Modeling and Optimal Control of Solution Mediated Polymorphic Transformation of l-Glutamic Acid

Abstract

The solution-mediated polymorphic transformation (SMPT) of L-glutamic acid is modeled using the method of moments (MoM) with the addition of a dissolution term to account for the transformation of the metastable to the stable polymorph. The numerical solution methodology involves the kinetics of nucleation, growth, and dissolution for the polymorphic system. The effects of the cooling profile, initial solute concentration, and seeding conditions on the product quality were investigated. In supersaturated solutions with respect to both polymorphs, the natural cooling yielded the highest mass of the metastable form, while the nonlinear cooling resulted in the highest mass of the stable form (13.41 g/kg of solvent). The ratio of the stable to metastable form masses was higher with the higher cooling rate parameters. In solutions supersaturated with respect to the stable form and undersaturated relative to the metastable form, the dissolution of the metastable form favored the production of the stable form. The number-weight average size of the stable particles was 148.5 μm with the nonlinear cooling policy which was 51% and 134% more than those corresponding to the linear and natural cooling policies. Finally, nonlinear programming (NLP) was used in a dynamic mode to investigate the optimal control of the process with different objective functions. It was shown that the optimal control policy had a favorable effect on the yield of the stable or metastable form as well as the particle sizes at the end of the batch. The optimal control using an objective function to maximize the mass of the metastable form at the end of the batch resulted in 7.8 g of crystals/kg of solvent for metastable form which was 33% and 381% higher than the natural and linear cooling policies. For an objective function to maximize the mass of the stable form, the optimal cooling policy increased the mass of the stable form by 3.2% compared to the nonlinear cooling policy.

Form selection of concomitant polymorphs: A case study informed by crystallization kinetics modeling

“…More than 90% of active pharmaceutical ingredients are manufactured as crystals 1 . Besides the primary importance of chemical purity, the control of polymorphic purity in both batch and continuous crystallization processes is of increasing interest in recent years 2‐4 . Polymorphs of a compound differ in crystal structure and are ubiquitous in both nature and industry.…”

“…showed negligible changes over time, thereby implying the absence of nucleation (Figure A8). No significant breakage and agglomeration of particles were found during the experiments (Figure A9).Solution concentration of seeded crystallization was simulated bythe PBE model (Equations (1) and(2)) that was integrated with respective growth kinetic models (MT, BCF, and B + S). The growth parameters of TFA form I were optimized by minimizing the residual difference between simulated and experimental supersaturation values (Equation (30)).…”

Systematic model identification and optimization-based active polymorphic control of crystallization processes

“…Raman and image analysis were used to measure solute concentration, crystal size distribution and polymorphic ratio; a finite elements method was used to solve the population balance equation, PBE (using the software FEMLAB). Many different solution techniques were used to solve the PBE for the polymorphic transformation of L-glutamic acid: moving pivot technique (Cornel et al 2009), finite volume method in gPROMS (Ono et al, 2004) and the method of moments (Hermanto et al 2007;Hermanto et al 2009;Hermanto et al 2011;Sheikholeslamzadeh and Rohani 2013). Despite working with the same system the authors of the mentioned studies used different types of equations to express the kinetics of the phenomena involved in the polymorphic transformation of L-glutamic acid.…”

Prediction of Solubility of Active Pharmaceutical Ingredients in Single Solvents and Their Mixtures — Solvent Screening

“…One of the main applications of the thermodynamic models is in the chemical industries which use solvent (or their mixtures) [19][20][21][22]. Two cases of the vapor-liquid equilibrium of common industrial solvent systems are discussed here.…”