Fitting bevacizumab aggregation kinetic data with the Finke–Watzky two-step model: Effect of thermal and mechanical stress

Abstract

Size exclusion chromatography with light scattering detection (SEC-MALLS) was assessed as a means to characterize the type of bevacizumab aggregates that form under mechanical and thermal stress, quantitatively monitoring the aggregation kinetics. The analytical method was monitored and verified during routine use at two levels: (1) the “pre-study” validation shows that the method is specific, linear, accurate, precise, robust and stability indicating; (2) the “in-study” validation was verified by inserting quality control samples and the use of control charts, indicating that the analytical method is in statistical control and stable.The aggregation kinetics data were interpreted using a modified Lumry–Eyring model, but the quality of the fit can be considered poor (R2>0.96), especially at higher temperatures. This indicates that the order of the reaction could not be reliably determined, suggesting a different degradation mechanism. The kinetic data set also fit the minimalistic Finke–Watzky (F–W) 2-step model, with an excellent quality of fit (R2>0.99), yielding the first quantitative rate constant for the steps of nucleation and growth in bevacizumab aggregation. The bevacizumab pharmaceutical preparation contains (initially) dimers, approximately 1.6% of bevacizumab total concentration, and the effect on aggregation kinetics of seeding was analyzed using the F–W 2-step model assuming [B]0≠0 (for the seeded case). The results suggested that the seeding had no impact on aggregation kinetics. Furthermore, the Arrhenius equation cannot be used to extrapolate the shelf-life since no linear temperature dependence of the rate constant was found within the temperature range. Although the real-time stability data provides the basis for determining the product shelf-life, predictive methodologies such as Vogel–Tammann–Fulcher (VFT) or the Arrhenius approach can be misleading and result in overestimates of the product shelf-life. However, they can be successfully applied to fixing the lower and upper limits of the aggregation rate, i.e. the best and worst-case scenarios regarding the aggregation potential of the product.In conclusion, the present study evaluates the first application of the F–W 2-step model to fitting and interpretation of experimental aggregation data for bevacizumab pharmaceutical preparations, using SEC-MALLS in this context.