Thermodynamic and kinetics studies on crystallization of L-Aspartic acid and β form L-Glutamic acid: measurement and modelling
Creators: name: Pabba, Sudhakar
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 340307
subject: Structure and dynamics of materials
classificationCode: 340607
subject: Reaction kinetics and dynamics

description: In pharmaceutical industries, one of the main concerns is the desired purity of the drugs. To achieve the product purity specifications, the production of these chemicals involves one or more separation steps. Crystallization is one of the oldest separation techniques still in vogue due to its excellent purification capability with reasonable energy consumption. In addition to this, it plays a vital role in defining the stability and drug release properties of the final dosage forms. In the present study, crystallization of active pharmaceutical ingredients (APIs) such as L-Glutamic acid and L-Aspartic acid is studied. These drugs have commercial importance, and they can broadly disperse inside proteins associated with the disease. These amino acids have recently been identified as effective drugs for boosting the immune system, especially by inhibiting inflammatory responses to the coronavirus 2, which causes the severe acute respiratory syndrome.

Water is generally used as a solvent in the crystallisation of APIs. However, one of the major challenges in the production of L-Glutamic acid and L-Aspartic acid via crystallisation is their low solubility in the water. Therefore, this thesis focused on the identification of new solvents, having a higher solubility of these API drugs. 

As a first step, the work systematically investigated solubility of L-Glutamic acid and L-Aspartic acid in some new pure solvents and binary mixtures and then compared them with pure water. The influence of co-solvent addition to the binary mixtures on the solubility was studied with varying temperatures. The characterization techniques such as X-ray powder diffraction (XRD), scanning electron microscope (SEM) was employed to track the morphological changes in the drug after dissolution. The results demonstrated that formic acid and trimethylamine (TMA) acts as a co-solvent in the dissolution of these APIs in formic acid + water binary mixtures, while others exhibited an antisolvent effect on the solubilization of APIs in their respective aqueous mixtures. The solid-liquid equilibrium data (SLE) and discussions reported in this contribution can provide guidance for purification and novel strategies for the design and optimization of APIs crystallization.

As a second step, kinetic studies of the systems (APIs + solvents) were conducted to estimate the parameters, and kinetic model for the crystallization of APIs was developed from the experimental data. The temperature dependant model includes all of the kinetic transformation parameters. The crystallization kinetic parameters were estimated by metastable width from the batch data collected from in-situ measurement using Focused beam reflectance measurement (FBRM). The results revealed that nucleation was formed within the metastable zone width, which would help control the final product's desired properties. The kinetic model was used to examine the impact of operating conditions on metastable width and crystal consistency. This study evaluated some important nucleation parameters from Nvlt's approach, such as the nucleation constant (K) and nucleation order (m). 

The third step has focused on the optimization of process variables with new solvent system using the response surface methodology (RSM) model. This model is used to identify the main process parameters affecting crystallization. Several process parameters such as solvent composition, reaction temperature and mixing rate were studied in depth and further optimized. The modelling results indicated that a maximum yield of 99.5% APIs can be obtained under optimized conditions. Experimental verification gives a yield of 98.4% with a model error of 1.1%. This indicates the reliability of model. The data generated from this work will be useful in designing a cost-effective crystallisation process for APIs production in pharmaceutical industries.