Predictive Formulation Analytics delivers the sound basis to define the best formulation conditions and process parameters for each single purification step in DSP of recombinant proteins.
Knowledge on the behavior of a candidate protein (colloidal, thermodynamic, chemical and interface stability) in particular at high concentrations, as occurs during elution or at the concentration/diafiltration membrane, is a mandatory prerequisite for initiating a focused DSP development: The general evaluation and characterization of the protein´s basic physicochemical properties (basic profiling) within a DoE matrix using a high throughput dynamic light scattering (DLS) plate reader, composition gradient static light scattering (CG-MALS) and nanoDSC to identify potential stability issues or formulation challenges by applying these methods already at an early stage.
The information on how pH, ionic strength, buffer types and stabilizers affect the protein stability and solubility enables the design of an efficient DSP while avoiding pitfalls or bad surprises such as product loss through aggregation/precipitation or degradation. Clogging of membranes or chromatography columns can be circumvented.
Based on this knowledge the appropriate chromatographic steps can be selected, approved and optimized. This scientific DoE based approach is more expedient and less time consuming compared to the commonly applied trial and error approach.
Once the process design is established and verified at development scale, the process can easily be scaled up and transferred into GMP manufacture at significantly minimized risk.
In parallel, sufficient amounts of material can be generated from test runs to be used for further formulation development, e.g. forced degradation study, at an early stage.
The use of Predictive Formulation Analytics as a starting point of process development supports DSP- as well as formulation-development already from an early stage and ideally results in a common formulation for both API drug substance and drug product.