Parametric Tolerance Interval Test for Delivered Dose Uniformity (DDU)

Working Group Update

Moheb M. Nasr, Ph.D.Office of New Quality Assessment

(ONDQA, CDER, FDA)

Advisory Committee of Pharmaceutical Science

October 25, 2005

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Contents

Background Information DDU Test Approaches Desired Outcome of DDU Efforts for IPAC-RS General Agreements – FDA Perspective Where are we today? Case Studies from NDAs and/or active candidates

in late development Summary FDA Proposal

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Background Information Pre-1998; Walter Hauck (SGE), proposes to use

PTIT for delivered dose uniformity testing to FDA Hauck’s proposal:

Agency sets goalpostsAgency sets coverage within goalpostsApplicant determines sample size to meet

Agency requirements

1998, Inhalation Drug Product Workshop (about 600 attendees)

November 2001, IPAC-RS presented a report in response to Dr. Hauck’s presentations

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Background Information Since 2001, FDA’s position has been that data should be

provided to support any proposed PTIT criteria from approved drug products in the United States or from those which are, “close” to approval in the U.S. (e.g., NDA in review or IND in late Phase-3)

Several approaches of PTIT were discussed between IPAC-RS and FDA

Fall 2003, CDER proposed the formation of an FDA working group to report to ACPS (Bob O’ Neil, Moheb Nasr, Badrul Chowdhury and Lawrence Yu)

An FDA/IPAC-RS joint technical subgroup was formed (Bo Olsson, Dennis Sandell, Rik Lostritto, Guirag

Poochikian, Yi Tsong, and Meiyu Shen) to provide evaluations and recommendations

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DDU Test ApproachesTest Attribute Current Practice PTIT

Mean limit 85-115% of LC 85-115% of LC

Individual limits

None allowed outside 75-125%

No limit on individuals

# of tiers 2 tiers with a 1:3 ratio of sample sizes

2 tiers with a 1:3 ratio of sample sizes

Tier sample size

Guidance defined

“Inflexible”

Applicant defined

“Flexible”

Tier II testing versus Tier-I

Less likely to pass at Tier-II (individual limit effect)

More likely to pass at Tier-II (design feature of the test)

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Desired Outcome of DDU Effort for IPAC-RSMichael Golden (GlaxoSmithKline), 21 October 2003

Agree that PTI test approach is the default standard Parametric (no Zero Tolerance) Coverage as quality definition

Allow product-by-product justification of sample size multiple sampling plans, e.g., 12/36 to 30/90

Agree on a quality standard that is acceptable for FDA and industry

Have published Guidance reflecting these agreements

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General Agreements – FDA Perspective

FDA is committed to implement QbD principles in all drug products The Agency is appreciative for the collaboration with IPAC-RS throughout

the process All parties came to a better understanding of respective positions PTIT is a more scientific and risk based approach to setting DDU

specifications Goalposts: 80-120% of label claim Elimination of the zero tolerance criteria is appropriate in this context The FDA-proposed methodology for control of upper and lower “tails”

outside goalposts was accepted by IPAC-RS Beginning and End testing from the same OINDP unit was agreed The Pocock approach to split the Type I error between the two tiers was

agreed This approach combines the advantage of a larger sample size in 2nd tier with a

reasonable possibility of completing the test in 1st tier These agreements are significant and took a substantial time to reach

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Where are we today? Need to remember that DDU testing is just one of several

attributes tested when evaluating quality of OINDP to assure safety and efficacy

OC curves indicate the probability of passing given a hypothetical population standard deviation

OC curves are not used for individual batch decisions

The following operational equations represent the approach which would be used in practice to test a batch:

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Operational Equations used to determine pass or fail

Mean = sample mean SD = sample standard deviation K’s are tabulated using the PTIT model Pass if:

85% ≤ Mean ≤ 115% , AND SD ≤ [120 – Mean] / K, [if mean >100%] OR SD ≤ [Mean – 80] / K, [if Mean < 100%]. These 2 SD equations are identical by symmetry.

