Antimicrobial resistance (AMR) is a concerning global threat. It arises when bacteria, viruses, fungi, and parasites evolve mechanisms to withstand the effects of antimicrobial drugs, rendering treatments less effective. This not only complicates the management of infections but also significantly increases the risk of severe disease, transmission, and mortality.

In this context, the END-RAM project is articulated in two fundamental axes. Firstly, it seeks to improve the advanced diagnosis of antimicrobial resistance through the development of an innovative LFIA (Lateral Flow Immunoassay) and a predictive tool based on artificial intelligence with application in massive sequencing techniques. Secondly, it is committed to advancing next-generation therapies, including cell-targeted nucleic acid treatments and immunotherapy, to combat the most dangerous antimicrobial-resistant bacteria threatening public health.

The project is funded by the Centre for Technological Development and Innovation (CDTI) and the Spanish State Research Agency (AEI) under the TransMisiones 2024 call for proposals. The initiative aims to develop new tools to improve the diagnosis and treatment of infections caused by antimicrobial-resistant bacteria.