Cohort One — Now Building

Fighting Malaria
Together.

30 biomedical scientists. One mission. We're building an AI-powered malaria detection system using smartphone technology — designed for Africa, by Africans.

42%
Don't get tested early
70%
Higher mortality risk on delay
1 in 3
Cases go undetected
About BMLSIA

Nigeria's First Lab Science Innovation Academy

BMLSIA was built on one conviction: biomedical laboratory scientists are more than testers — they are innovators. Our first cohort of 30 fellows, selected from 140+ applicants across Africa, is collaborating across 11 roles to build MPDetect from the ground up.

AI-Powered Detection

ML models trained on blood smear images to identify malaria parasites — built by biomedical scientists who understand the biology.

Smartphone-Based

Designed to work with phone cameras and low-cost hardware, reaching community health workers far from centralized labs.

Lab Science Foundation

Unlike generic tech products, MPDetect is built by BLS professionals who understand smear preparation, staining, and parasite morphology.

Surveillance Integration

Every diagnosis is a data point. Results feed into real-time dashboards to support outbreak detection and program monitoring at scale.

Our Mission

To make early malaria diagnosis faster, smarter, and more accessible to every community — using innovative technology to enable timely treatment and significantly reduce preventable deaths.

The Crisis

Every Two Minutes,
A Child Dies From Malaria

This isn't a treatment problem alone. It's a detection problem. Getting accurate, timely diagnosis to communities that need it most is the gap we are building to close.

627K+
Annual deaths
Majority are children under 5
95%
Deaths in Africa
Where infrastructure is most limited
70%
Higher mortality risk
When diagnosis is delayed 48+ hrs
1 in 3
Cases missed
Due to testing gaps in remote settings

Traditional Microscopy

  • ×30–45 min per read
  • ×Requires trained microscopist
  • ×No automatic data capture
  • ×Fails in low-resource settings

What MPDetect Targets

  • AI-assisted reads via smartphone
  • Operable by community health workers
  • Auto result logging & geo-tagging
  • Built for low-resource LMIC settings
Our Approach

How MPDetect Works

A four-stage pipeline — from blood smear capture to national surveillance — built for settings where traditional lab infrastructure doesn't exist.

01In Development

Capture

A health worker or lab scientist captures a prepared blood smear image using the MPDetect app on a standard smartphone.

02In Development

Analyze

An ML model processes the image to identify and count malaria parasites, detect species, and estimate parasite density.

03Planned

Report

Results are displayed on-screen within seconds, logged with timestamp, GPS location, and patient ID to a surveillance dashboard.

04Planned

Aggregate

Anonymized data flows into a central system, building real-time outbreak maps and population-level insights at scale.

Get Involved

Join The Movement

There are multiple ways to contribute — whether you have expertise, infrastructure, or simply believe that African scientists can solve African health problems.

Mentor & Train

Guide the next generation of biomedical innovators. Share your expertise across science, tech, and product.

Become a Mentor

Partner With Us

Collaborate to pilot the MPDetect system in clinics and communities. We're actively seeking lab partners for early evaluation.

Start a Partnership

Support Our Work

Fund the development and rollout of life-saving diagnostic tools to communities that need them most.

Donate
The Team

30 Fellows. 11 Roles.
One Shared Mission.

Selected from 140+ applicants across Nigeria and Africa, Cohort One brings together biomedical scientists, engineers, writers, and designers — all committed to proving that lab scientists can be builders too.

AI/ML EngineeringFrontend DevelopmentBackend DevelopmentProduct ManagementBiomedical ScienceResearch & Science CommunicationMedical Writing & StorytellingGraphic DesignContent CreationUI/UX DesignData Science
30+
Team Members
11
Innovation Roles
140+
Applications Received
5+
Nigerian Universities
Meet the full cohort at bmlsia.org