For some of the case studies which follow, judicious pooling of data was done to utilize existing data. This would not be done as part of a future test

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Solution MDI Case study Six batches evaluated, n=10 cans; each can is tested

at beginning (B) and end (E) of life Sample mean is close to LC (within 3%) and SD is

typically within 3%

Coverage within Goalposts (beta) Sample Size (n) 90% 87.5% Other

10 as Tier-I Pass B, E Pass B, E - 20 as Tier-I Pass B, E Pass B, E - Other - - -

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Suspension MDI Case Study LOW strength presentation of a multi-strength product Three batches evaluated, n=10 canisters; each can is tested

at beginning (B) and end (E) of life Sample mean values are typically within 6% of LC and SD is

also within 5%

Coverage within Goalposts (beta) Sample Size (n) 90% 87.5% Other

10 as Tier-I Pass B, E Pass B, E - 20 as Tier-I Pass B, E Pass B, E - Other - - -

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Suspension MDI Case Study HIGH strength presentation of the same multi strength

product Three batches evaluated, n=10 canisters; each can is tested

at beginning (B) and end (E) of life Mean values are typically within 4 % (but as high as 106%) of

LC and SD is also within 4.5%

Coverage within Goalposts (beta) Sample Size (n) 90% 87.5% Other

10 as Tier-I Pass B, E Pass B, E - 20 as Tier-I Pass B, E Pass B, E - Other - - -

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Device Metered DPI Case Study 3 batches were evaluated at 2 stability time points (0 and 18

months), N=10 units tested at beginning (B) and end (E) of life That is 12 evaluations in this case Sample mean is typically within 3% of LC and SD is typically

between 3.5 to 5.5% 10 of 12 evaluations pass 90% coverage at n=10 11 of 12 evaluations pass Tier-I at 87.5% coverage (n=10) 12 of 12 evaluations pass Tier-II (n=30) at 87.5% coverage when

the values were pooled from the 2 previous time points (9 and 12 months) keeping batch # and life stage the same

Coverage within Goalposts (beta) Sample Size (n) 90% 87.5% Other

10 as Tier-I 10 of 12 Pass B, E

11 of 12 Pass B, E

-

20 as Tier-I - - - 30 as Tier-II - 12 of 12

Pass B, E -

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Summary It is appropriate to set the coverage within the defined goalposts (80-

120% of label claim) to assure that the quality is in line with safety and efficacy concerns and with a balanced manufacturing and consumer risk

A number of real cases were evaluated including recently approved products and active candidates in later development

90% coverage is similar to the current Agency Guidance recommendation if the zero tolerance criterion is removed

Batches failing current FDA criteria (based on zero tolerance violation) could pass the FDA’s proposed PTIT (next slide)

However, 87.5% is more flexible, yet allows for appropriate discrimination to ensure that quality batches are marketed; batches which are outside acceptable safety and/or efficacy ranges

or which represent inferior quality are rejected

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FDA Proposal

PTIT applied to DDU testing is in line with FDA current initiatives: QbD and demonstration of product and process

knowledge Science and risk-based specification of drug product

Goalposts are 80% to 120% of label claim 87.5% coverage within the goalposts is appropriate Sample size is determined and set by the applicant Exceptions to proposed criteria could be proposed by the

applicant with adequate scientific justification. FDA proposes to update the draft MDI / DPI Guidance

accordingly

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Desired Outcome of DDU Effort for IPAC-RSMichael Golden (GlaxoSmithKline), 21 October 2003

Agree that PTI test approach is the default standardAgree that PTI test approach is the default standard Parametric (no Zero Tolerance)Parametric (no Zero Tolerance) Coverage as quality definitionCoverage as quality definition

Allow product-by-product justification of sample sizeAllow product-by-product justification of sample size multiple sampling plans, e.g., 12/36 to 30/90multiple sampling plans, e.g., 12/36 to 30/90

Agree on a quality standard that is acceptable for FDA and industry

Have published Guidance reflecting these Have published Guidance reflecting these agreementsagreements

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FDA: Roles and Responsibilities *

Review side (lead) Scientific assessment of product and

manufacturing process design

Evaluate and approve product quality specifications in light of established FDA standards (e.g., impurities, stability, etc.)

Set and maintain product quality standards

* Janet Woodcock, M.D. Pharmaceutical Quality Assessment Workshop, October 5, 2005

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Regulatory Flexibility

Acceptable quality batches will be allowed into the market that currently could be rejectedNo Zero Tolerance limitFlexibility in setting the sample sizeTier-II testing does not carry any penaltyExceptions to FDA criteria could be proposed

based on appropriate justification

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Questions to ACPS

1. Would you accept FDA WG proposal as outlined in slide # 15?