Africa's HealthTech innovation academy for biomedical laboratory scientists. We train them to build AI-powered healthcare that reaches real patients, one cohort at a time.
Our fellows work inFrontend Development
BMLSIA is a next-generation innovation academy for biomedical laboratory science students and professionals. We are not a classroom. We are a build space where scientists learn to code, design, research and ship the healthcare technology Africa needs.
To empower biomedical laboratory scientists to become innovators, storytellers, educators and changemakers through science, technology and creative thinking.
A world where lab professionals are seen as tech-enabled problem-solvers shaping the future of healthcare in Africa and beyond, not just testers.
From the Fellows Programme to campus clubs and community outreaches, there is a place to start whether you are a first-year student or a practising scientist.
Our flagship programme. Fellows join multidisciplinary teams, build a real healthcare product and show it at a public Demo Day, backed by mentors, an alumni network and a route to funding.
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Student-led clubs on campuses across Africa, with weekly meetings, global webinars and a shared healthtech project.
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We run digitised community outreaches for partner organisations: registration, vitals, lab results and an impact report, all on OutEMReach.
Learn moreEach BMLSIA outreach is run on OutEMReach, so every patient is registered once and every result, volunteer and number ends up in an impact report instead of a lost paper file.
Partners include
Every BMLSIA product starts with a problem a lab scientist has seen first-hand. Cohort fellows design, code and ship them with mentors.
Run a whole outreach from a phone.
A mobile-first micro-EMR for community health outreaches. Patient registration, vitals, test results, volunteers and impact reports in one installable app.
Used at LAUTECH, UNILAG, Babcock and the University of Ibadan.
Visit OutEMReach
Find blood donors faster.
Donor management for hospitals and blood banks, with state and LGA filters and WhatsApp appeals that reach donors where they already are.
Our first paying customers found their donors through Pintra.
Visit Pintra
Practise the bench before you stand at it.
A virtual MLS lab where students stain, grade and test at realistic stations, earn XP and learn from their mistakes without wasting a reagent.
Stations for malaria Giemsa staining, ABO/Rh grouping and urinalysis.
Visit LabiQuest
Malaria diagnosis from a smartphone photo.
AI that reads blood smear images captured on a phone, built for community health workers in low-resource settings and by scientists who know what a good smear looks like.
In active development by 30 fellows across 11 disciplines.
Visit MPDetectEach cohort follows the same 16-week path, so every fellow knows what to expect and every team ships.
Open application. 140+ applications reviewed and 30 changemakers selected across 11 disciplines.
Teams form, roles are assigned, tools are set up (Notion, GitHub, Figma) and mentors are introduced.
Deep problem research: literature reviews, user interviews and competitive analysis, ending in a Problem Statement.
A full development sprint with every discipline contributing, plus bi-weekly mentor check-ins and milestone reviews.
Testing, iteration, documentation and whitepaper publication. All assets go to GitHub.
A public showcase, live and virtual, where teams present to judges, funders and healthcare leaders.
Abdul Bello
Graphic Design
Uni. of Ibadan
Abdullateef Abdullahi Akanbi
Biomedical Science
Usmanu Danfodiyo Uni.
Abuoma Ejikeme
Biomedical Science
Uni. of Ibadan
Blessing Chukwudi
Biomedical Science
Uni. of Nigeria, Nsukka
Blessing Chukwuma
AI/ML Engineering
Uni. of Nigeria, Nsukka
Bright Gabriel
Medical Writing & Storytelling
Uni. of Port-Harcourt
Charles Diovu
AI/ML Engineering
Enugu State Uni. of Science and Technology
Chidimma Ilonze
Medical Writing & Storytelling
Uni. of Nigeria, Nsukka
And 22 more fellows building across Africa and beyond.
Fellowship6 Oct 20264 min read
AI-powered malaria diagnosis could make parasite detection faster, more accurate, and accessible in low-resource settings, especially rural communities.
Fellowship5 Oct 20263 min read
AI and mobile microscopy could transform malaria detection by bridging traditional laboratory diagnosis with faster, smarter, and more accessible technology.
Fellowship5 Oct 20263 min read
Malaria kills hundreds of thousands yearly. This article explores how AI-powered microscopy can make parasite detection faster, easier, and more accurate.
Join as a student or professional, mentor the next cohort, or bring BMLSIA to your community for a smart outreach.
