(277e) Multi-Scale and Multi-Purpose Modelling for in silico Designing and Optimization of Pharmaceutical Crystallization Process

Crystallization
often serves as a key final and intermediate separation/purification unit
operation in pharmaceutical production. More than 90% of small molecule drugs
are produced in crystalline form[1]. Operation conditions of
crystallization process determine process metrics such as crystal size
distribution, yield, space-time yield (STY) and crystal quality attributes like
crystal shape, morphology as well as solvates. The crystal product properties
affect the efficiency of downstream unit operations such as filtration, drying and
formulation. Moreover, in pharmaceutical products the crystal properties affect
the stability and efficacy of drugs. Therefore, a comprehensive multi-scale and
multi-purpose thermodynamic and kinetic modeling is the main objective of this
work in order to understand crystallization mechanism and define optimum operation
conditions. Optimization of crystallization operation conditions includes selection
of the best solvent or mixture of solvents, cooling rate, anti-solvent flowrate, pH profile, mixing and seeding
parameters as well as selection of mode of operation such as batch or
continuous. Figure 1 shows a comprehensive multi-scale and multi-purpose modeling
framework for in silico designing and optimization of pharmaceutical
crystallization process.

Figure 1: A
schematic diagram illustrating comprehensive multi-scale and multi-purpose
modeling framework for in silico designing and optimization of
pharmaceutical crystallization process

The
framework will be implemented in Matlab-Simulink environment as a tool to
support different engineering tasks from solvent selection to crystallization
process design, optimization and control in life science and biopharmaceutical
industries.

Acknowledgment:
We would like to thank the Danish Council for
Independent Research (DFF) for financing the project with grant ID:
DFF-6111600077B.