Tablet shape was found to have little effect on intertablet coating uniformity but did, however, play a role in intratablet
coating uniformity due to the extent to which tablets have a preferred orientation as they pass through the spray zone. The
analysis of several different tablet shapes shows a trend with an orientation index (OI)—a quantitative measure of the existence
of a preferred tablet orientation in the spray zone—that correlates with a mean aspect ratio of the tablet shape (see Figure
3). Tablets with a smaller mean aspect ratio tend to have improved intratablet coating uniformity over those with a larger
mean aspect ratio.
Figure 3 (Pfizer–DEM): The Orientation Index (OI) describing the extent of a preferred orientation in the spray zone— and
the resulting likelihood for poor intra-tablet coating uniformity—is shown for several tablet shapes. The mean tablet aspect
ratio (A) is defined by the tablet length (L), width (W), and thickness (T). The dashed line represents the least squares
linear fit to the data.
The deployment of EDEM modeling in Pfizer drug-product development has accelerated the decision-making process by predicting,
before process scale-up, the performance of commercial tablet shapes at process scale. The modeling is rapid, broadly applied
across the solid-drug product portfolio, and has flexibility to assess unique shape decisions early in the development process.
The value of this predictive computational tool was estimated using DoOptima software (Decision Options, LLC), which uses
a market normalization process to analyze the impact on projects at various phases accounting for the typical number of projects
transferring to commercial scale per year, the material, manufacturing, supplies, and labor costs associated with conducting
the trial compared with the cost of the software license and resources for the simulations. The net present value of predictive
modeling for film-coating scale-up was estimated at approximately $500,000 in the first year (9). Based on this success, the
future focus should be to continue to advance and deploy predictive computational models to support drug product development
See a video demonstration from DEM Solutions here.
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