Dose Content Uniformity for Aerosol Products

1
Dose Content Uniformityfor Aerosol Products

• Wallace P. Adams, Ph.D.
• OPS/IO
• Advisory Committee for Pharmaceutical Science
• 13 March 2003
• Rockville, MD

2
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)

3
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

4
Present DCU and SCU Tests

• Nonparametric (with a parametric element)
• Single dose and multi-dose products
• At tier 1
• NMT 1 of 10 containers outside of 80 - 120 of
  label claim (LC)
• 0 outside 75 - 125 of LC
• Mean of 10 not outside 85 - 115 LC

5
Present DCU and SCU TestsDCU Through Container
Lifefor Multi-dose Products

• MDIs
• DCU measured at B, M and E lifestages
• for each of three containers
• NMT 1 of 9 determinations outside 80 - 120 of LC
• 0 outside 75 - 125 of LC
• means at each of B, M and E not outside 85 - 115
  of LC

6
Present DCU and SCU TestsDCU Through Container
Lifefor Multi-dose Products

• DPIs (device-metered)
• Same as for MDIs
• Nasal sprays
• Similar to MDIs, except 10 determinations at B
  and 10 at E

7
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

Per discussion with Dr. Walter Hauck
8
A Parametric Tolerance Interval

• Intended to control ranges of specified coverage,
  e.g.,
• 85 of the doses within
• 75 - 125 of LC at
• 95 confidence
• We therefore specify
• min proportion of the batch that should fall
  within the limits (coverage)
• acceptable tolerance limits (target interval)
• degree of confidence

Per discussion with Dr. Walter Hauck
9
Development Of ParametricTolerance Interval
Approaches

• Official in Japanese Pharmacopoeia (JP, 1996)
• Pharmacopoeial Discussion Group
• European Pharmacopoeia, JP, and USP
• Statistics Working Group of PhRMA
• ICH/PDG Task Force

10
Development Of Parametric Tolerance Interval
Approaches, cont.

• Content Uniformity and Dose Uniformity Current
  Approaches, Statistical Analyses, and
  Presentation of an Alternative Approach, with
  Special Reference to Oral Inhalation and Nasal
  Drug Products
• RL Williams et al, Pharm Res, 200219359-66
• A Parametric Tolerance Interval Test for Improved
  Control of Delivered Dose Uniformity of Orally
  Inhaled and Nasal Drug Products
• IPAC-RS, 15 November 2001

11
OPS Issues

• Definition of limiting quality
• Essential to an acceptable DDU test
• 85 of doses in the batch within 75 - 125 of
  label claim?
• 85 of doses within 80 - 120 of label claim?
• 90 of doses within 75 - 125 of label claim?
• 90 of doses within 80 - 120 of label claim?
• other options?

12
OPS Issues

• Robustness of the test
• for non-normally distributed data
• e.g., short-tailed distribution
• properties of the test when the batch is at or
  below the IPAC-proposed limiting quality (e.g.,
  85 coverage)

13
OPS Issues

• Impact of eliminating the zero tolerance
  criterion (ZTC)
• IPAC-RS claims that ZTC increases producer risk
  with little improvement in consumer protection
• value for skewed data

14
OPS Issues

• ? level (less than or equal to 0.05)
• Estimated consumer risk of IPAC-RS proposal
  exceeds 5
• Approaches to assuring ? ?0.05

15
Question 1 for ACPS

• Does ACPS agree that a parametric tolerance
  interval test is conceptually acceptable as a
  replacement for the agencys nonparametric (with
  certain parametric elements) DCU and DCU through
  container life tests for OINDPs?

16
Question 2 for ACPS

• Does ACPS feel that DCU quality standards should
  provide assurance that batch failure rates do not
  exceed some specified level, e.g., 10?

17
Acknowledgments

• Ajaz Hussain (FDA)
• Guirag Poochikian (FDA)
• Don Schuirmann (FDA
• Meiyu Shen (FDA)
• Yi Tsong (FDA)
• Walter Hauck (Thomas Jefferson University)
• Roger Williams (USP)