QO 8 6 10 8 3 4 3 10 76%

UV-ATR Hydrogenation Reaction Monitoring API 9 7 8 7 6 7 5 8 74%

NIR Process T - Ylide formation API 8 5 8 5 3 8 10 10 73%

NIR Steroide B - Reaction Monitoring API 8 5 10 2 8 8 8 10 73%

UV-VIS Rinsate Cleaning Optimization API 9 5 9 3 8 9 10 8 72%

Turbidity Dissolution Endpoint DP-INJ 5 8 9 1 8 8 8 10 69%

OLGC SRD Distillation Monitoring API 6 3 10 6 3 2 5 10 66%

Vial Headspace Analysis for Oxygen DP-INJ 8 9 8 1 3 2 5 9 61%

OLMS Ceplasporin Dryer Monitoring API 3 4 8 10 5 3 5 5 60%

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Technology Development Process

PAT Project Ideas

Justificationreview andprojectprioritization

Lab proof ofconcept

Project specific teamorganized

Plant proof ofconcept

Decision toproceed

Adapted from an illustration by Seamus O’Neill (PASG, Ireland)

ProductionQuality OperationsEHSTechnology GroupsAutomationEngineeringPAT Champion

PAT ChampionPASGTech GroupsVendor

PAT ChampionProductionQuality OpsEHSTech GroupsAutomationEngineering

Project TeamPASGVendor

Project TeamSite ManagementPASG

SIMP

Site Imple-mentation Plan

Development

CPA

(if needed)

Plant POC Report

Tech Report on Lab POC Studies

PAT Project Charter

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PAT ImplementationTeam

PATProject

PATChampion

RFTChampion

ManufacturingOperations

R&D(co-dev)

QualityOperations

Engineering

Regulatory

Environmental,Health and Safety

ValidationServices

Automation

InformationTechnology

Management

Maintenance

Tech Services(KPT or PPT)

PASG

Implementation of a PAT requires input from a multi-disciplinary team.

- 24 -

GAMP Model for Instrument Qualification

User Requirements

Functional Specifications

Design Specifications

Installation

Installation Qualification

Operational Qualification

Performance Qualification

Good Automated Manufacturing PracticeGood Automated Manufacturing Practice

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More Questions

Is the information used for material release?

Do components come into direct contact with product?

Is there a GMP Impact?

Is there a Regulatory Impact?

Does the system affect product quality?

What if the system fails?

How should the data be archived?

Etcetera (ca. 14 questions for a system level impact assessment)

What are you going to do with the data?

Really asking:

Is the PAT for Process Knowledge or Process Control ?

Answer: Quality Impact Assessment document

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URS

User RequirementsSpecifications

QIA

QualityImpactAssessment

Ready forRoutine

Operation?

Implementation Process

DefineRequirements

PAT TeamPASG

VendorProject TeamPASGValidation Services

ProductionQualityPAT Champion

Cost review, justification, vendor selection,and approval

FAT, SAT, installation,qualification

Applicationverification

DefinitiveCPA

Capital ProjectApproval

FDS

FunctionalDesignSpecifications

IQ/OQ

Installation and Operation Qualification

PQ

Performance Qualification

Lifecycle Docs• Analytical Methods• Operation SOPs• Maintenance SOPs• Training Docs• Change Control• Periodic Review•Business Continuity Plan

Cross SiteLearning

Project TeamPASGVendor

Adapted from an illustration by Seamus O’Neill (PASG, Ireland)

RoutineOperation

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Example #1 – CU in a Sterile Suspension

Application: Drug ProductSterile Aqueous Suspension

Quality Impact: No Impact, Process Knowledge(product was not for sale)

Objective: Improved Content Uniformityduring later stages of filling

operation.

Project: RFT and Continuous Improvement

Black Belt project to providesuggested process changes forimproved content uniformity.

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Drug Product – Sterile Injectable

Parenteral Suspension

Solid

• Drug (20 - 150 mg/mL)

Vehicle

• Water (> 95%)

• Surfactants

• Preservative

2 mL vial with 1.2 mL fill

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Sterile Suspension Filling Operation

On-line Turbidity of Bulk Suspension Recycle Loop

Off-line or At-LineNIR Analysisof Filled Vials

- 30 -

Potency vs. Amount Filled

Filling operation is controlled within specifications, but thereis opportunity for improvement near the end of the batch.

