The intensive livestock production is facing to great sanitary and regulatory challenges that could jeopardize is development as a productive system.
Among other, it could be mentioned the ban of antibiotics as growth promoters, the strict regulation related with Veterinary Medicinal Products residues in food and the worrying increase of microbial resistance to antibiotics used to treat several pathologies, some of them zoonotic diseases. This negatively affects animal welfare and causes heavy losses in the production. Under these circumstances probiotics can be an advantageous alternative in livestock production, as far as it has not the main inconveniences of traditional therapeutic, provided that they meet a series of prerequisites for its commercial implementation:
The research developed by PROBISEARCH using modern technologies “-omics”, among which include genomics, transcriptomics, proteomics and metabolomics, makes possible the isolation, identification and the development of strains of microorganisms, especially appropriate to control certain pathological processes in different animal species, whether animal production as pets. Preliminary studies carried out on humans and different animal species have allowed to verify the advantages of this systematic selection to other traditional methods.
Prevention and treatment of various infectious diseases that affect various mucous membranes (mastitis, metritis, génito-urinary and reproductive tract disorders) and some digestive disorders would be targets for the prevention and treatment with probiotics.
This approach is also very promising in animal species or pathological processes whose therapeutic possibilities are very limited, as it is the case of salmonella in poultry and pigs or preventing various infections in fish farming.
PROBISEARCH carries out a detailed study of the process that is intended to mitigate, combat or improve, selects candidates strains and assesses their safety, efficacy and commercial viability, ensuring total confidentiality of the collected data.