MozBioMed.AI develops technological solutions to revolutionize health in Mozambique and Africa
Learn more about MozBioMed.AI and our mission to transform health in Africa
MozBioMed.AI is a British startup with Mozambican roots, based at The University of Manchester, dedicated to biomedical research and the development of innovative solutions in diagnostics and drug discovery/repurposing for neglected tropical diseases. With a strong focus on artificial intelligence (AI), MozBioMed.AI aims to transform public health in Mozambique by promoting cutting-edge science with real social impact.
Founded in 2023 by a team of passionate Mozambican scientists, healthcare professionals, and technology experts, MozBioMed.AI was born from the urgent need to harness the power of digital innovation to meet the unique healthcare challenges faced by Mozambican communities.
To popularize the use of artificial intelligence in Mozambique to combat neglected tropical diseases such as HIV/AIDS, tuberculosis, and malaria, with special attention to rural communities where access to diagnosis and treatment is still limited.
To build an African ecosystem of excellence in AI applied to healthcare, empowering local scientists and creating innovative solutions with the potential for national and global impact.
Mozambican specializing in AI and Pharmacy. Scientist at The University of Manchester.
(United Kingdom)
(Mozambique)
(Mozambique)
(Kenya)
(Brazil)
(Brazil)
(Brazil)
(United Kingdom)
(United Kingdom)
(Uganda)
Dr. Bélio Castro – Ministry of Health of Mozambique
Dr. Joel Choveque – Ministry of Health of Mozambique
Dr. Nildo Joaquim – Ministry of Health of Mozambique
MozBioMed.AI aims not only to develop innovative scientific solutions but also to create profound social impact. Our focus is on rural and low-resource communities in Mozambique, where neglected tropical diseases have devastating effects. We believe that education is the key to building a better future, which is why we are training the next generation of Mozambican scientists. In addition, our AI solutions will directly contribute to improving access to faster and more accurate treatments and diagnostics.
Our Specialties and Technical Expertise
We work on repurposing approved drugs, using AI to identify new therapies for diseases affecting the African population, such as HIV, tuberculosis, and malaria.
We use AI to develop predictive models and diagnostic tools aimed at improving the recognition and treatment of neglected tropical diseases in Mozambique and other parts of Africa.
We offer courses and training programs, including master's programs in Artificial Intelligence applied to Public Health, to empower healthcare, technology, and science professionals in Mozambique to use AI for improving the healthcare system and tackling local challenges.
We connect scientific research with solutions that directly impact communities, especially those most in need of accessible diagnostic and treatment options.
AI-Based Diagnostics
Objective: Development of an artificial intelligence application capable of detecting leprosy lesions in skin images, operating 100% offline — ideal for rural settings without internet access.
Objective: Creation of an AI-based tool for rapid malaria screening, designed for offline operation and optimized for populations with limited access to healthcare services.
Objective: Development of a portable device that uses infrared spectroscopy combined with artificial intelligence algorithms to enable rapid tuberculosis diagnosis directly at the point of care.
Objective: A project that leverages simple clinical and laboratory data, such as blood counts and rapid tests, combined with artificial intelligence, to provide fast and accurate diagnoses of dengue and malaria.
Drug Repurposing with Artificial Intelligence
Objective: Use of artificial intelligence integrated with experimental and clinical trials to identify new uses for drugs in the treatment of tuberculosis,
Objective: Predictive modeling with AI to accelerate drug repurposing against leishmaniasis, based on African data.
Objective: A project combining AI and experimental validation to find more effective treatments for schistosomiasis.
Objective: Artificial intelligence models and scientific validation to identify new therapeutic uses for existing drugs in the fight against HIV.
Objective: A project applying AI and clinical data to accelerate the development of therapeutic solutions for lymphatic filariasis.
Objective: A project focused on using artificial intelligence and multi-target drug design to develop innovative treatments against neglected tropical parasitic diseases (NTDs) such as malaria, schistosomiasis, filariasis, leishmaniasis, and cysticercosis.
Objective: A project that uses AI to identify and optimize therapies targeting multiple biological pathways simultaneously, aiming for more effective treatments for viral diseases.
Our scientific production and available tools
This innovative AI tool uses low-cost infrared spectroscopy to diagnose leprosy and monitor treatment outcomes with up to 100% accuracy. With its ability to distinguish between healthy individuals and patients at different stages of treatment, this breakthrough technology promises to improve healthcare in low-resource settings worldwide.
This innovative AI tool, powered by Fourier-transform mid-infrared spectroscopy (FTIR-MIR), accurately screens diabetes and dyslipidemia with over 90% accuracy. By analyzing serum samples, it offers a rapid, non-invasive, and affordable diagnostic method for these critical cardiovascular risk factors.
In 2023, 38.8 million people were living with HIV. This groundbreaking study used QSAR-based machine learning, molecular docking, and dynamics simulations to uncover 124 new anti-HIV drug candidates from a screening of 37 billion compounds. Leveraging CHEMBL and ZINC-22 databases, advanced models predicted bioactivity and validated results, opening exciting new possibilities for HIV treatment.
This pioneering study, recognized by the WHO, is one of the first to identify ferritin as a crucial prognostic and therapeutic biomarker for COVID-19. Using AI, it predicts COVID-19 diagnosis and severity with over 90% accuracy, offering new insights for early intervention.
In development: an AI-driven cervical cancer screening system that integrates with malaria test slides. As lab technicians examine malaria slides, a smartphone camera captures images, and AI detects cervical cancer signatures. This technology enables large-scale screening, empowering general practitioners, especially in rural areas, to diagnose and treat cervical cancer, addressing the shortage of oncologists in countries like Mozambique.
In development: an AI tool for early cervical cancer diagnosis using liquid biopsy. By analyzing photographs of female urine samples with specific staining, it detects early cancer signs with high accuracy. This technology aims to revolutionize cervical cancer screening in Mozambique and Africa, making it more accessible and affordable, especially in underserved regions where oncologists are scarce.
Practical guides for using AI in biomedical research, with a focus on African contexts.
We work together with leading institutions
We are open to collaborations, partnerships, and new ideas