Lot A

140

145

150

155

160

165

0 20 40 60 80 100

Approximate Percent Filled

Pot

ency

(m

g/m

L)

Off-line NIR HPLC

RSDNIR = 0.44%

RSDHPLC = 0.83%

RSDNIR = 1.91%

RSDHPLC = 2.57%

Lot B

140

145

150

155

160

165

170

0 20 40 60 80 100

Approximate Percent Filled

Pot

ency

(m

g/m

L)

Off-line NIR HPLC

RSDNIR = 0.55%

RSDHPLC = 0.49%

RSDNIR = 3.04%

RSDHPLC = 4.47%

- 31 -

At-Line NIR for Suspension Vial Analysis

Foss NIRSystems Model 6500

• Dispersive NIR spectrometer

• fiber-optic probe

Spinner - Sample Module

• fiber-optic probe

• in-house built accessory

Vision® software

Analysis time ~ 1 vial/min

Non-destructive, Non-invasive

- 32 -

Sample Spinner Schematic

45 °

sample

fiber optic probe

needle bearing

sleeve holder

mountingbracket

rotating gear( = 125 rpm)

- 33 -

Effect of Spin-rateon Apparent Concentration

130

150

170

190

210

230

250

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

Time (min)

App

aren

t Con

cent

rati

on (

mg/

mL

) 0 rpm

25 rpm

50 rpm

125 rpm

- 34 -

Raw Near-IR Spectra

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1100 1300 1500 1700 1900 2100

Wavelength (nm)

Abs

orba

nce

log

(1/R

)

187

168

150

131

114

100

125

150

175

200

Sample

Pot

ency

(m

g/m

L)

- 35 -

1st Derivative Spectra

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

1100 1300 1500 1700 1900 2100

Wavelength (nm)

1st D

eriv

ativ

e

0.00

0.04

0.08

0.12

1250 1300 1350 1400 1450 1500

-0.010

-0.005

0.000

0.005

0.010

0.015

1600 1650 1700 1750 1800 1850

- 36 -

Near-IR Calibration

100

110

120

130

140

150

160

170

180

190

200

100 110 120 130 140 150 160 170 180 190 200

Lab Potency (mg/mL)

NIR

Pot

ency

(m

g/m

L)

Training Set (SEC = 1.28 mg/mL, R = 0.99)Test Set (SEP = 1.40 mg/mL, R = 0.99)

Partial Least Squares Model2 factors, 1st derivative, 1650-1800 nm

- 37 -

Optek Turbidity Sensor

1. Sensor Body2. Windows3. NIR Filter4. Photo Diode5. Optics Module6. Tungsten Lamp

- 38 -

Calibration of On-line Turbidity Sensor

Incrementally dilute a concentrated suspension with known amounts of vehicle.

Correlate calculated suspension potency with turbidity sensor response.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 10 20 30 40 50Time (min)

A/D

Con

vert

er (

volts

)

117

122

127

132

137

142

147

152

157

162

Pot

ency

(m

g/m

L)

158.3 mg/mL

153.7

148.5

140.9

135

140

145

150

155

160

165

1.5 2.0 2.5 3.0 3.5

Optek Signal (volts)

Cal

cula

ted

Pot

ency

(m

g/m

L)

Calcuated Potency = 116.6 + 12.95 (OpSig) R² = 0.995

- 39 -

DOE Study using On-line Turbidity RFT Black Belt Project to improve Content Uniformity by optimizing

filling parameters. 6 factor DOE study was conducted varying mixing time, mixing power,

recirculation flow-rate, etc.

Tommy Garner

- 40 -

DOE Results

Bottom mixer has minimal contribution to mixing.

- 41 -

DOE Results continued Mixer power is critical for consistent CU.

- 42 -

Improved Filling Process Proposed process change: leave mixer on longer.

Three lots demonstrated no dip and no tail at end of fill.

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Advantages offered by On-Line Turbidity

Improved temporal sampling resolution.

Cost savings, by reducing or eliminating the need to perform off-line analysis by NIR or HPLC.Note: HPLC analysis by routine labs is ca. $100/analysis.

