Sterile Packaging: An Examination of Statistics and Sampling”

Introduction

• Principles of Risk Management

• Basics of sampling

• Statistical considerations for balancing

costs and risks

• Issues such as sterilization configuration

and data analysis

• Introduction to analysis of variance for

assuring sterile product in the field.

2

Principles of Risk Management

• Two primary principles of quality risk management

are:

– The evaluation of the risk to quality should be based on

scientific knowledge and ultimately link to the protection of

the patient; and

– The level of effort, formality and documentation of the quality

risk management process should be commensurate with the

level of risk.

• Sample size is a function of risk

3

Ho : ‘sameness’

Ha : ‘difference’

Type I Error Reject Ho when Ho is true

a-risk

Type II Error

Fail to reject Ho when Ha is

true

b-risk

Correct Decision Fail to Reject Ho when

Ho is true

Correct Decision

Reject Ho when Ha is true

a = The risk of making a Type I Error. Typically, a = 0.05, or 5%

b = The risk of making a Type II Error. Typically, b = 0.10, or 10%

‘Confidence’ = 1 - a

‘Power’ = 1 - b

Decision Errors

Test

Decision

The

Truth

Ho Ha

Ho

Ha

4

Relationship of CTQ to Risk

CTQ Type Suggested a Suggested b

Safety

(Special Situation)

1% 0.1%

High 1% 1%

Medium 5% 5%

Low 5% 10%

5

Sample Size and Risk •Recommended sample size based on risk (Assuming all units meet requirements)

•Low Risk (RPN 1- 300)

• 95% Confidence / 90 % Reliability

• Sample Size = 28

•Medium Risk (RPN 301-600)

• 95% Confidence / 95 % Reliability

• Sample Size = 59

•High Risk (RPN 601 – 1000)

• 99% Confidence / 99% Reliability

• Sample Size = 458

•Safety (Special Situation)

• 99% Confidence / 99.9% Reliability

• Sample Size = 4602

𝑛 = ln 1 − 𝐶𝑜𝑛𝑓𝑖𝑑𝑒𝑛𝑐𝑒 /ln(𝑟𝑒𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑦)

6

Sample Size for Continuous Data

2

2

2

Z Z Sn

a b

• You can substitute the t-value for smaller sample sizes.

• Differs slightly from the method used by software such as JMP™.

7

Values of Alpha and Beta

Confidence Level b a

1-Sided Specification 2-Sided Specification

80% 0.842 0.842 1.282

90% 1.282 1.282 1.645

95% 1.645 1.645 1.960

98% 1.960 1.960 2.241

99% 2.326 2.326 2.576

100% 2.576 2.576 2.807

8

K-Value Sample Size

• Want to get a sample size for individual

values

– Determine the Confidence Level

– Determine the percent of population coverage

(Reliability)

– Use ISO 16269-6 (ISO standard for tolerance

intervals) to find the value of K

9

LSk

USk

*

*

X

X

Example

• Validating an new sterility cycle, how many

dosimeters should we test to ensure that

we have 99% confidence that 99% of the

dosimeters receive a dose that is within

0.75 kGy of the target dose of 16 kGy

given a 0.25 kGy standard deviation?

10 150

3

75.1625.0*16

**

n

k

k

LSkUSk X or X

Sterility Assurance

• How do you know that your medical device

is sterile?

– Packaging validation studies?

– Dosimeters during sterilization?

– 100% Inspection?

• Statistically rationale sampling is required! 11

ANOVA and Field Sterility

• ANalysis Of VAriance (ANOVA).

• Desire to understand how Critical Process

Parameters (CPP) impact sterility in the field.

• Utilizing Design of Experiments (DOE), we can

develop a robust design and process to ensure

a high level of confidence that product remains

sterile in the field.

General Approach

• Formulate a hypothesis of factors that could impact

sterility in the field.

• Determine what levels of each factor to evaluate

• Design experiment

• Run experiment

• Analyze results

– Might require stability testing or time study

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Example

• Three factors (Cycle, Seal Strength, Load)

• 8 runs

• Three packages per run

• 24 total observations

• Evaluate

– Any sterility failures at time 0

– Sterility failures over time

– Accelerated conditions

• Using logistic regression we can determine the odds of

failure in the field based on varying conditions.

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Example

15

Cycle Seal Load Failures

½ Low ½ 3

½ High ½ 1

Full Low ½ 1

Full High ½ 0

½ Low Full 0

½ High Full 1

Full Low Full 1

Full High Full 0

The ½ cycle is 4.7x more likely to fail in field versus Full cycle

The Low seal is 4.7x more likely to fail in field versus High seal

The ½ load is 4.7x more likely to fail in field versus Full load

Packaging Validation Studies

• Typically optimizing settings to ensure

sterility barrier.

• Testing might include:

– Leak test

– Peel force

16

Analysis of Leak Test

• Attribute

– Larger sample size

17

Analysis of Tear Test

• Variable

– Smaller sample

– Correlated to leak?

• 3 Factor Study

– Time (2-6 Seconds)

– Temperature (180 – 200 Degrees)

– Pressure (400-500 PSI)

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Responses

StdOrder RunOrder CenterPt Blocks Time Temp Pressure Seal Strength

2 1 1 1 6 180 400 2.1

7 2 1 1 2 200 500 3.1

5 3 1 1 2 180 500 3.5

8 4 1 1 6 200 500 2.9

1 5 1 1 2 180 400 1.8

4 6 1 1 6 200 400 1.9

3 7 1 1 2 200 400 1.5

6 8 1 1 6 180 500 3.6

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Analysis

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Source DF Seq SS Adj SS Adj MS F P Main Effects 3 4.57000 4.57000 1.52333 76.17 0.084 Time 1 0.04500 0.04500 0.04500 2.25 0.374 Temp 1 0.32000 0.32000 0.32000 16.00 0.156 Pressure 1 4.20500 4.20500 4.20500 210.25 0.044 2-Way Interactions 3 0.13000 0.13000 0.04333 2.17 0.454 Time*Temp 1 0.00500 0.00500 0.00500 0.25 0.705 Time*Pressure 1 0.08000 0.08000 0.08000 4.00 0.295 Temp*Pressure 1 0.04500 0.04500 0.04500 2.25 0.374 Residual Error 1 0.02000 0.02000 0.02000 Total 7 4.72000

Configuration and Analysis

• A very complex issue is the configuration of the

device and the sterilization chamber.

• The device configuration and packaging

materials can be evaluated during packaging

validation

• Focus on the loading of the sterilization chamber

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Sterilization Configuration

• Usually use dosimeters to map dosage.

• Coverage (minimum)

– Height 3 levels

– Depth 3 levels

– Width 3 levels

– Numbers for Height

– Letters for Width

– Front, Back, Middle for Depth

22 2B-Middle

3A-Front

3C-Back

Analysis

• Some lessons learned

– Not usually a linear mapping

– Dunnage matters!

– Run to run is fairly consistent with regard to

location

23

Analysis

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Summary

• Sample size is related to risk. Higher the risk to the

patient, the larger the sample size.

• Sterility Assurance is established by validation.

• Field Sterility is established by packaging stability

studies.

• Statistical analysis can be employed to give “confidence”

about the configuration and sterilization results seen in a

run.

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