dissolution routinely tested to provide in vitro drug release information

Statistical Evaluation of Dissolution for Specification Setting and Stability Studies

Fasheng LiAssociate Director, Pharmaceutical Statistics

Worldwide R&DPfizer, Inc

37th Annual MBSW Muncie, IN

May 20, 2014

Dissolution routinely tested to provide in vitro drug release information

Drug development: prediction of in vivo drug release profiles Quality control: assessment of batch-to-batch consistency

Decision making during dissolution method and drug development

Data based specification setting for USP <711> dissolution test Dissolution monitoring on stability

Statistical assessment integral to decision making process.

Motivation

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Outline

Setting Extended Release Dissolution Specifications

Number of time points needed Case 1: Two-point spec Case 2: Three-point spec

Evaluation of possible specifications

Dissolution on Stability

No significant linear trend observed Non-linear trend observed

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Dissolution Specification Setting

How many time points are necessary for setting dissolution specifications?

Based on “Guidance for Industry: Extended Release Oral Dosage Forms: Development, Evaluation, and Application of In Vitro/In Vivo Correlations”, at least three points (early, middle, late) on the dissolution profile should be used to have specifications

Are fewer than three time points sufficient?Are three time points enough?

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Dissolution Spec Setting – Case 1

Mean disso profiles of three typical batches of a sustained release drug product

Proposed to have specs at two time points (30 and 180 minutes)

Team discussed to add a spec at either 15 or 60 minutes

Specs at 30 and 180 minutes

Add either 15 or 60 minutes?

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Dissolution Spec Setting – Case 1 An empirical

first-order two-parameter non-linear regression model fit to the release profiles

Goodness-of-fit of the model evaluated by a coefficient of determination R2-type measure

Model appropriateness evaluated by the lack-of-fit test

R2 = SSTotal

SSE1

,

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Release = A(1-e-bt) is a two-parameter Weibull model

Dissolution Spec Setting – Case 1 Dissolution profiles

defined well by a two-parameter release model

Mathematically, any two points on the profile would be able to sufficiently define the release profile

No need to add a third time point for specification

Team agreed to set disso specifications without a third point

,

Two-point spec

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Dissolution Spec Setting – Case 2

Mean disso profiles of three typical batches of a extended release drug product

Originally specs at 5 time points proposed; should 1 more be added to improve control?

Question: How many time points are needed for setting dissolution specifications?

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Dissolution Spec Setting – Case 2 An empirical

three-parameter non-linear regression model (Weibull ) fit to the release profiles

Goodness-of-fit of the model evaluated by a coefficient of determination R2-type measure

Model appropriateness evaluated by the lack-of-fit test

R2 = SSTotal

SSE1

,

The three-parameter Weibull model is sufficient and adequate to define dissolution profiles in this case

Recommend three-time points for dissolution specifications

Three-point spec

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Brief Summary ,

Three-point specifications are apparently more advantageous than six-point specifications:

Cost Savings

Save 50% reducing from 6 to 3 time points

Quicker Analytical Results

Conformity Risk Reduction: Assuming the probability of passing USP <711> dissolution test at each time point is the same (e.g. 98%), the overall probability to pass:

0.983 = 94% with three time points

vs. 0.986 = 89% with six time points

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Evaluation of Dissolution Specifications,

After Determining Number of Time Points

Evaluate proposed dissolution specifications against USP <711> at each time point

Recommend new dissolution specifications if necessary

Statistical Approach

Simulations performed on individual dissolution data at each of the specification time points to check the probabilities of passing different stages (L1, L2, and L3) of USP <711> dissolution test

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USP <711> Dissolution Test

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Acceptance Criteria for Extended Release Drug Products

Controlled release product specs:

@1 hour: <= 30% @4 hours: 40-60% @24 hours: >= 80%

Re-evaluate specs due to method change

Data: 46 unique dissolution conditions Each have 6 to 96

individual disso profiles A total of 1578 disso

profiles collected

Evaluation of Dissolution Specifications

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50000 simulations performed on 46 dissolution data sets to check probabilities of passing USP <711> stages (L1, L2, and L3)

Current three-point specifications

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Specifications Stage

% of Disso TestsAcceptance Probability

by Stage Lx

Need Stage Lx Pass 100% by Stage Lx Mean StDevQ1: <= 25% Q4: 35-55% Q24: >= 80%

L1 100.0 13.0 95.3 9.0L2 87.0 52.2 98.5 2.9L3 47.8 80.4 99.5 1.4

Q1: <= 30% Q4: 35-55% Q24: >= 80%

L1 100.0 15.2 96.2 7.6L2 84.8 58.7 99.0 2.1L3 41.3 87.0 99.8 0.7

Q1: <= 30% Q4: 40-60% Q24: >= 85%

L1 100.0 4.3 59.4 38.2L2 95.7 17.4 87.1 19.1L3 82.6 47.8 91.0 19.9

Proposed Specs

ComparableSpecs

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Controlled release product - recommended specifications for new dissolution method

@1 hour: <= 30% @4 hours: 35-55% @24 hours: >= 80%


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Revised three-point specifications

Revised three-point specifications

Individual Dissolution Profiles

Mean Dissolution Profiles

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Brief Summary – Disso Spec Setting,

The number of time points on dissolution profiles used for specification setting

Can be justified by fitting a non-linear release model Based on the number of parameters of the non-linear release

model

Specifications at each time points

Can be evaluated by performing simulations on dissolution data against USP <711> criteria

Calculate the probability to pass USP criteria

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Dissolution on Stability

Dissolution usually monitored on stability as a numerical quality attributes with numeric specifications

e.g. %Release at 6 hours should be between 40-60%

Dissolution data may not have a significant linear trend along stability time

Linear trends not significantNon-linear trends observed

How to evaluate dissolution data on stability? Typical Q1E shelf life analysis not appropriate.

