(451f) Use of Blue Dye Powder Tracer to Evaluate the Residence Time Distribution of Continuous Manufacturing Direct Compression Equipment

Use Of Blue Dye Powder Tracer To Evaluate The Residence Time Distribution
Of Continuous Manufacturing Direct Compression Equipment

Authors  Bill Engisch, Mike Kennedy, Steve La

Affiliation/Company Amgen, Inc.

Purpose

Continuous manufacturing (CM) of solid
oral dosage drug products is a rapidly emerging technology being implemented by
the pharmaceutical industry to reduce development and commercial costs, improve
product quality and operational efficiency, and provide a flexible
manufacturing network. The residence time distribution (RTD) of a CM process is
a powerful characterization tool that can be used to develop robust process
control through predictive modelling. There would be great advantages to being
able to understand the RTD through a visual API surrogate that can be
qualitatively observed, quick to implement, and independent of traditional NIR
methods that are instrument dependent. This has a huge advantage early in development
when API may be limited, analytical methods such as NIR have not yet been
developed, or equipment access is limited. Therefore, the purpose was to
develop and verify a visual API surrogate method for evaluating RTD.

Methods

The work presented here is from a case
study for testing the feasibility of manufacturing a solid oral dosage
formulation via continuous direct compression (DC) on a GEA CDC-50
(commercially available integrated CM DC line). During the study, a method was
developed to assess residence time through tracer-pulse addition experiments
using a small quantity of FD&C Blue No. 2 Aluminum Lake dye as a tracer and
collection of time-stamped samples from the output of the tablet press.

Results

Prior to an API trial on the CM equipment,
a placebo trial using a similar formulation composition with a surrogate for
the API was executed. During these placebo runs, the residence time as a
function of CM process conditions was evaluated with pulse additions of blue
dye.  Collected tablets were compared to a pre-made set of color standards with
known concentration for quick qualitative analysis.

Post-analysis involved quantitative
measurement of the blue dye tablets via a photo spectrometer. Color difference (delta E*ab, calculated based on baseline
white tablets via the CIE76 formula) is plotted against sampling time in the
figure below (red diamonds).  The shade of blue from the pulsed-in dye
correlates with concentration. The resulting concentration-time profile of
tablets from the CDC-50 experiments (shown as blue diamonds) was translated
into a RTD via a fit to the axial dispersion model.

During the API trials, samples from a
transition experiment (change between API loads) were collected and afterwards assayed
by HPLC, verifying the RTD prediction derived from the quantitative analysis of
the blue dye containing placebo tablets. See the figure below; the model and
assayed tablets are overlayed.

Conclusion

The blue dye method provided
information needed to predict system response without consuming a limited API
supply. RTD is a tool that provides valuable insight into any continuous
process, and in this case, it was used to predict the transition time needed to
reach a steady state following process or formulation changes.