Zidar, Mitja, Cucuzza, Stefano, Boncina, Matjaz and Kuzman, Drago (2025) Noncomplex stability predictions for complex biotherapeutics: advanced kinetic modeling simplified. Scientific reports.

Abstract

In this article, the focus will primarily be on the critical long-term predictions of aggregates for different protein modalities. It will be demonstrated that this concentration-dependent quality attribute can be effectively modelled using a first-order kinetic model. This model characterizes the stability profiles of quality attributes through exponential functions, providing robustness and high precision in stability predictions. The use of a first-order kinetic model emphasizes the vital role of temperature selection in stability studies. By carefully choosing the appropriate temperature conditions, it becomes possible to identify the dominant degradation process and accurately describe it using a simple first-order kinetic model. This approach helps to prevent the activation of additional degradation mechanisms that are not relevant for storage conditions, allowing for the design of a study focused on a single mechanism. The simplicity of the kinetic model obtained from this approach reduces the number of parameters that need to be fitted and minimizes the number of samples that need to be measured. This enhances the robustness and reliability of predictions. Furthermore, by utilizing proper temperature conditions, the majority of quality attributes in biologics, including aggregation, can be successfully modelled using a first-order kinetic framework. This highlights the crucial importance of temperature selection in studying the stability and degradation of biologics.

Item Type:	Article
Date Deposited:	16 Jul 2025 00:45
Last Modified:	16 Jul 2025 00:45
URI:	https://oak.novartis.com/id/eprint/55476