Quality by Design Quality by Design –– Facilitating Facilitating Real Time Release (RTR) Real Time Release (RTR) Practical Challenges and Opportunities during RTR Practical Challenges and Opportunities during RTR ImplementationImplementation

Carl E. Longfellow Ph.D.,Senior Director, New Product and Process Development,

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Discussion Topics

IntroductionHistory leading to QbD initiativeWhat is RTR?

RTR – Essential ElementsPeopleScience

- Statistical Tools- Control Strategy

Quality Systems and Processes

Challenges and Opportunities

Benefits

History

What lead to QbD initiativeNot new to other industriesLack of continuous improvement is an outcome of regulatory oversight

- No business driver to improve processes- High cost to file regulatory changes globally- Relatively short timelines and limited experience to develop robust processes

Short comings recognized by regulatory authorities

ICH guidelines establishedQ8-Pharmaceutical DevelopmentQ9-Quality Risk ManagementQ10-Pharmaceutical Quality Systems

FDA CMC Program

Major Takeaways

RTR is not the goal of Quality by Design (QbD). It is a possible outcome of QbD development

RTR is possible when there is a high level of product and process understanding, a robust control strategy (including PAT), and science and risk-based quality systems aligned with Q10

QbD and RTR raise the bar on quality. Returning to routine sampling and testing for product release may not be possible.

Real Time Release (RTR)— Regulatory Definition

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2001 EMEA NOTE for GUIDANCE ON PARAMETRIC RELEASE (CPMP/QWP/3015/99)System of Release that gives assurance that the product is of

intended quality based on the information collected during the manufacturing process and on the compliance with specific GMP requirements related to parametric release

- It is therefore based on the successful validation of the manufacturing process and review of the documentation on process monitoring carried out during manufacturing to provide the desired assurance of the quality of the product

FDA PAT GUIDANCE, September 2004 - RTR is the ability to evaluate and ensure the acceptable quality of in-process and/or final product based on process data

REAL TIME RELEASE

Science

SystemsPeople

Real Time Release – Essential Elements

ICH Q8 Pharmaceutical Development

ICH Q9 Quality Risk Management

ICH Q10 Quality Systems

Real Time Release Elements - PeopleMultidisciplinary and cross-functional teams are a key to making QbD a success

TechnologyTechnology

Regulatory Regulatory AffairsAffairs

Quality Quality OperationsOperations

StatisticsStatistics

Formulation Formulation DevelopmentDevelopment

ChemometricsChemometrics

Analytical Analytical DevelopmentDevelopment

OperationsOperations

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Real Time Release Elements - Science

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Real Time Release

Science

Quality Risk Management

Knowledge Management

Statistical Tools

Sampling plan justification

Estimation of acceptable coverage to demonstrate product quality- raise the bar over USPOperational Characteristics (OC) CurveSimulations

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Statistical Tools- Development of Sampling Plans

How often do we sample and where do we sample?- Statistical rationale for sampling (in combination with risk

assessments/prior knowledge)-

Sampling of tablets during the compression unit operation for a low dose tablet (as it may be more prone to segregation) may be different than that for a high dose tablet

- Rationale for placement of PAT device in manufacturing equipment –

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Why is the NIR for blender placed in the bottom of the blender versus the top (or side) and is the sample representative of the batch?

Statistical Tools - Operating Characteristics Curves

Operating Characteristic (OC) Curves are often used to illustrate the performance of a lot acceptance test. These curves provide a way to compare the performance of different tests.

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A calculation relevant to the Acceptance Criterion

High probability means lots will typically be found acceptable by the test being evaluated

Steepness of the curve indicates the discrimination of the test

Thomas Pyzdek, Quality Engineering Handbook, Second Edition, Marcel Dekker Inc.

Operating Characteristic Curve (Median of Results)

0%5%10%15%20%25%30%35%40%45%50%55%60%65%70%75%80%85%90%95%100%

95.095.596.096.597.097.598.098.599.099.5100.0

Coverage

Pr. o

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USP Wyeth

Statistical Tools - Operating Characteristics Curve for UDU Test

“Development of a content uniformity test suitable for large sample sizes” Sandell et. al., Drug Information Journal, Vol. 40, pp337-344, 2006.

Coverage is the proportion of dosage units within 85-115% LC and is considered a relevant measure of the uniformity of the batch. At 98% coverage, USP would pass the batch 90% of the time, but there is zero chance of the second plan passing the batch

Statistical Tools Simulations – Monte Carlo Simulations

Monte Carlo Simulations* - A technique that converts uncertainties in input variables of a model into probability distributions. By combining the distributions and randomly selecting values from them, it recalculates the simulated model many times and brings out the probability of the output.

- MCS allows several inputs to be used at the same time to create the probability distribution of one or more outputs.

- Different types of probability distributions can be assigned to the inputs of the model. When the distribution is unknown, the one that represents the best fit could be chosen.

- The use of random numbers characterizes MCS as a stochastic method. The random numbers have to be independent; no correlation should exist between them.

- MCS is a sampling method that generates the output as a range instead of a fixed value and shows how likely the output value is to occur in the range.