Eliminated error of taking “grab” samples for off-line analysis. This was found to be significant, if the sampling line is not properly configured, due to settling.

Time savings - ability to perform several parts of the DOE during the same run, i.e., ability to see when system has become perturbed or equilibrated.

- 44 -

Purge Data

80

100

120

140

160

180

200

0 100 200 300 400 500 600 700 800

Vial

Pot

ency

(m

g/m

L)

NIR

HPLC

After startup of filling line following settling of suspension.

- 45 -

Nyquist-Shannon Sampling Theorem

The sampling rate must be twice the maximum frequency component of the "signal" being measured, otherwise aliasing will occur.

fsampling 2 fsignal

Graphical representations seeAliasing. Bruno A. Olshausen, PCS 129 – Sensory Processes, Oct 10, 2000.http://redwood.ucdavis.edu/bruno/npb261/aliasing.pdf

- 46 -

Purge Data (Short Timescale)

80

100

120

140

160

180

200

0 20 40 60 80 100 120 140 160

Vial

Pot

ency

(m

g/m

L)

NIR

HPLC

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USP Compendial CU Testing

<905> “Uniformity of Dosage Units” in USP-NF

Stage 1 Acceptance CriteriaAssay 10 samples, i.e., n = 10Pass if RSD ≤ 6.0% and no value is outside 85% to 115% claim. Fail if one or more value is outside 75% to 125% claim.

Stage 2 Acceptance CriteriaAssay 20 more samples, i.e., n = 30Pass if RSD ≤ 7.8%, no more than one value is outside 85% to 115% claim, and no value is outside 75% to 125% claim.

Statistics are based on a small sample population;i.e., analytical testing with low statistical power.

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CU Testing Criteria for Large N

USP <905> is unsuitable for data sets comprised of large sample populations.

Proposed Acceptance Criteria outlined in article:

Sandell D., Vukovinsky K., Diener M., Hofer J., Pazdan J., and Timmermans J. Development of a Content Uniformity Test Suitable for Large Sample Size. Drug Information Journal, Vol 40, pp. 337-344, 2006.

- 49 -

Objective

Provide a non-qualitative means of assessing completion of API dissolution during compounding prior to aseptic filtration.

Quality Impact Assessment

Indirect Impact.Current IPC is by monitoring pH.

Key PlayersJustine McKenzie Project ManagementBob Witteman Greenbelt, Manufacturing EngineerTim Wang Kalamazoo Injectable ManufacturingBob Leasure Site PAT Support

Example #2 – DP Dissolution Monitoring

- 50 -

Solu-Cortef Dissolution Monitoring

O

OH

O

O

OOH

O

O

OH

O

O

O

O

O- Na+

O

OH

OH

O

Na+O

O

O-

-O

NaOH

aqueous

+Na

NaOH

aqueous

Excess Base

Solu-Cortef is a sterile lyophilized parenteral product.The hydrocortisone API is converted to the hemisuccinate sodium salt by addition of base, with care not to exceed the specification of pH 7.8.

RDWitteman conducted a RFT Greenbelt study,which concluded that slow response of the on-line pH probe can lead to OOS final pH.

On-line turbidity provides a more sensitive IPC over pH.

- 51 -

Solu-Cortef Dissolution Monitoring

- 52 -

Optek Forward Scatter Turbidity Probe

Optek Model AS16-NSingle Channel Photometer

• Forward scatter Turbidity Probe

• Operates in NIR from 730 to 970 nm

• OPL from 1 to 40 mm

• Aseptic Ingold or Triclover fittings

• Analog controller, 4-20 mA I/O (no computer)

• ca. $10K

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Implementation Plans

Optek Turbidity Probes have been installed in two CIP compounding tanks in Kalamazoo’s new aseptic production facility.

C&Q of the analyzers is underway as part of the validation of the new production facilities.

Current plans are for the equipment to be used for indirect impact process monitoring.

Use of the equipment for direct impact process control will be evaluated after additional process knowledge is gained and with consideration of benefits from RFT and Lean manufacturing.

- 54 -

Example #3 – API Solvent Recovery

Application: Cost Savings by Improving Yield forSolvent Recovery in API Operations

Quality Impact: Direct Impact (as deemed by QO)

Issues: Relatively slow determination of cutfor collecting product fraction.Based on In-Plant Lab GC analysis.

