This work presents an in silico tool that supports crystallization process development and optimization studies by means of mechanistic modeling, uncertainty identification, comprehensive sensitivity analysis and a quantified process risk assessment. Kinetic model parameters and operation design parameters are considered as a source of uncertainty and variation. Monte Carlo simulations are performed to propagate input uncertainty/variation to model output in terms of process yield, mean crystal diameter and size distribution. To quantify the individual effects and importance of these parameters, global sensitivity analysis e.g. Morris Screening and variance-based decomposition, is performed. The process risk is defined as failure to reach target product specifications and its consequences for the given design space is quantified. This promising study shows, that global uncertainty and sensitivity analysis coupled with the quantification of process risk assessment is a powerful tool and should be of interest to those participating in effective and efficient crystallization process development.
- Pharmaceutical crystallization
- Uncertainty analysis
- Global sensitivity analysis
- Process risk assessment
- Compartmental modeling