A spray drying process model enabled accurate prediction of
dryer outlet temperature and collection relative humidity for a
range of spray drying conditions spanning a threefold increase in
liquid feed flow rate. Linking calculated collection RH values with powder vapor sorption data kept powder residual moisture content
close to target values for the process development runs, thus reducing
the risk of an impact on finished product quality. The process
throughput increase was realized with a substantial time savings as
compared to an iterative, empirical approach, illustrating that process
modeling has development lifecycle benefits as well as product
quality control implications.
A particle-formation Monte-Carlo simulation allowed rank ordering
of formulation and process variables by their relative
importance in determining the aerodynamic size distribution of
spray-dried engineered particles, a crucial product characteristic
in pulmonary drug delivery. The factors identified as having the
strongest effect were atomized droplet diameter, excipient concentration
in the feedstock, and particle-formation void fraction.
This knowledge allows an informed approach to implementation
of formulation and process controls to ensure consistent quality
of the finished product. Additionally, the simulation proved quite
accurate at prediction of aerodynamic size distributions.
Both models have proven to be valuable aids in understanding
formulations and the spray drying unit operation during early
phase process development, and in laying the groundwork for a
quality-by-design approach to pharmaceutical product development.
As process and powder characterization data sets grow, the
concurrent growth and synthesis of these models should prove
invaluable in the eventual establishment of a design space for the
powder production process.