Good Cascade Impactor Practices - Good Cascade Impactor Practices, AIM and EDA for Orally Inhaled Products - page 96

Table 4.1 Factors to be considered in CI method development ( Adapted from [ 3 ]— used by
permission )

Method development
Factor potentially affects Cause(s) MB APSD

API recovery solvent Measurement Ye s Ye s

Quantitation lower limit Measurement Ye s Ye s

Use of collection surface coating Machine Ye s Ye s

Recovery techniques Man/measurement Ye s Ye s

Use of a pre-separator Machine No, except for carrier

based DPIs

Ye s

Cleaning procedure Man/material Ye s Ye s

Electrostatic charge Machine/material Ye s Ye s

Environmental factors (barometric
pressure, temperature, humidity)

Material Ye s Ye s

Use of a backup filter Machine Ye s Ye s

GCIP can be considered the sum of two basic parts:

1. Factors affecting the performance of the CI system that should be considered in
method development
2. Factors that should be considered in day-to-day use

As might be expected, most of the issues raised in this guidance are the same as
those already discussed largely from the subsequent assessment of Bonam et al. [ 2 ].
The factors identified in the GCIP document as influencing APSD as well as MB
are summarized in Tables 4.1 and 4.2 , respectively. These lists provide a systematic
guide to those involved in CI method development and routine use as to signposts
for potential causes of deviations in both MB and aerosol APSD.
These tables serve to highlight the desirability for a simpler-to-perform yet as
precise as possible process for determining OIP quality based on emitted aerosol
particle size-related data. These factors are each linked to one or more of the causes
of variability discussed in the previous section.

4.3.1 CI Method Failure Investigation Tree

The compilers of the GCIP document were primarily focused on addressing the issue
of how to manage MB values that are outside the current ±15% label claim dose
limit set in the 1998 draft CMC Guidance for OIPs by the FDA [ 4 ]. An issue of signifi-
cance is the lack of a fallback method in the event that an out-of-specification (OOS)
or out-of-trend (OOT) MB is determined. The MB failure investigation tree, which
might also be termed as CI method failure investigation tree (Fig. 4.4 ), was a signifi-
cant achievement, in that for the first time, a process for addressing OOS/OOT events
associated with CI/MSLI-based measurements was established that provides a work-
able pathway for the analyst faced with such circumstances.