Project: Install On-line Gas Chromatographicanalysis with associated automation.

- 55 -

OLGC Installation One of seven solvent recovery

columns at the site.

Column #5 is used to recover seven different solvents.

• DMF

• Methylene Chloride

• Ethyl Acetate

• THF

• DMAP (THF containing alcohols)

• Toluene

• Acetone

Photo shows• Column

• Still Pot

• In-Plant Lab

- 56 -

Existing At-line GC Assay Performed by manufacturing operators in the

“In-Plant Lab” (IPL)

Analysis is time consuming due to manual steps:

• Collect sample

• Transport to IPL

• Sample preparation and injection

• Assay runtime,as long as 45 minutes depending on solvent

Prompt for manual analysis is based on column temperatures and “wait” times indicated in Master Record

- 57 -

Siemens Maxum II On-line GC

Dual Oven, Isothermal GC

Sampling ValvesCalibrationStandard

- 58 -

On-line GC Schematic

Column 1 Forward(ITC)

Column 2 Forward(main) Column 1 Reverse

(BF main)

S S S R

Column 1

Column 2

12

10

9

8

3

4

5

76

Carrier Infrom EPC

SampleOut

SampleIn

SSO

Detector Vents

Restrictors

- 59 -

Automation

In-PlantLab System

DCS (073HWL04)

WKS1 (B362)

GC Instrument (B73)

pe362hb

APP Node (B362S927)

B362OPC001

PDH OPC Client

Runs OPC Server/Client Interface to WKS1. Member of

AMER domain.

Controlled by Workstation software on WKS1

Runs Workstation and OPC Server/Client software interfaced to B362S927.

Member of AMER domain.

Network Fileshare Storage

Backup of data files and configuration from WKS1 on AMER domain resource.

Gets PAT data either from APP node or

directly from WKS1

PCN Switch in B362

- 60 -

Right Oven FID (High Boiling Organics)

- 61 -

Right Oven TCD (Water)

- 62 -

Left Oven FID (Low Boiling Organics)

- 63 -

Method Validation

● Specificity

● Precision – Repeatability

● Linearity

● Quantitation Limit

Method parameters assessed during the validation using ablack-box approach, but still addressing the following:

○ Accuracy

○ Detection Limit

○ Range

ComponentType

Constituent

Major acetone NLT 98.5

water none 0 to 5 0 to 30 ± 3% ± 0.9

methylene chloride none 0 to 5 0 to 20 ± 0.5% ± 0.1

ethyl acetate none 0 to 2 0 to 1 ± 1% ± 0.01

tetrahydrofuran none 0 to 2 0 to 1 ± 1% ± 0.01

toluene none 0 to 2 0 to 0.5 ± 1% ± 0.005

methanol NMT 0.5 0 to 2 0 to 1 ± 1% ± 0.01

ethanol none 0 to 2 0 to 0.5 ± 1% ± 0.005

Linearity

Range†

(vol %)

Working

Range‡

(vol %)

Minor

* NLT is not less than. NMT is not more than.† The "Linearity Range" may differ from the "Working Range" and spans the region where linearity criteria are applied.‡ Repeatability is based on Siemens specification for 8 hour repeatibility, expressed as a percentage of "Working Range".

Repeatability(vol %)

Limits*

(vol %)

SiemensRepeatability

Specification‡

- 64 -

Sample PreparationEach sample solution prepared according to the following instructions.1. Half-fill the indicated size volumetric flask with the major component solvent.2. Add spike volumes of each indicated neat minor component or stock solution to the flask by using Class A volumetric pipettes.

For volumes greater than 20 mL, a graduated cylinder may be used to measure the volume of the minor component being added.If a stock solution is used, then only one addition of the stock is needed to meet the spike levels for minor components.