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Dissolution on Stability – No Linear Trend

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No Statistically significant

Linear Trend

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Linear Trend

Clear linear trend for the chemical impurity data ICH Q1E Analysis

Appropriate

ICH Q1E Analysis is not meaningful

No overall statistically significant trend in

dissolution at 10 hours

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Shelf-life predicted based on the major chemical impurities: Apply linear regression analyses following the ICH Q1E guidance

The risk of failing dissolution on stability will be quantified

Make sure the risk of failing dissolution spec is low Utilize dissolution profiles tested at each of the stability

time points

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A three-parameter Weibull model:

%Release = A(1-exp(-b*tm))

fit to all mean or individual dissolution profiles at each of the stability time points for all registration stability batches

The risk of failing dissolution at a future stability test time since time is not relevant can be quantified by

1. Constructing prediction limits with confidence level p%

2. Checking the limits against the spec of (45, 65)

3. If the prediction limits are within the spec limits, the risk of failing a future average dissolution would be no more than 100-p%

Storage Condition Strength

Nonlinear Model Parameters and Fit Statistics

99 % Pred Limits for

Dissolution at 10hr

99 % Pred Limits Meet

Spec (45, 65)?

%Chance for a Future Disso Test

to FailA b m R2 P-value

25°C/60%RH

1 94.5 0.0176 1.711 0.9939 0.0000 49.6, 63.0 Yes 0.0452 94.0 0.0147 1.760 0.9952 0.0000 47.8, 59.7 Yes 0.0123 94.8 0.0159 1.739 0.9960 0.0000 49.5, 60.6 Yes 0.0034 95.7 0.0142 1.777 0.9964 0.0000 49.5, 60.1 Yes 0.0035 96.2 0.0140 1.783 0.9960 0.0000 49.5, 60.8 Yes 0.0036 94.4 0.0135 1.800 0.9955 0.0000 48.3, 60.1 Yes 0.003

7 93.6 0.0107 1.867 0.9945 0.0000 44.5, 57.4 Not the lower limit 0.865

30°C/75%RH

1 95.8 0.0180 1.714 0.9932 0.0000 50.9, 65.3 Not the upper limit 0.6692 94.4 0.0150 1.764 0.9952 0.0000 48.8, 60.9 Yes 0.0033 95.7 0.0165 1.734 0.9940 0.0000 49.7, 63.4 Yes 0.0744 97.5 0.0149 1.756 0.9951 0.0000 49.6, 62.1 Yes 0.0125 96.6 0.0137 1.796 0.9950 0.0000 49.2, 62.0 Yes 0.0076 96.1 0.0132 1.811 0.9952 0.0000 48.9, 61.3 Yes 0.003

7 95.1 0.0108 1.867 0.9955 0.0000 46.2, 57.9 Yes 0.112

)e-A(1 Release%m-bt

• Model fit mean dissolution profiles of stability times points very well (R2 > 0.99)

• The risk of failing dissolution test on stability at a future time is no more than 0.9%

Risk of Dissolution on Stability

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Risk of failing disso on stability is < 0.9%

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Risk of failing disso on stability is < 0.7%

Dissolution on Stability – Non-linear Trend

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Extended release product: with a clear non-linear trend for dissolution data at x hours


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Empirical model of:

%Release at x hours = A(1-e-b*(t+t0))

can be fit to dissolution at x hours from manufacturing age for all registration stability batches

Shelf life (in terms of manufacture age) can be predicted when the 95% confidence interval intersects with the spec limits

Shelf life (in terms of stability storage age) can be determined by subtracting the manufacturing age of the initial stability time point (stability time 0 month)


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Stability program started at 7.4 months of manufacturing age

Predicted shelf life is about 54.5 -7.4 = 47.1 months

Brief Summary – Dissolution on Stability,

Stability dissolution data often show no significant linear trends

No significant linear or non-linear trend

Dissolution profile data can be utilized to remediate the risk of meeting dissolution specifications• More information used versus evaluate at 1 time

point on the profile

Non-linear trend

Empirical non-linear model fit to stability data could help justify the prediction of shelf life

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Summary

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Dissolution for extended release drug products facing decision makings in areas such as

Setting Specifications Number of time points on the profile for spec Specification limits at the time points

Dissolution on Stability No significant linear trend Non-linear trend

• Statistics will be able to contribute greatly in the above areas to make regulatory appealing decisions

Statisticians need to work proactively with team scientists

Acknowledgment

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Kim Vukovinsky, Senior Director, Pharmaceutical Statistics, Worldwide R&D, Pfizer Inc.

dissolution routinely tested to provide in vitro drug release information

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