Biomedical Engineering Reference
In-Depth Information
Table 10.12
Comparison between FSI and NGI for screening of DPI lactose blends based on
FPM
<5
μ
m
(
From
[
38
]—
courtesy of D. Russell-Graham
)
NGI
FSI
Blend
Mean (
μ
g)
RSD (%)
Mean (
μ
g)
RSD (%)
A
58.4
4.9
66.6
3.8
B
59.2
4.5
66.2
4.0
C
50.4
13.4
60.9
3.1
D
55.4
3.7
60.6
3.6
E
63.2
6.8
62.8
6.0
produced at different blend speeds. The values of FSI-determined
FPM
<5.0μm
for the
blends were as expected, according to the predicted order in relation to percentage
of fine lactose in each blend.
However, surprisingly, blend speed appeared to have had no effect on this metric.
In contrast, corresponding values of
FPM
<5.0μm
determined by NGI showed the
anticipated differentiation between both blend speed and % lactose fines, except for
a higher than expected value of
FPM
<5.0μm
for blend E.
In a supplementary study, a commercial DPI device was loaded with capsules of
different fill weights to investigate in greater detail the tracking capability of the FSI
over a wider variation in fine particle mass (
FPM
<5.0μm
) than was evident in the pre-
ceding study. The tracking ability for this metric was assessed over a far greater
magnitude (~90
g) than expected in product development. A new marketed DPI
was filled with capsules of four different fill weights—and therefore different values
of
FPM
<5.0μm
—using a different formulation to that evaluated in the previous stud-
ies. Three actuations of each fill weight were delivered into each CI system in accor-
dance with the compendial methodology as previously described.
This head-on comparison for
FPM
<5.0μm
by both measurement techniques
revealed a near 99% correlation within a wide range of potency (Fig.
10.33
). On that
basis, it appears that if precautions are taken to eliminate bias from particle bounce,
the FSI can track changes in this performance metric as well as the NGI. However,
these authors acknowledged at the time that more work would need to be done to
compare the tracking ability of their FSI compared with that for the NGI in cases
where differences in blend performance are as small as typically found in product
development. While
FPM
<5.0μm
tracking between the FSI and NGI was the main
objective of this study, such an approach would also be useful to test a new inhaler
and drug blend in early product development using also
CPF
>5.0μm
and total impactor
recovery (
TIR
) of API as a supplementary performance metric and system suitabil-
ity check, respectively.
Aside from the technical contribution made by the Pfizer work, their investiga-
tions also provided useful practical information relating to the potential time savings
associated with AIM (Table
10.13
).
The total time quoted for six FSI measurements was estimated to be about one-
third that required for six equivalent analyses with a fully optimized NGI set-up
utilizing multiple sets of equipment and analysts. Given that FSI techniques were
μ
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