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Parametric Tolerance Interval Test for Delivered Dose Uniformity DDU Working Group Update

2. Contents. Background InformationDDU Test ApproachesDesired Outcome of DDU Efforts for IPAC-RSGeneral Agreements FDA PerspectiveWhere are we today?Case Studies from NDAs and/or active candidates in late developmentSummaryFDA Proposal. 3. Background Information. Pre-1998; Walter Hauck (S

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Parametric Tolerance Interval Test for Delivered Dose Uniformity DDU Working Group Update

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    1. 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

    2. 2 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

    3. 3 Background Information Pre-1998; Walter Hauck (SGE), proposes to use PTIT for delivered dose uniformity testing to FDA Hauck’s proposal: Agency sets goalposts Agency sets coverage within goalposts Applicant 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

    4. 4 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

    5. 5 DDU Test Approaches

    6. 6 Desired Outcome of DDU Effort for IPAC-RS Michael 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

    7. 7 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

    8. 8 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:

    9. 9 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

    10. 10 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%

    11. 11 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%

    12. 12 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%

    13. 13 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

    14. 14 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

    15. 15 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

    16. 16 Desired Outcome of DDU Effort for IPAC-RS Michael 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

    17. 17 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

    18. 18 Regulatory Flexibility Acceptable quality batches will be allowed into the market that currently could be rejected No Zero Tolerance limit Flexibility in setting the sample size Tier-II testing does not carry any penalty Exceptions to FDA criteria could be proposed based on appropriate justification

    19. 19 Questions to ACPS Would you accept FDA WG proposal as outlined in slide # 15?

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