Advanced Peptide Synthesis Program Uses Predictive Modeling and Simulation Tools to Shorten Peptide Process Development
The field of Solid Phase Peptide Synthesis (SPPS) has boomed over the last few decades. But many companies are still relying on procedures used in the laboratory to achieve large-scale production. This has proven to be inefficient and not cost-effective. Not surprisingly, the overall quest to produce high-quality peptides at lower costs while meeting customers’ expectations for issues like cutting solvent consumption (and reducing environmental impact) without affecting the product quality has intensified.
Pharmaceutical manufacturers expect their CMDOs to deliver an efficient, yet robust and cost-optimized process for producing the final product. But a trial-and-error strategy that pushes the development of an optimal process later is not the most effective approach.
As part of an innovation program called “Advanced Peptide Synthesis,” the Polypeptide Group has developed a set of tools using Ypso-Proxima® software that helps its development chemists make the most efficient choices at an early stage. These tools include:
A chemist’s predictive toolbox
The structured database goes beyond basic information about molecular weight, hydrophobicity plot and the evolution of net charge with respect to pH. It aggregates information about peptide sequence edition, predictions of charges vs pH, mass spectra, conformation potential, solubility of peptides, impurity profile, and solvent consumption for downstream processes, which supports better selection of raw materials, and estimations of coupling times for given target peptide yield and purity. Confidence in the predictive results is increasing over time as more and more cases are fed to the database, including complex peptides with exotic motifs and exotic building blocks.
SPPS simulation tool
The simulation tool gives chemists answers to questions such as: what are the rate- determining steps within the set of reactions involved in a peptide synthesis, how to boost the reaction kinetics, and how to optimize the volume of solvent used? The simulation tools are based on results from measuring the evolution of a system over time and developing numerical models that are able to represent the reaction mechanisms.
Using these new in-silico development toolboxes, peptide chemists will be a step closer to being “right the first time” in their iterative development strategy.
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