(162d) Disintegration and Dissolution Modeling for Accelerated Drug Product Process Development
- Conference: AIChE Annual Meeting
- Year: 2017
- Proceeding: 2017 AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
Monday, October 30, 2017 - 1:36pm-1:58pm
We present a methodology to streamline tableting process
development complemented by a mathematical model of disintegration and
dissolution. In a state-of-the-art tableting process development the main goal
is to achieve an optimal tradeoff between mechanical strength, disintegration
time, friability, dissolution profile, tablet weight uniformity and any other
performance variable of interest. Excluding dissolution testing, the assessment
of tensile strength, disintegration time, friability and tablet weight
uniformity is based on simple and fast tests which can be performed during the
tablet manufacturing and the results can be promptly used for the process
optimization. In contrast, the dissolution assessment is laborious, time
consuming and can only be reliably performed in analytical laboratories.
Therefore, taking into account the dissolution profile in the optimization loop
largely increases the development cycle-time which is often not feasible at
early process development stages. However, this is particularly important when
formulating amorphous drug product intermediates to optimize the release rate
and supersaturation maintenance which are paramount for drug performance .
In the proposed methodology the early assessment of
dissolution profile is performed with a first principles mathematical model which
takes into account intrinsic material properties such as drug diffusivity in the
polymer matrix and in the dissolution media , the polymer swelling/erosion
rate  and whether the API is crystalline or is in an amorphous solid
dispersion. The disintegration dynamics are handled with a Population Balance
Equation  and are coupled to the dissolution model. Whenever direct
assessment of intrinsic material properties is not possible, these parameters
are obtained via curve-fitting the model to experimental dissolution data. The
curve-fitting is performed using a particle swarm optimization algorithm, which
is suitable for multivariate and multi-objective problems.
We present a case-study on the application of the
methodology to the downstream process development of an amorphous solid
dispersion which illustrates the advantages of complementing laboratory
development with a computational tool in terms of process and drug performance
without hindering the development cycle-time.
Figure 1: Dissolution profile of a tablet formulated from
an amorphous solid dispersion intermediate obtained both experimentally and
from the presented mathematical model.
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