(621f) Parameter Estimation of Reaction Kinetics from Spectroscopic Data - Developments and Applications
- Conference: AIChE Annual Meeting
- Year: 2018
- Proceeding: 2018 AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
Thursday, November 1, 2018 - 9:45am-10:06am
That is why, we take a closer look at the development of optimization-based procedures in order to estimate the variances of the noise in the system variables and spectral measurements. Then, with the estimated variances we determine the concentration profiles and kinetic parameters simultaneously using adequate strategies. The work is based on the approach proposed by Chen et al. (2016) using maximum likelihood principles for simultaneous estimation of reaction kinetics and curve resolution from process and spectral data. For this a new software environment was developed which is continuously enhanced. This environment is based on Pyomo with different discretization options for the processes described by ordinary differential/differential algebraic equations, such as collocation using Pyomo.DAE and an efficient implementation of variable-order and variable-coefficient BDF methods, implemented in IDA by sundials. The further investigations regarding this software environment, the identification of absorbing species and challenges arising from pharmaceutical processes are presented within this talk. The outcomes are illustrated by several case studies of pharmaceutical processes. The nonlinear programming (NLP) problems, formulated for these applications, are solved using IPOPT and using sIPOPT for the determination of confidence regions for the kinetic parameter estimates.
We gratefully acknowledge Pfizer Inc.âs funding.
W. Chen, L. T. Biegler, and S. G. MuÃ±oz. An approach for simultaneous estimation of reaction kinetics and curve resolution from process and spectral data. Journal of Chemometrics, 30:506â522, 2016. doi:10.1002/cem.2808. URL http://dx.doi.org/10.1002/cem.2808.