(214c) Micro-Scale Process Development and Optimization for Crystallization Processes

Initial
experimental phases of crystallization process development are commonly carried
out at very small scales, typically using 1-5mL vessels. The aims of these
early phases of process development are to select a solvent based on solubility
and crystal solid state. These activities are commonly conducted in high
throughput reactor systems, such as the Crystal16^® and Crystalline,
from Technobis Crystallization Systems, as shown in Figure 1(a) and 1(b),
respectively. However, for the development, validation and optimization of crystallization
process models this data is usually not utilized and the selected solution system
is probed experimentally and more quantitatively at much larger scales,
typically between 100 – 1000 mL. A more quantitative usage of the data
generated at small scale for the development of process models which may
significantly reduce the number of larger scale experiments required, would aid
in addressing the increasing constraints on time and materials in
pharmaceutical development.

Solubility
and metastable zone width (MSZW) experiments are routinely conducted with both
experimental systems, shown in figure 1, with clear points (indicating the
point of dissolution) and cloud points (indicating the on-set of nucleation in
solution) utilised to indicate the MSZW for a given cooling rate, agitation
rate and solute composition [2]. Through turbidity and temperature measurements,
both experimental systems provide the ability to quantitatively determine MSZW and
therefore, the primary nucleation kinetics of the solution system [2, 3]. In
addition, the Crystalline system also has the added measurement capabilities of
particle visualization, providing a number based representation of the particle
size distribution (PSD), as shown in figure 2, and Raman modules for
concentration and solid form monitoring. In-situ sizing via image analysis is also
not prone to sampling issues possible with offline PSD measurements techniques
like laser diffraction. In addition, the in-situ image analysis capabilities
can be enormously beneficial in terms of aiding process understanding,
providing crucial information for crystallization mechanism and model
discrimination activities. The lack of probes inserted into the reaction vessel
also leads to no cross contamination and no interference in the crystallization
environment. All of these techniques are
integrated into a small reactor with overhead stirring and refluxing
capabilities, which can qualitatively mimic the likely vessel configurations at
larger scales.

(a)                                                            (b)

Figure
1: Images of the (a) Crystal16^® and (b) Crystalline experimental
systems from Technobis Crystallization Systems [1].

Figure
2: Particle visualization and calculated PSD based on images.

In
this work, data from paracetamol and 3-methyl-1-butanol solutions at the
micro-scale was utilized to estimate the crystallization kinetics of the model,
including crystal growth and primary nucleation, enabling model development, as
well as mechanism discrimination. The final predictions of the developed
process model were compared with a previously developed and validated process
model, which employed larger scale 1 L scale experiments. Cross-validation with
FBRM, laser diffraction and online solute concentration data from the larger
scale, 1 L was conducted. Although perfect agreement was not achieved, primarily
due to scale and reactor dependent kinetic mechanisms, such as primary
nucleation and secondary nucleation, the process model was in general
qualitative agreement with the original model developed with larger scale
experimental data. A key outcome of this work is an adapted process development
workflow for the design, model validation and optimization of processing models
for crystallization systems. This workflow enables crystallization process
development with an order of magnitude lower demands for materials. In
particular raw API, which may not be available in the early stages of process
development. In addition, the design space for the process can be assessed
early on, such a process robustness and viability of continuous processing,
with less dependence on larger scale, more material intensive experiments. As a
result, by utilizing commonly available micro-scale process data the material
demands and requirements for larger scale experiments can be significantly
reduced, leading to a step change in pharmaceutical process development
efficiency and productivity.

References:

[1]
Technobis Crystallization Systems, Our products, accessible online:
https://www.crystallizationsystems.com/our-products, (2016).

[2]
Mitchell, N.A, Frawley, P.J., Nucleation
kinetics of paracetamol–ethanol solutions from metastable zone widths, J.
Cryst. Growth, 312(19), 2740–2746, (2010).

[3]
Kadam, S.S, Kulkarni, S.A., Ribera, R.C., Stankiewicz,
A.I., ter Horst, J.H., Kramer, H.J.M.,  A new view on the metastable zone width
during cooling crystallization, Chem. Eng. Sci., 72, 10–19 (2012).