(424e) Overcoming the Challenges of Noisy Data during the Calibration of NIR As a PAT Technique to Measure Roller Compacted Ribbon Density

RESULTS
AND Discussion

        Calibration
of the NIR method to ribbon density was challenging due to the presence of
spectral data from broken, split and curved ribbons in the data set
particularly for blend 3 which had the highest moisture content (6.96 % w/w). 
All initial processing of the full data set indicated that some form of data
cleaning was required in order to process the MultiEye™ at-line data set. The
visual discard method was applied to the full data set and was found to be
particularly successful for blends 1 and 2 (Figure 1). After using the
visual discard data cleaning method MulitEye™ data the calibration correlation
was found to be as good as the off-line higher scan resolution Perkin Elmer
spectrometer. Blend 1 off line r=0.92, visual discard r=0.95.

However it is
necessary to replace the visual method of spectra cleaning with a non-subjective
method which was capable of screening for these erroneous probe readings. The trimmed
mean eliminates a specified percentage of the data from both the high and the
low ends of the dataset before evaluating the standard mean of the remaining
data. For this data set the trimmed mean method sets a limit on how data is
cleaned from the data set allowing for the removal of a faulty probe reading
(25% of data) or a poor sample (33% of data). The 33% Trim Mean in place of the
Full Mean reduced the impact of spectral variation or misreads between samples
or probes. The Trim Mean method was found to be at least as successful as the
Visual Discard method at cleaning the data set prior to development of the
calibration equation (Table 1 and Figure 2). The Trim Mean method was preferred
as the decision on data to include in the calibration model as it is not
subjective and simple to apply. Major variation is apparent in the spectral data
for Blend 3 (75%) which renders it unsuitable for prediction and calibration. These
processing variations were attributes to the high moisture of MCC in this
compacted blend.

CONCLUSIONS

        The 33% Trim Mean method offers a simple and practical solution to
dealing with the NIR spectral challenges when applying this PAT technique to
roller compacted ribbon in-line/at-line. Further development of this method
when used for calibration could investigate the optimal number of ribbon
samples to % data trimmed to achieve a statically robust balance of data
cleaning. Increasing the number of samples used to during calibration may allow
for a greater retention of data in the TrimMean e.g. 5 samples and keeping 3
giving a 20% Trim Mean. The Trim Mean method is therefore no less successful
then other simple calibration methods but offers the advantage of a simple,
easy to follow and non-biased means of removing NIR data collected due to probe
sampling error at-line/in-line.

ACKNOWLEDGMENTS

        Research is
funded by the Synthesis and Solid State Pharmaceutical Centre (SSPC) under
grant number 12/RC/2275, the Mathematics Applications Consortium for Science
and Industry funded by Science Foundation Ireland Investigator Award 12/IA/1683
and the Pharmaceutical Manufacturing Technology Centre, Ireland. Microcrystalline
cellulose PH102 donated by FMC Corporation. Innopharma Laboratories for use of
the MultiEye^TM NIR Spectrometer.