Rubens Lima do Monte Neto

Life Sciences

Biologist Rubens Neto earned his undergraduate degree at the Federal University of Paraíba and furthered his education with a master’s degree in pharmacology from the same institution. He pursued his doctorate in the same field at the Federal University of Minas Gerais. As a post-doc, Rubens contributed to the Infectious Diseases Research Center at the Laval University Hospital Center in Canada. A dynamic individual, Rubens balances his academic pursuits with his passion for photography and scuba diving, where he serves as an instructor. His interest in technology was sparked when he assembled his first 3D printer years ago, which eventually became a crucial part of his research project. Currently, Rubens is working on a device that aims to provide quick and efficient diagnosis for various diseases prevalent in Brazil, leveraging the power of 3D printing technology.

Projects

OmniBOX: An affordable, 3D-printed, smartphone-operated device for infectious disease diagnosis
Science / Engineering

The existing solutions for molecular diagnostics are not sufficiently accessible, rapid, or compatible to serve as a point-of-care alternative. This limitation hinders the development of strategies to control infectious diseases. Our project aims to address this issue by developing a device, named OmniBOX, for the molecular detection of arboviruses – including dengue, zika, and chikungunya – as well as Leishmania spp. and Schistosoma mansoni.

OmniBOX, aptly named for its portability and user-friendly interface, allows results to be read and interpreted by non-specialists. The device itself will detect and display the result, which can also be accessed via Bluetooth on a mobile application. Accurate disease diagnosis is crucial as it guides treatment, enhances the likelihood of early recovery, and is essential for case reporting that can inform public health interventions.

Amount invested

R$ 100,000.00

Open Calls

Chamada 1
  • Topics
  • arbovirus
  • Chikungunya
  • dengue
  • diagnóstico
  • Infectious disesase
  • Leishmaniasis
  • Molecular detection
  • OmniBOX
  • Zika