Vaccine formulations are complex and are even more complex with the addition of non-aluminum adjuvants in formulations – both commercially and in early phase development. Reversed-phase liquid chromatography (RPLC) is among the most important tests in the (bio)pharmaceutical industry for release and stability indicating measurements including adjuvant content and purity profile. However, the time constraints of developing “on-demand” robust quantitative methods prior to each change in formulation can easily lead to sample analysis becoming a bottleneck in vaccine discovery and development. In this session, we describe a digitally enabled generic analytical framework for non-aluminum vaccine adjuvants. A dynamic RPLC database was built from In Silico simulations of adjuvant components and was able to model and produce analytical methods that are suitable in both the development and QC space. This work is a valuable contribution to the growing role of digitalization to sustainably develop and deploy new analytical assays across academic and industrial sectors.
Learning Objectives:
1. Upon completion, participants will be able to understand current bottlenecks in analytical RPLC development for adjuvant components in varying complex vaccine formulations.
2. Upon completion, participants will be able to understand how In Silico modeling tools can be applied to vaccine analytical development for numerous non-aluminum adjuvant components in complex formulations.
3. Upon completion, participants will be able to understand how digitally enabled analytical workflows were reinforced by experimental and pre-qualification results on commercially available adjuvants that are suitable for QC laboratories.
4. Upon completion, participants will be able to discuss and explore how digitally enable analytical workflows can be utilized outside of adjuvant workstreams in the (bio)pharmaceutical industry.