3. q.s. with the major component solvent; i.e., acetone.

blank

Major Component: Sample or Solution ID Stock #1 Stock #2 blank 1 2 3 4 5 6 7

Limit: 98.5 vol% Volumetric Flask Size (mL) 50 50 500 500 500 500 500 500 500 500

4100 mL Spike Solution neat neat neat Stock #1 Stock #2 neat neat neat neat neat

Stock Spike Volume (mL) 10 10

Minor Component: Spike Volume (mL) 3 8 n/a n/a 8 3 20 50 150

Limit: 0.5 vol % Target Level (vol %) 6 16 0.120 0.320 1.6 0.6 4 10 30Linearity Range: 0 to 5 vol % % of Linearity Range 2.4% 6.4% 32.0% 12.0% 80.0% 200.0% 600.0%Working Range: 0 to 30 vol % % of Working Range 0.4% 1.1% 5.3% 2.0% 13.3% 33.3% 100.0%

Minor Component Percentage 15.0% 36.4% 22.2% 9.7% 30.3% 33.3% 75.0%

Minor Component: Spike Volume (mL) 1 4 2 7 20 100 50

Limit: 0.2 vol % Target Level (vol %) 2 8 0.040 0.160 0.4 1.4 4 20 10Linearity Range: 0 to 5 vol % % of Linearity Range 0.8% 3.2% 8.0% 28.0% 80.0% 400.0% 200.0%Working Range: 0 to 20 vol % % of Working Range 0.2% 0.8% 2.0% 7.0% 20.0% 100.0% 50.0%



Limit: 0.3 vol % Target Level (vol %) 2 6 0.040 0.120 2 0.4 1 0 0Linearity Range: 0 to 2 vol % % of Linearity Range 2.0% 6.0% 100.0% 20.0% 50.0% 0.0% 0.0%Working Range: 0 to 1 vol % % of Working Range 4.0% 12.0% 200.0% 40.0% 100.0% 0.0% 0.0%



Limit: 0.5 vol % Target Level (vol %) 16 6 0.320 0.120 0.4 1 2 0 0Linearity Range: 0 to 2 vol % % of Linearity Range 16.0% 6.0% 20.0% 50.0% 100.0% 0.0% 0.0%Working Range: 0 to 1 vol % % of Working Range 32.0% 12.0% 40.0% 100.0% 200.0% 0.0% 0.0%



Limit: 0.1 vol % Target Level (vol %) 2 4 0.040 0.080 0.2 0.6 1.2 0 0Linearity Range: 0 to 1 vol % % of Linearity Range 4.0% 8.0% 20.0% 60.0% 120.0% 0.0% 0.0%Working Range: 0 to 0.5 vol % % of Working Range 8.0% 16.0% 40.0% 120.0% 240.0% 0.0% 0.0%



Limit: 0.5 vol % Target Level (vol %) 8 2 0.160 0.040 1.4 2 0.4 0 0Linearity Range: 0 to 2 vol % % of Linearity Range 8.0% 2.0% 70.0% 100.0% 20.0% 0.0% 0.0%Working Range: 0 to 1 vol % % of Working Range 16.0% 4.0% 140.0% 200.0% 40.0% 0.0% 0.0%



Limit: 0.1 vol % Target Level (vol %) 4 2 0.080 0.040 1.2 0.2 0.6 0 0Linearity Range: 0 to 2 vol % % of Linearity Range 4.0% 2.0% 60.0% 10.0% 30.0% 0.0% 0.0%Working Range: 0 to 0.5 vol % % of Working Range 16.0% 8.0% 240.0% 40.0% 120.0% 0.0% 0.0%


NMT

NMT

acetone

water

NLT

NMT

preps from neat minor components

Volume required for preps:

preps from stockStock Solutions

ethanolNMT

methylene chlorideNMT

ethyl acetateNMT

tetrahydrofuranNMT

toluene

methanol

- 65 -

Sample Preparation

blan

k

1

2

3

4

5

6

7

water

meth

ylene

chlor

ide

ethyl

aceta

te

tetrah

ydro

fura

n

tolue

ne

meth

anol

ethan

ol

01

23

45

Vol

ume

%

Sample

Minor Component

- 66 -

Analyte Ratios – Assessment of Specificity

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7

Sample #

Rel

ativ

e P

erce

nt

of M

inor

Com

pon

ent

ethanol

methanol

toluene

tetrahydrofuran

ethyl acetate

methylene chloride

water

- 67 -

Regression AnalysisComponent: methanol

Limit: 0.5Repeatability Specification: 0.01

Linearity Range: 0 to 2

Sample Theoretical Median Average Std Dev Recoveryblank 0 0.080 0.092 0.090

1 0.16 0.176 0.176 0.002 110% 0.002 Pass2 0.04 0.060 0.060 0.001 149% 0.001 Pass3 1.4 1.389 1.384 0.009 99% 0.009 Pass4 2 1.948 1.948 0.014 97% 0.014 Pass5 0.4 0.374 0.374 0.011 94% 0.011 Pass6 0 0.000 0.005 0.008 0.008 Pass7 0 0.000 0.000 0.000 0.000 Pass

Average: 110% 0.006Data in blue boxes used for assessing validation criteria.

