Defense Date
2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Chemical and Life Science Engineering
First Advisor
Dr. Thomas Roper
Second Advisor
Dr. Michael Hindle
Third Advisor
Dr. Michael Peters
Fourth Advisor
Dr. Mo Jiang
Fifth Advisor
Dr. Tai Yuen Yue
Abstract
Crystallization of pharmaceutical APIs controls the particle size, shape, and purity, all of which have direct effect on the performance and safety of the medicine. In recent years, the push to develop and understand continuous processes has enveloped the scientific community in drug manufacturing research, for both chemical reactions and crystallizations. Continuous crystallization is a relatively new field in pharmaceutical sciences and engineering. Utilization of steady state operation, combined with a depth of process understanding, enables crystallization to become a science rather than an art. Process development strategies and their results are presented for four unique active pharmaceutical ingredients in this dissertation. Development and optimization of a two-stage continuous mixed suspension mixed product removal (MSMPR) of ciprofloxacin HCl was carried out on the Pharmacy on Demand platform, meeting ICH Q3A guidelines for individual impurities. A successful and accurate predictive model of one impurity in the ciprofloxacin system was developed and used to control the impurity’s removal by adjusting the operating temperature of stage one. On a batch crystallization platform, API isolation issues, such as oiling out, were solved by the careful manipulation of the impurity profile from two different synthetic routes of furosemide. In one of these routes, a novel isolation of the API yielded a new solid complex form of the molecule with furfurylamine, not previously reported in the literature. A unique batch cold-temperature crystallization of propofol was conducted in an effort to replace the classical method of isolation: fractional distillation. The new crystallization was adequate in purging impurities at a level greater than any distillation. In addition, novel solubility and kinetic assessments of a high-concentration crystallization of propofol was made in order to model and understand the new system. A continuous cooling crystallization of acetaminophen in a binary solvent mixture was used to train and test a machine learning algorithm. The test results were compared against classical population balance modeling predictions, and found to be more accurate while requiring less theoretical and mathematical understanding from the user. Lastly, the culmination of this body of work was captured in a “user-manual” on proper lab techniques and process development strategies to build a batch or continuous crystallization from scratch in order streamline the workflow for future scientists in the M4All family at VCU.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
4-4-2024