*Sanford Bolton, Charles Bon– Pharmaceutical Statistics- Practical and Clinical Applications, Fourth Edition, Marcel Dekker,

Monte Carlo Simulations – Contour Plots for Potential Scenarios

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NIRmean

Indicates potential scenarios where a batch would have a high probability of passing planNote: Plus signs represents cases with probability between 6-8%, empty squares for probability between 8- 10%, and solid squares for probability above 10%.

Simulations – Help provides an assessment of risk for chosen coverage

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Real Time Release Elements - Science

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Real Time Release

Science

Quality Risk Management

Knowledge Management

Control Strategy

Control Strategy: A planned set of controls, derived from current product and process understanding, that assures process performance and product quality. The controls can include parameters and attributes related to drug substance and drug product materials and components, facility and equipment operating conditions, in-process controls, finished product specifications, and the associated methods and frequency of monitoring and control. (ICH Q10)

Ensures input quality attributes and process parameters are maintained within the approved design space(s)---thus product should meet specifications without finished product testing.

PAT is one of the key tools that enable RTRIts application should be based on a risk evaluation

What is RTR? Control Strategy example for a high dose, roller compaction process….

Particle Size Analyzer – Control of RC output within pre-established range helps control hardness

NIR – Uniformity of Blend

NIR for tablets online testing, At Line automatic tablet weight checking –Uniformity/weight control

Fette Control Loops – Weight / uniformity control

NIR – Uniformity of Blend

Robust control strategy = Increased assurance of quality = RTR

Blending Content for API and FE

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Particle Size Output

Compression – FT-NIR Interim ReportNIR Report for This Pull

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Date(mm/dd/yy): 01/11/07

Time: 9:51:40

Operator: Administrator

Batch Number: XXXXX

Sample: XXX mg tablets - Pull No: x

Index FileName Id %API %FE %Target

1 B93052-01.0 xxx mg 53.48 30.69 98.7

2 B93052-01.1 xxx mg 53.79 30.83 99.2

3 B93052-01.2 xxx mg 53.77 30.87 99.2

4 B93052-01.3 xxx mg 52.75 31.63 97.3

5 B93052-01.4 xxx mg 53.58 31.24 98.9

6 B93052-01.5 xxx mg 53.72 31.01 99.1

7 B93052-01.6 xxx mg 53.91 30.73 99.5

8 B93052-01.7 xxx mg 54.11 30.99 99.8

9 B93052-01.8 xxx mg 53.72 30.86 99.1

10 B93052-01.9 xxx mg 54.86 30.25 101.2

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Summary for API Conc (%):

Average: 99.2%

Minimum: 97.3%

Maximam: 101.2%

Std. Dev: 1.0

Note: Summary based on the actual (not rounded) individual results.

Summary by Individual Tablets

LSL USLTarget

90 92 94 96 98 100102104106 109

100.0%99.5%97.5%90.0%75.0%50.0%25.0%10.0%2.5%0.5%0.0%

maximum

quartilemedianquartile

minimum

108.61105.15103.81102.53101.47100.3699.3698.4897.5896.7294.77

QuantilesMeanStd DevStd Err Meanupper 95% Meanlower 95% MeanN

100.454081.59546480.0098345100.47336100.4348

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Moments

Rel.DVS%

Distributions

Lower Spec LimitUpper Spec LimitSpec Target

Specification90

110100

Value Below LSLAbove USLTotal Outside

Portion0.00000.00000.0000

% Actual

LSL USLTarget

-3s +3sMean

90 100 110

CPCPKCPMCPLCPU

Capability2.0891.9942.0092.1841.994

Index2.0711.9771.9932.1651.977

Lower CI2.1072.0122.0262.2032.012

Upper CI

Below LSLAbove USLTotal Outside

Portion0.00000.00000.0000

Percent0.00000.00110.0011

PPM8.0527.4837.479

Sigma Quality

Z BenchZ LSLZ USL

Benchmark Z5.9796.5525.983

Index

Overall, Sigma = 1.59546

Capability Analysis

Rel.DVS%

Distributions

Mean: 100.5%

PPK: 1.994

Summary by Individual Tablets (Run chart)

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Y Rel.DVS% Rel.HPMC%

Overlay Plot

FE Active

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ICH Q10 Alignment Science and Risk based Approach to QualityDisaster recovery plansChemometric Model MaintenanceHandling of outliersBatch release process in the RTR environmentQuality risk management (enabler)Tracking and trending of data

Real Time Release Elements – Quality Systems and Processes

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Quality Systems and Processes - Development of Disaster Recovery Systems

Things to considerWhat do we do if a PAT measurement system stops functioning?What do we do when all the PAT measurement systems stop

functioning?What do we do if the chemometric model is no longer

appropriate? - What are the alternative procedures and sampling plans for

sample/batch analysis and release?

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Decision Tree for Failure Modes– PAT Failure During the Manufacturing Process

Does PAT pass System

Suitability?

NO

Proceed with unit operation/manufactu

ring process

YES

YES

NO

Is PAT functional during the Process?