MeasuredRepeatability

Criterion 1

Result: Pass

Criterion 2

Result: Pass

Criterion 3

Result: Pass

Criterion 4 The QL must be less than 50% the limit for the respective minor component.Result: Pass

For each minor component of interest, the square of the regression coefficient from the plot of measured volume % vs. theoretical volume % must be 0.99 or better.

The slope of the linearity plot of measured volume % vs. theoretical volume % for each minor component of interest must be 1 ± 0.2.

For each minor component of interest, the repeatability for each solution (for which six consecutive repeat injections were made) must be equal to or less than the respective repeatability specification provided in Table 1.

Linear Regression 0.973113975 0.007696776intercept: 0.00770 0.007619648 0.007140433

slope: 0.97311 0.999693536 0.014973114residual sum of squares: 0.00112 16310.13646 5

correlation coefficient: 0.99910 3.656637021 0.001120971square of correlation coefficient: 0.99819

std error for the y-estimate of the regression line: 0.01497 "X" Range "Y" Fit Valuelimit of detection: 0.05078 0 0.008

limit of quantitation: 0.15387 2 1.954

Linest Statistics

0.0

0.5

1.0

1.5

2.0

2.5

0.0 0.5 1.0 1.5 2.0 2.5

Theoretical (vol %)

Mea

sure

d (

vol %

)

Median

Average

Fit

0.0000.2190.1760.0860.0730.0000.1770.1780.1770.1740.1740.1750.0590.0600.0590.0600.0600.0591.3891.3891.3891.3801.3891.3661.9501.9461.9451.9501.9691.9260.3940.3770.3720.3670.3610.3750.0190.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.000

Sample ID volume %

blank

5

6

7

1

2

3

4

- 68 -

Issue: Frequent Failure of Injection Rotor

The variety of solvent polarity and incompatibility of MOC caused “grooving” of the injector rotor

Fix involved specifying a different PTFE coated rotor.

- 69 -

Projected Savings

Solvent Price per GallonApproximate

% of ROI

Toluene $ 2.54 59%

Ethyl acetate $ 3.44 20%

Tetrahydrofuran $ 8.59 8%

Dimethylformamide $ 3.90 7%

Methylene Chloride $ 3.67 3%

THF(alcohol containing stream)

$ 8.59 2%

Acetone $ 3.07 1%

The Return on Investment of the implementation was estimated to be one year,based on solvent cost and production volumes at the time of CPA submittal.

- 70 -

Lessons Learned Stick to the Plan

Do not deviate from define validation approach established at the beginning of the project;otherwise the project may be delayed.

Train Appropriate Personnel AppropriatelyCross-train key users for daily care and troubleshooting of the instrument.User training should be budgeted as part of the project scope.

Keep it SimpleDepending on the technology, analysis of multiple streams/products may present challenges and additional overhead.

- 71 -

Acknowledgements Drug Product Suspension CU

• Tom Garner - RFT Black Belt and Project Manager

Drug Product Dissolution Monitoring• Robert Wittemann - RFT Green Belt and Production Engineer

• Tim Wang - PPT Production Engineering

On-line GC for Solvent Recovery• Brad Diehl - PASG Implementation Support

• Frank Sistare - PGM Groton

• Joe Geiger - Production Engineering Solvent Recovery

• Jeff Terpstra - Project Management

• Pete Miilu, Marc Surprenant - IT Automation

• Donald Zeilenga - KPT and Site PAT Support

• Scott Wagenaar, Kurt Holton - Production Operations

• Andrew Meister - Instrumentation Maintenance

- 72 -

- 1 - a roadmap for pat implementation in pharmaceutical manufacturing robert m. leasure principal...

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