1 PTIT for DCU of OINDP: Approaches to Resolution of Identified Issues Wallace P. Adams, Ph.D. OPS/IO Advisory Committee for Pharmaceutical Science 21 October 2003 Rockville, MD

2 Outline Current DCU and SCU Tests Parametric Tolerance Interval Test (PTIT) Consensus Points OPS Issues The “Gap” and the Quality Assurance Constraint Proposed Resolutions

3 Two Guidances Metered Dose Inhaler (MDI) and Dry Powder Inhaler (DPI) Drug Products - CMC Documentation (Draft, October 1998) Nasal Spray and Inhalation Solution, Suspension, and Spray Drug Products - CMC Documentation (Final, July 2002)

4 The DCU and SCU Issue DCU (dose content uniformity) SCU (spray content uniformity) Uniformity of metered doses from an MDI, DPI or nasal spray –within a container for multiple dose products –among containers –among batches

5 Current DCU and SCU Tests Nonparametric (with a parametric element, the sample mean restriction) Single dose and multi-dose products

6 Present DCU and SCU Tests: DCU Through Container Life for Multi-dose Products (Tier 1) MDIs –DCU measured through container life DPIs (device-metered) –Same as for MDIs Nasal sprays –SCU measured at B and E lifestages –for each of 10 containers

7 DCU 1,3 MDIs and DPIs (pre-metered; device- metered) DCU TCL 1,3 MDIs and DPIs (device- metered) SCU TCL 2 Nasal Sprays Unit for DeterminationMinimum labeled dose # of units sampled per container 13 (B,M, E)2 (B, E) First tier, # containers103 First tier, total # determinations10920 Accept after first tier if:  1 outside % and 0 outside % LC  2 outside % and 0 outside % LC Second tier: # additional containers tested 206 Second tier: total # determinations both tiers Accept after second tier if:  3 outside % and 0 outside % LC  6 outside % and 0 outside % LC AdditionalSample mean within % LC at each tier Sample mean within % LC at each of B, M, E lifestages and each tier Sample mean within % LC at each of B, E lifestages and each tier FDA DCU and DCU TCL Tests 1 Metered Dose Inhaler and Dry Powder Inhaler CMC Draft Guidance, Oct Nasal Spray, Inhalation Solution, Suspension, and Spray Drug Products CMC Guidance, July Both DCU and TCL tests apply to MDIs and device-metered DPIs

8 A Parametric Tolerance Interval Approach General form of the criterion: Y  kS where: Y = absolute value (LC - sample mean) k = a tolerance interval constant s = sample std dev RL Williams et al, Pharm Res, 2002; 19:359-66

9 A Parametric Tolerance Interval Intended to control ranges of specified coverage, e.g., –85% of the doses within – % of LC at –95% confidence We therefore specify 1 –minimum proportion of the batch that should fall within the limits (coverage) –acceptable tolerance limits (target interval) –degree of confidence 1 RL Williams et al, Pharm Res, 2002; 19:359-66

10 Consensus Point # 1 Acceptability of the PTIT statistical approach conceptually –Based on a statistical hypothesis test –Facilitates risk communication to practitioners and patients/consumers –Places constraints on both maximum sample SD and sample mean

11 Consensus Point # 2 Elimination of the Zero Tolerance Criterion (ZTC) –ZTC: prohibits any dose in the sample from falling outside the stated interval reduces the likelihood that a unit in the batch will deviate substantially from LC –ZTC conflicts with the producer’s choice of sample size –for normal distributions, PTIT preserves the specified alpha level without the ZTC

12 OPS Issue # 1 Robustness to  level –Non-normal distributions for certain data distributions,  can substantially exceed 0.05 do non-normal distributions exist for some OINDP products and batches? –Estimated consumer risk of IPAC-RS proposal exceeds 0.05 by a small amount, e.g., 0.051, for normally distributed data at certain deviations in batch mean from LC –Approaches to assuring   0.05?   0.05,   0.025?

13 Maximum Type I Error is 5.1% ( occurs for smallest sample size at mean deviation of ±9 %LC) Normal distribution at limiting quality (85% coverage of 100±25% LC) Sample size B. Olsson, ACPS Meeting, 13 Mar 2003

14 Non-normal Distribution IPAC-RS Report, 15 Nov 2001, p. 68

15 OPS Issue # 2 Definition of limiting quality –85% of doses in the batch within % of label claim? –85% of doses within % of label claim? –90% of doses within % of label claim? –90% of doses within 80 – 120% of label claim? –other options? The “Gap” widens as the sample size increases The “Gap” tends to widen as the mean deviates increasingly from 100% LC The “Gap” narrows as the coverage increases and the target interval narrows

16 IPAC-RS Report, 15 Nov 2001, p. 12

17 PTI Test, Multi-Dose Products IPAC-RS Report, 15 Nov 2001, p. 25

18 Consumer protection (Limiting Quality, LQ) same PTI test’s curve is sharper (narrowed area of uncertainty) Fewer acceptable batches rejected (lower producer risk) “Gap”: Fewer rejections does not mean lower quality of accepted batches (see simulated production illustration below)“Gap”: Fewer rejections does not mean lower quality of accepted batches (see simulated production illustration below) Comparison of Operating Characteristic Curves 21 “Gap” LQ FDA test: as in Draft MDI/DPI Guidance B. Olsson, ACPS Meeting, 13 Mar 2003

19 OPS Issue # 3 Robustness in the Producer Protection Region –does the PTIT become more conservative for non-normal distributions?

20 IPAC-RS Report, 15 Nov 2001, p. 68

21 The Quality Assurance Constraint: An Additional Limiting Quality The “Gap” exists between the “FDA curve” and the PTIT curves for all limiting qualities At a 90% acceptance probability, the PTIT allows greater batch variability than does the “FDA curve” for three of four limiting qualities OPS desires to limit the magnitude of the “Gap”

Probability to Accept (%) 5% Area of uncertainty Consumer protection region Producer protection region (changes with sample size) Variability (either standard deviation at a given batch mean or coverage) Operating Characteristic Curve Quality Assurance Region (fixed) Y. Tsong, ACPS Meeting, 13 Mar Slide adapted from B. Olsson, 13 Mar 2003

23 FDA Working Group to Determine (Over the Next Six Months) Limiting Quality Standard Confirm appropriateness of   0.05 Establish appropriate “Quality Assurance Constraint” (at 90% acceptance probability) To include FDA clinical recommendations

24 A Proposed Resolution Adopt the PTIT approach Left side of Operating Characteristic (OC) curve to be approximately superimposable with the FDA OC curve, with emphasis on the 90% acceptance probability region

25 Acknowledgments Craig Bertha, Ph.D. Alan Carlin Walter Hauck, Ph.D. Ajaz Hussain, Ph.D. Guirag Poochikian, Ph.D. Donald Schuirmann Meiyu Shen, Ph.D. Edward Sherwood Yi Tsong, Ph.D. Marilyn Welschenbach, Ph.D. Helen Winkle