The new Zetasizer Helix from Malvern Instruments enables the detailed study of mechanisms of protein aggregation and is a powerful tool for early stage biopharmaceutical development.
This new system combines industry-leading Zetasizer dynamic light scattering (DLS) technology, for sizing of proteins and other biomolecules, with Raman spectroscopy. Raman spectroscopy enables monitoring of the changes in secondary and tertiary protein structure.
The combination of DLS and Raman spectroscopy allows measurement of protein size and structure from a single small volume sample, providing unique insight into protein folding, unfolding, aggregation, agglomeration and oligomerization. Such detailed information supports both the effective application of Quality by Design and the efficient development of biosimilars.
Raman spectroscopy delivers information on protein unfolding by monitoring the variations in molecular vibrations that result from changes in secondary and tertiary protein structure. The combination of dynamic light scattering with Raman spectroscopy characterizes a wealth of chemical, structural, and physical parameters of biotherapeutic proteins under formulation conditions, at high concentrations up to 100mg/ml and using a wide range of buffers and excipients.
Parameters measured include: secondary and tertiary protein structure; melting temperature; onset temperature of aggregation; and transition enthalpy values; as well as aggregation propensity and protein solubility.
The Zetasizer Helix is the latest commercialised product to emerge from Malvern’s Bioscience Development Initiative (BDI), a collaborative research program dedicated to providing solutions to the evolving needs of the biopharmaceutical industry. A key priority for the industry is obtaining a greater understanding and control over the formulation process, a need exacerbated by the increasing adoption of QbD.
By allowing users to fully scope protein behavior within a formulation the Zetasizer Helix provides insight at the molecular level as to which variables trigger, for example, oligomerization and aggregation, supporting a QbD approach.