The CERCA Institution has awarded the 2025 Pioner Awards, which recognize recent doctoral theses with the greatest potential to transform scientific knowledge into solutions useful for society and the market. Among the award-winning projects is the doctoral thesis of Dr. Carles Rubio Maturana, a postdoctoral researcher in the Microbiology group at the Vall d’Hebron Research Institute (VHIR).

Dr. Rubio completed his thesis under the supervision of Dr. Joan Joseph Munné, a researcher in the Microbiology group at VHIR, and Dr. Elisa Sayrol Clols, from the Universitat Politècnica de Catalunya. The thesis was carried out within the VHIR Microbiology group, at the International Health Section of the Microbiology Service of Vall d’Hebron Hospital, and at the Drassanes Vall d’Hebron Centre for Communicable Diseases, in collaboration with the Universitat Politècnica de Catalunya (Computational Biology and Complex Systems Group, BIOCOM-SC). The project was co-funded by the Probitas Foundation and the UPC Centre for Development Cooperation.

Dr. Rubio’s project focused on the design and development of an automated, low-cost system for the diagnosis of malaria and urogenital schistosomiasis, two infectious diseases with high prevalence in tropical and subtropical regions and a significant impact in countries of the Global South. The system combines artificial intelligence, digital image analysis, and a conventional optical microscope robotized using 3D-printed components.

The solution enables automated sample screening, microscopic image acquisition, and real-time analysis using convolutional neural networks. Images are captured using a mobile device, which guides the movements of the microscope and runs the artificial intelligence algorithms, subsequently facilitating validation of the results by laboratory professionals.

“The main goal of the project was to develop an accessible diagnostic tool designed to operate in laboratories with limited resources without compromising rigor or diagnostic quality,” explains Dr. Carles Rubio. “The combination of conventional microscopy, artificial intelligence, and low-cost technologies makes it possible to reduce analysis time and support healthcare professionals, especially in areas where these diseases continue to have a very high impact.”

The artificial intelligence models developed have demonstrated high diagnostic performance both for detecting Plasmodium parasites in blood samples and for identifying Schistosoma haematobium eggs in urine samples. The system has achieved levels of accuracy and sensitivity comparable to conventional microscopy, with the added advantage of reduced analysis time and greater standardization of the technique.

The system has been validated in the Microbiology Laboratory of Vall d’Hebron University Hospital and at the Drassanes Centre for Communicable Diseases and International Health, as well as at the Nossa Senhora da Paz Hospital in Cubal, Angola, located in an area with high endemicity for both diseases and with which the hospital has collaborated for more than 10 years.

The developed solution is adaptable to most conventional optical microscopes, does not require an internet connection, and is designed to be implemented without major financial investment. The 3D models and part of the technological development have been published in open access, and the labeled digital image database is available so that other research groups can train and improve new artificial intelligence models.

Beyond its diagnostic use, the technology developed may also have applications in the training of microscopists, quality control of staining procedures, and the strengthening of laboratory information systems in low-resource settings.