Introduction

The method described in this patent can predict the efficacy of vaccines against avian infectious bronchitis virus (IBV), without the use of experimental infections.  IBV is an important disease in clinical and economic terms since it causes respiratory and reproductive symptomatology, loss of performance and mortality.

Technical features

Currently the control of avian infectious bronchitis virus (IBV) in poultry farming is based on the use of attenuated vaccines. Cross protection is often insufficient because of the great variability of this virus and the continuous onset of new virus strains, often due to intense live animal commercialization: vaccines must be accurately chosen and kept up to date according to the local scenario.  The only method available to date to predict cross protection between strains are experimental infections, but they are costly and ethically questionable. This patent identifies and compares the physico-chemical properties of immunogenic proteins through a machine learning algorithm, that identifies the virus strain most suitable for the local context.

Possible Applications

• Poultry farming animal pathogen control;
• May be used by veterinarians, research institutes and pharmaceutical companies;
• Applicable to human pathogens.

Advantages

• Early selection of the most effective vaccine reduces costs due to animal morbidity;
• Can be validated for use on human pathogens.