Noel Co., Ltd. (CEO Chan-Yang Lim, hereinafter referred to as "Noel"), an AI medical device development company, announced on the 25th that it has signed a contract to supply miLab™ MAL, an AI-based malaria diagnostic solution, to Ghana, West Africa. The contract is worth a total of $975,000 (approximately 1.36 billion won) over the next two years, and the product will be supplied in stages to major local health institutions and malaria management centers.
This contract was concluded based on existing supply experience and performance evaluations in West African markets, including Benin, Nigeria, Côte d'Ivoire, and Angola. Noel plans to support product supply and operations through local partners.
Noel's miLab MAL is a digital microscope-based diagnostic solution utilizing AI technology. In a joint study with Labcorp, a US diagnostics company, it achieved 100% sensitivity, specificity, and positive/negative predictive values. Furthermore, its technological prowess was recognized in a report by UNITAID, a WHO affiliate, where it was described as "the most advanced digital microscope platform integrating all the functions of a microscopic diagnostic system."
Noel is attracting attention for its technological innovation and growth potential in the global public health field, including being the only medical AI company invited to the Gates Foundation Chairman's recent meeting in Korea.
CEO Lim Chan-yang stated, “West Africa is a key region accounting for approximately one-third of the world’s malaria cases, and demand is steadily increasing through public procurement and cooperative projects.” He added, “Based on this supply, we plan to strengthen our position in the African market and accelerate our entry into the European and North American markets.”
Meanwhile, according to the WHO's 2024 Global Malaria Report, Ghana, with a population of approximately 34 million, is projected to see approximately 6.55 million malaria cases and 11,000 deaths in 2023. Existing local diagnostic methods primarily rely on microscopic examinations and rapid antigen tests (RDTs), but these have been criticized for limitations such as a lack of skilled personnel and low sensitivity.
Noel's miLab MAL is evaluated as a solution that can simultaneously improve the accuracy and efficiency of field-based malaria diagnosis by handling the entire process, from sample preprocessing to high-definition image capture, AI analysis, and result confirmation, in a single device.
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