YES

Can the instrument be repaired in a suitable time frame?

Can the instrument be replaced with a spare instrument?

Generate Event Report Form, Fix/replace

instrument

NO

Are there alternative controls to ensure/control process variability?

Are there measurements downstreamwhich could be used to correlate data?

Do we need further sampling?

Generate Event Report Form, Capture Process/

Action Items

Revert to Testing using Regulatory Analytical Procedure

Generate Investigation/ERF to identify root cause

Capture Process/Action Items

YES

Stop Process*,Evaluate Instrument

*: Please note that it may not be practical to stop some unit operations in themanufacturing process during the middle of the run. For eg: Blending

Predefining reaction ensures proactive quality as compared to thinking of reaction after event - reactive quality

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Quality Systems and Processes Chemometric Models- Establishment and Maintenance

How do you transfer small scale models to large scale equipment?

- Need to assess variability due to equipment, personnel, environment, measurement systems, materials etc. and refine models as necessary

What are the procedures for chemometric model maintenance?

How often would a periodic check on the model performance be performed?

What are the criteria for the revision of models in the RTR environment and how does this differ from the R&D/monitoring environment?

Quality Systems and Processes- Handling of Outliers

Development of mechanisms/predefined systems to handle outliers in the measurement systems (proactive quality)

- Should use a holistic assessment of the process measurements (in- process + final product) to assess product/process performance and impact to quality

- Reaction to outlier’s must be risk based -

# of occurrences dictate reaction to outliers(setting

of zero tolerance criteria critical)

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The reaction to an outlier after significant process/product history should be different than an outlier observed when the amount of historical information is minimal

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Consider potential impact of an outlier to patient safety and efficacy

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Quality Systems and Processes- Batch Disposition and RTR

Points to consider for batch disposition in a RTR environment…Use of electronic batch records and identification of exceptions

(flagging) that foster easier batch release Development of SPCs and a process/product monitoring system

provide a real time assessment of process/product performance

Quality Systems and Processes- Batch Disposition Points to Consider, Continued…

What is the relationship between the PAT attribute measured and the acceptance criteria for the drug product?Dissolution of an extended release product – if attribute measured

as a surrogate for dissolution is polymer concentration, need to establish correlation between polymer concentration and dissolution (models)Need to define strategy for defining dissolution (or other quality

attribute) in a Certificate of Analysis (CoA). Options include:- Generate a dissolution result based on model developed to

demonstrate correlation to polymer and use in CoA. Indicate that the dissolution is a calculated value and not a measured value

- Defining polymer concentration in CoA and indicate that this is a surrogate for dissolution

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Quality Systems and Processes- Quality Risk Management – What it is…

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NO RISK NO REWARD

KNOW RISK KNOW REWARD

Quality Systems and Processes- Quality Risk Management – Points to Consider

Procedures for the implementation of QRM uniformly across the entire organizationUse of the same language (terminology), processEstablish criteria for re-evaluation of risks and mitigation plans –

time, event or knowledge based

Training program Various levels – awareness, participant, facilitator, team leader) to

ensure effective utility of the toolChoice of the right QRA/QRM approach (Risk filter, FMEA,

HACCP)Utilize tool in a proactive manner, not in a reactive fashion

Quality Systems and Processes- Tracking and Trending

Procedures (and processes) for tracking and trending of dataIdentify what needs to be tracked and trended (and Why?)

- Process inputs (including raw material characteristics, parameters), process outputs, process capability measurements (cycle times, yields, process capabilities)

Identify tools/process for tracking and trending- Establishing procedures/systems within quality systems

Establish rules for tracking and trending- When are we going to react and how?

Establish responsibilities for processTrainingContinuous improvement

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Challenges and Opportunities Associated with RTR

Regulatory challenges (global harmonization)

Risk Management – better understanding is necessary

ResourcesInitial capital commitment is needed for PATPersonnel with diverse background necessary for successful PAT

implementationCulture/mindset challenges (proactive versus reactive quality)Impact to QP/Q release person (understand control strategy, RM

approach, quality systems, etc for RTR environment)

Quality Systems DevelopmentWill need quality systems to be based on risk management

principles (e.g. Need systems in place for PAT equipment failure)Robust change control systems needed

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Benefits from RTR, QbD, PAT

RTR/QbD can lead to lower manufacturing costs (faster cycle times, fewer rejects, reduced QC resources, and greater yields)

Demonstration of Process/Product Knowledge can lead to RTR and other examples of regulatory flexibility (e.g. fewer post-approval supplements)

Use of PAT/QbD can facilitate Technology Development and Transfer (TD&T) process Understanding of process/product makes TD&T easierContinuous Quality Verification (ASTM Standard Guide E2537-

08)--not today’s 3 batch validation

Even higher level of product quality for our patients

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Acknowledgements

Steve SimmonsChunsheng Cai

Carlos Conde-ReyesPlinio Delos-Santos

Parimal DesaiJoseph DevitoLori Henning

Nirdosh JagotaShailesh Singh

Merlin UtterT.G. Venkateshwaran

Dominic Ventura