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Profile Analysis of Cascade Impactor Data: An Alternative View Andrew R Clark, Ph.D. Orally Inhaled and Nasal Drug Products Subcommittee of the Advisory.

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Presentation on theme: "Profile Analysis of Cascade Impactor Data: An Alternative View Andrew R Clark, Ph.D. Orally Inhaled and Nasal Drug Products Subcommittee of the Advisory."— Presentation transcript:

1 Profile Analysis of Cascade Impactor Data: An Alternative View Andrew R Clark, Ph.D. Orally Inhaled and Nasal Drug Products Subcommittee of the Advisory Committee for Pharmaceutical Science April 26, 2000

2 Comparing impactor distributions - Why and how Batch release –Is the current batch equivalent to those used in pivotal trials ? Bioequivalence –Is a “new” product equivalent to the innovator ? Marker or label validation –Does the marker or label match well enough to represent the active drug ? Simple statistical “distance” or a measure with physical significance ?

3 Physical significance of distribution differences Al. Deposition TB deposition Fraction Deposition Aerodynamic diameter (um) Test MMAD 3 um, GSD 3 Reference MMAD 3 um, GSD 2 Cumulative % undersize % Undersize difference 12 at both 9.0 and 1.2  m Deposition Probability 0.9, 0.8 at 9.0  m and 0.4, 0.0 at 1.2  m for TB and Al respectively W0W0 W5W5  f(  w i )  P d.f(  w i )

4 A model for investigations of F2 and   Changes in size distribution for a log-normal model Reference MMAD 3 um, GSD 2 Test MMAD 1 um, GSD 2 Test MMAD 3 um, GSD 3 Aerodynamic diameter (um) Cumulative undersize (%) Median diameter Change in median diameter Change in GSD GSD = d 50 /d 16

5 F2 variation as a function of MMAD and GSD relative to a reference distribution for the ACI F 2 GSD Reference ( MMAD = 2.0, GSD = 2 ) F 2 MMAD (um) Reference ( MMAD = 2.0, GSD = 2 )

6 How F2 measures changes in size distribution Response of F2 for the ACI to changes in MMAD and GSD relative to a 2  m MMAD, GSD = 2 reference aerosol

7 F2 50 Contours for relative change in MMAD and GSD F2 5o contours for the ACI for reference aerosols ranging of 1 to 8  m MMAD with GSD of 2. (Aerosols with MMAD and GSDs lying within the contours would be judged to be similar, i.e. F 2 = > 50.) For 1 um reference d max - d min ~ 0.7  m For 4 um reference d max - d min ~ 2.5  m

8 F2 50 Contours for relative change in MMAD and GSD F2 50 contours for the MLI for reference aerosols ranging of 1 to 8 um MMAD with GSD of 2. (Aerosols with MMAD and GSDs lying within the contours would be judged to be similar, i.e. F2 = > 50.) 1 um 2 um 4 um 8 um GSD aerosol / GSD reference MMAD aerosol / MMAD reference For 1 um reference d max - d min ~ 0.5  m For 4 um reference d max - d min ~ 2.5  m

9 How  2 measures changes in size distribution Response of  2 for the ACI to changes in MMAD and GSD relative to a 3  m MMAD, GSD = 2 reference aerosol

10 Theoretical total lung and alveolar deposition for an inhaled aerosol (GSD of 2) with and without a 5 second breath hold Alveolar deposition with 5s breathold Alveolar deposition without breathold Total lung deposition with 5s breathold Total lung deposition without breathold Deposition [ %] of inhaled MMAD [um] F2 = 50  d p ~ 4 % F2 = 50  d p ~ 150 %

11 Change in deposition as a function of MMAD and GSD relative to a reference aerosol with an MMAD of 2  m and a GSD of 2 (Note. All deposition changes have been shown as negative to facilitate comparison with Figure 3.) How changes in size distribution affect deposited dose

12 Comparison of F2 50 and 10% deposition contours Comparison of F2 50 contours for the MLI with “10% change in lung deposition” contours derived from a lung deposition model

13 An alternative :Theoretical Deposition Fraction & weighted distributions Normalize and apply “distance” statistic ? Deposition weights (P d ) determined from lung deposition model Weighted distribution = Wt stage * P d

14 Weighted distributions and TDF for pMDI data

15 Weighting technique applied to label validation data

16 Issues with Weighting and TDF approach Advantages –Flexibility Choose weighting factors for drug / product application –Can apply simple statistics to values to Wt. or % –Has physical relevance Disadvantages –How to choosing weighting factors Deposition models Receptor distribution –Whole lung versus deposition pattern (TB/AL ratio ?) –Not a primary measure Combination Weights plus “distance” statistic ?


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