Fundamentals of peptide adsorption in reversed-phase liquid chromatography
File(s)
Author(s)
Mercado Valenzo, Oscar
Type
Thesis
Abstract
This Thesis investigates the fundamentals of peptide adsorption in reversed-phase liquid chromatography (RPLC), focusing on improving peptide purification strategies, which are crucial for research and industrial applications. Peptides, short chains of amino acids, are increasingly significant in pharmaceutical research and drug development due to their therapeutic potential. The main challenge in peptide purification is achieving high purity, which is essential for the efficacy and safety of peptide-based drugs.
The research explores the key parameters influencing peptide retention and separation in RPLC, including hydrophobicity, solvent composition, column characteristics, and mobile phase interactions. It also introduces the development of the SMART (Systematic Multi-parametric Adaptive Responsive and Tailored) algorithm, which optimises elution profiles to enhance separation efficiency, reduce solvent usage, and increase throughput. This algorithm was tested on various peptides, including glucagon, demonstrating its potential for analytical and industrial applications.
A comprehensive study of different RPLC column packing materials was conducted, with silica-based columns being the focus. The Thesis explores the limitations of current RPLC methods, particularly the difficulty in separating closely related peptide impurities. To address this, it proposes alternative column selection strategies and optimised elution conditions to improve the resolution of these impurities.
Overall, this Thesis contributes to advancing peptide purification techniques by improving theoretical understanding and offering practical methodologies. The results have direct implications for the pharmaceutical industry, where efficient, scalable, and sustainable purification processes are critical for producing high-purity peptide therapeutics. The research lays a foundation for future innovations, particularly in optimising chromatographic methods for more complex peptide systems and improving sustainability in large-scale manufacturing processes.
The research explores the key parameters influencing peptide retention and separation in RPLC, including hydrophobicity, solvent composition, column characteristics, and mobile phase interactions. It also introduces the development of the SMART (Systematic Multi-parametric Adaptive Responsive and Tailored) algorithm, which optimises elution profiles to enhance separation efficiency, reduce solvent usage, and increase throughput. This algorithm was tested on various peptides, including glucagon, demonstrating its potential for analytical and industrial applications.
A comprehensive study of different RPLC column packing materials was conducted, with silica-based columns being the focus. The Thesis explores the limitations of current RPLC methods, particularly the difficulty in separating closely related peptide impurities. To address this, it proposes alternative column selection strategies and optimised elution conditions to improve the resolution of these impurities.
Overall, this Thesis contributes to advancing peptide purification techniques by improving theoretical understanding and offering practical methodologies. The results have direct implications for the pharmaceutical industry, where efficient, scalable, and sustainable purification processes are critical for producing high-purity peptide therapeutics. The research lays a foundation for future innovations, particularly in optimising chromatographic methods for more complex peptide systems and improving sustainability in large-scale manufacturing processes.
Version
Open Access
Date Issued
2024-10-26
Date Awarded
01/12/2024
License URL
Advisor
Williams, Daryl
Sponsor
Engineering and Physical Sciences Research Council
Grant Number
EP/T005556/1; EP/T518207/1
Publisher Department
Chemical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)