Research from Maranhão wins national innovation award in biomedical engineering for the SUS

The award ceremony will be held in December, in Brasília. Promoted by the Brazilian Society of Biomedical Engineering (SBEB), with support from the Ministries of Health and Science, Technology and Innovation (MCTI), the award recognizes biomedical engineering initiatives with the potential to contribute to the SUS and generate positive impacts on the lives of the population.

Entitled "Computational Epidemiological Surveillance for the SUS: a platform for the rational design of RNA biosensors", the research proposes a computational platform to design biosensors capable of identifying genetic material from infectious agents.

The technology has already been computationally validated for the dengue and zika viruses. According to the research, the platform showed more than three times greater thermodynamic discrimination between the true target and the analyzed controls.

The proposal is to use the technology in environmental epidemiological surveillance, with analysis of water and sewage samples. This way, it would be possible to screen different pathogens without having to redevelop the entire technology for each agent investigated.

As it is a fully digital solution developed in Brazil, the platform also seeks to reduce dependence on foreign technologies in the area of ​​molecular diagnostics. The strategy can facilitate the adoption of the tool by public health laboratories with fewer resources available.

Currently, according to the researcher, the development of molecular tests for the surveillance of arboviruses still depends, to a large extent, on experimental processes based on trial and error.

For the Unified Health System, especially in regions with less laboratory infrastructure, the time needed to develop these tests can limit the ability to respond to threats to public health.

“This step can be expensive and time-consuming, meaning it takes months between the identification of a new pathogen and the availability of a reliable screening test”, warns the researcher.

To face this challenge, the solution developed by G.E.A.F. Biotechnology and Innovation in RNA uses a computational platform capable of designing RNA biosensors in a deterministic way.

Based on the genetic sequence of the agent to be identified, the system predicts a structure with greater specificity and stability, reducing the need for an experimental selection stage.

In Maranhão, the research was covered by the Deep Tech Catalyst notice, from the Maranhão Research and Scientific and Technological Development Support Foundation (Fapema).

The call allocated R$4.55 million to support up to 15 proposals in the areas of digital agriculture, biotechnology and bioeconomy, renewable energy and sustainability, health and social technologies.