We’re proud to share that MultiplexAI has been selected as one of El País’ 10 good news stories of 2025—a recognition that highlights the power of science, partnerships, and practical innovation to improve lives.
Turning Conventional Microscopes into AI-Powered Diagnostic Tools
MultiplexAI is a groundbreaking initiative bringing together nine leading institutions across Africa and Europe to develop an AI mobile diagnostic “copilot” capable of detecting every disease visible on a microscopy slide.
In many settings, microscopy-based diagnosis still depends on the trained eye of highly qualified specialists—experts who are often scarce. MultiplexAI aims to help close that gap by transforming conventional microscopes into smart devices, enabling faster and more consistent detection in seconds, and at a fraction of the cost.
MultiplexAI is coordinated by the Barcelona Institute for Global Health (ISGlobal) and powered by SpotLab’s AI technology. The consortium partners include:
- Barcelona Institute for Global Health (ISGlobal) (Spain)
- SpotLab (Spain)
- Ahmadu Bello University, Zaria (Nigeria)
- CISM – Centro de Investigação em Saúde de Manhiça (Mozambique)
- Université Félix Houphouët-Boigny (Ivory Coast)
- Jimma University (Ethiopia)
- IRCCS Ospedale Sacro Cuore Don Calabria (Italy)
- Instituto de Salud Carlos III (Spain)
- Hutzpa Innovations (Nigeria)
MultiplexAI is a 3.5-year, €5 million project supported under the European & Developing Countries Clinical Trials Partnership (Global Health EDCTP3)—a major program advancing global health innovation through international collaboration.
El País’ Planeta Futuro feature is a refreshing and hopeful read, alongside other stories such as a potential new drug that could transform the fight against HIV, the rescue of Sudan’s seed heritage, and the launch of the African Space Agency. You can read the full article here (in Spanish):
In 2026, our focus is clear: scale what works, share what we learn, and widen access to better diagnostics—so that more health systems can benefit from fast, reliable microscopy-based detection.