Accelerated Predictive Stability for Vaccines

1 . INTRODUCTION

The main challenge for the formulation of biologically derived products is to control the rate of degradation of their constituents to ensure an acceptable lifetime during storage and transport around the world [1-3]. The concept of stability of biological compounds (proteins, viruses, bacteria) is complex to understand, involving theoretically, concepts of both thermodynamics and advanced kinetics. one way of estimating protein stability is to study the denaturation when a protein is subjected to chemical stress (denaturing agents, pH) or physical stress (temperature, pressure…, etc.). The temperature to which a compound of biological origin is exposed is a key parameter that directly impacts its degradation rate and therefore its stability. owing to their sensitivity to temperature, many vaccines are stored in refrigerated conditions (between +2°C and +8°C). Their exposure to higher temperatures may cause a more or less rapid alteration of their key properties (antigenicity, infectious titer, structure, oligomeric state, etc.). Thus, there are some obvious questions: At what temperature should a biological be stored? How long can it be kept in unrefrigerated conditions? At what rate does this product degrade depending on the temperature to which it is exposed? What is the impact of one or more temperature excursions during storage or transport (breaking of the «cold chain») on the quality of the product?

To answer these questions, we propose that kinetic modeling tools be used. A kinetic model identifies the rate of degradation of a product as a function of time and temperature. The kinetic parameters that make up this model are derived from the Arrhenius equation and are mainly the frequency factor (A), the activation energy (E) and the order (n) of the reaction. Knowing the kinetic parameters of various reactions operating within a product makes it possible to translate, on a continuous basis, the temperature fluctuations it undergoes (i.e. its «thermal history») into the level of degradation. Using this theoretical basis, we have endeavoured, on the one hand, to propose «good modeling practices » for biologicals and, on the other hand, we have tested the capacity of these models to predict in real time the level of degradation of vaccines during storage and transport.