Algorithm-Based Liquid Formulation Development Including a DoE Concept Predicts Long-Term Viral Vector Stability

Abstract

Specifically tailored amino acid-based formulations were previously shown to have a high potential to avoid stress-mediated degradation of complex molecules such as monoclonal antibodies and viral vectors. By using adenovirus 5 (Ad5) as a model, we studied whether such formulations may also efficiently protect viral vectors in thermal stress experiments and during long-term liquid storage. Algorithm-based amino acid preselection using an excipient database and subsequent application of design of experiments (DoE) in combination with a 37°C challenging model enabled the prediction of long-term storage stability of Ad5. By statistical analysis of the Ad5 infectivity, amino acids with significant influence on Ad5 stability were detected after 2 and 3 weeks of liquid storage at 37°C. Ad5 formulations comprising positively selected amino acids did not reveal any loss of infectivity after 24 months in liquid storage at 5°C. By contrast, a 2 log reduction after 3 months and complete loss of infectivity after 18 months was observed with a standard viral vector formulation. By an optimization round, we designed a simple and well-balanced formulation avoiding MgCl₂, previously considered essential in Ad5 formulations. This work demonstrates the efficacy of an algorithm-based development approach in the formulation development for viral vectors.

Keywords: adenoviral vectors; design of experiments; excipient(s); formulation(s); gene delivery; stabilization; vaccine(s); viral vector(s).