(524c) Spray Dried Particle Formation Model to Predict Application Performance

Spray dried particle formation
model to predict the Application performance 

Purpose:

Poorly soluble APIs are often formulated as a solid amorphous dispersion
in combination with an excipient polymer to enhance their solubility. A common
route to producing the dispersion is through spray drying. This process
involves spraying a solution of polymer, active pharmaceutical ingredient (API)
and solvent into a heated drying gas where the liquid spray droplets dry into
solid particles of the amorphous dispersion. 
With changes in spray drying solvent, excipient polymer, or formulation
composition, the particle formation process can be affected due to changes in
polymer solution dynamics and solvent volatility. This further results in changing
the particle morphology and composition uniformity, and potentially changes to
Solubilization enhancement performance.

Approach and Methods:

The earlier work (AIChE 2016 presentation) in
this regard presented a particle formation model to
relate the solvent, excipient, and API properties along with formulation
composition and process conditions to the morphological properties of the final
spray dried particle. The present
work demonstrates the application of the particle formation model to the formulations
including HP (High Productivity) HPMCAS grade polymers and additional model
API’s where there might be potential interactions existing between the API-Polymer-Solvent
systems. The effect of change in solution viscosity
with change in polymer concentration has been experimentally measured for
various grades of HPMCAS and HP HPMCAS polymer excipients and solvent systems.
The experimental database is used to generate the correlations for change in
solvent viscosity with the change in polymer concentration for a given
polymer-solvent / solvent blend system. These correlations are further
incorporated in the particle formation model framework. This takes into account
the reduced viscosity effect of HP HPMCAS polymer grade excipients compared to
that of the normal HPMCAS grade polymers. The corresponding particle morphological
properties are then predicted and their correlation to the experimental
dissolution performance can be determined. In case of the formulation systems
where the correlation is not straightforward, the model was extended to
incorporate any correlations for the polymer-API
interactions and the effect of any non-ideality due to
the polymer solution into particle formation model.

Results:

To apply the droplet drying model to spray drying API-HPMCAS and HP
HPMCAS dispersions, fundamental solution properties were characterized.  The viscosities of such solutions were found
to vary strongly based on the specific HPMCAS polymer and spray drying
solvent.  As shown in Figure 1 at similar
concentrations a wide range of viscosities were observed indicating very different
polymer configurations in solution. Figure 2 show the correlation between
polymer concentration and viscosity, which serves as an input to the particle
formation model.

Figure 1: Viscosity of Polymer/Solvent Solutions that serve as inputs
for particle formation modeling

Figure 2: Solution viscosity vs.
polymer concentration correlations for incorporation in the particle formation
model framework

Having quantified these properties, predictions around the droplet
drying process and resulting particle properties will be shared.  It will be shown that depending on the
solvents selected for spray drying, diffusion controlled or surface recession
controlled drying kinetics can occur resulting in very different particle
morphologies and compositional uniformity. These predictions would be then
correlated with the experimental dissolution performances of the given systems.

Conclusions:

The particle
formation model predicts the preferred solvent and excipient selection trends
based on API properties to streamline spray drying process design. Examples are
presented that show for specific APIs, such as Griseofulvin,
used with different grades of HPMCAS polymer excipient and various solvents, that
experimental dissolution trends correlate well with the model predictions. This
indicates that the basic model is helpful where there might not be any
interaction between the API and the excipient molecules. The capability of the extended model including
the solution viscosity effect and API-Polymer interaction effect are
demonstrated with the use of experimental correlations in the model framework. The
ability to predict the nature of the particles formed based on formulation and
process properties provides the formulator with a valuable tool to optimize
this process to hone in on a targeted outcome prior to conducting time
consuming experiments. Particle morphology can play a critical role in
downstream processing and ultimately the application performance. Combining
polymer chemistry and formulation expertise with modeling capabilities provides
formulators with a streamlined route to product development.