Benin enlists Korean-developed AI in nationwide battle against malaria
Summary
Noul said its Korean-developed AI malaria diagnostic system has entered Benin’s national malaria program after winning a public procurement contract from the health ministry. The company said the miLab MAL platform will start with 20 units for major hospitals treating severe malaria and expand across the public health system. Noul also said the device was backed by a 2025 clinical evaluation in Benin and was officially recommended by Benin’s PNLP as a point-of-care tool.
Key Facts
- The Benin study involved 211 children suspected of having severe malaria at major university hospitals in southern and northern Benin.
- miLab MAL recorded sensitivity of 98.82 percent and specificity of 100 percent in the Benin evaluation, according to Noul.
- The system reduced diagnostic time to less than 20 minutes, compared with an average of 75 minutes for manual microscopy.
- Benin’s PNLP recommended miLab MAL as a point-of-care device for malaria control programs in African countries based on the study’s final report.
Noul’s miLab MAL uses artificial intelligtence-based analysis to automate malaria diagnosis from blood smears to digital imaging. Courtesy of Noul
An artificial intelligence (AI)-powered malaria diagnostic system developed in Korea is moving from individual hospitals into Benin’s national malaria program after winning a public procurement contract from the country’s health ministry.
Noul, an AI diagnostic startup that uses digital microscopy to analyze blood samples, said Monday that its miLab MAL platform was selected through a public tender to supply major hospitals treating severe malaria cases, with an initial order of 20 units and plans to expand its use across Benin’s public health system.
The platform has been incorporated into Benin’s National Malaria Control Program (PNLP) as a point-of-care diagnostic tool, according to Noul.
The company said a clinical evaluation conducted in Benin in 2025 provided key evidence supporting its adoption.
The study involved 211 children suspected of having severe malaria at major university hospitals in southern and northern Benin.
Compared with manual microscopy, miLab MAL recorded sensitivity of 98.82 percent and specificity of 100 percent, according to Noul.
The system also reduced diagnostic time to less than 20 minutes, compared with an average of 75 minutes for manual microscopy, the company said.
Based on the study’s final report, Benin’s PNLP officially recommended miLab MAL as a point-of-care device for malaria control programs in African countries, Noul said.
Noul said the adoption demonstrated that the company’s AI technology could help overcome limitations in frontline diagnosis and serve as part of a national health system.
It also said Benin is among West African countries with a high malaria burden, citing World Health Organization estimates of about 5.1 million malaria cases and 9,900 deaths in 2024.
The company said its system automates the diagnostic process from blood-smear preparation through digital imaging and AI analysis, enabling faster and more standardized testing in settings with limited medical infrastructure and trained personnel.
With Africa accounting for about 95 percent of the global malaria burden, Noul said it plans to expand partnerships with medical institutions and public health programs in high-burden regions.
This article was published with the assistance of generative AI and edited by The Korea Times.
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