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iPAT project

Platform Based on Genomics, Bioinformatics, and Artificial Intelligence to Study Pathogens Isolated in Clinical Settings.

Coordinator
Dr. Jose Arturo Molina Mora, Centro de Investigación en Enfermedades Tropicales & Facultad de Microbiología, Universidad de Costa Rica (UCR)

Core Team

Description
Infectious diseases continue to pose a significant public health challenge, driven by various pathogenic agents. Epidemiological surveillance benefits from the use of molecular tools and high-throughput data analysis technologies—such as DNA sequencing, bioinformatics, and artificial intelligence—which help identify patterns of transmission, clinical presentation, and epidemiological trends. In Costa Rica, there is a clear need to expand systematic studies that integrate these approaches to investigate pathogens in specific contexts. The project “iPAT” evaluates a proof of concept for a platform that combines genomics, bioinformatics, and artificial intelligence to support and enhance pathogen surveillance, using two main models. The first line is related to the circulation of multidrug-resistant bacteria, including carbapenem-resistant strains, in hospitals. The second model is based on atypical mycobacterial infections in the Guanacaste region. While both infectious events are addressed by existing surveillance systems, this proposal introduces a novel, integrated approach. The project not only validates the platform but also contributes concrete improvements to epidemiological surveillance processes in the country.

Collaborators and publications