Willem: “Last year 430.000 people died because of Malaria. With fast quality diagnostics and prompt treatment, this number could be a lot lower. The quality and availability of these diagnoses are one of the core issues. MOMALA offers a scalable high-quality solution through a smartphone application. The app uses A.I. to automatically detect parasites in microscopic images of thick blood smears. MOMALA brings a solid business model to low resource environments, creating impact in a sustainable way.”
MOMALA is a smartphone application that's going to deliver high-quality Malaria diagnostics in low resource environments. Affordable with big impact.
What problem are you trying to solve? Malaria is still a huge problem in many parts of the world. In 2016 there were 212 million cases of Malaria and 430.000 deaths. One of the core issues is the availability and quality of diagnostics. Microscopy is still the golden standard in the Malaria diagnostic market but is not scalable due to lack of trained staff. The quality and time of a diagnosis can vary a lot with every expert. This is especially a problem in the low resource environments. Rapid diagnostic tests(RDTs) are a substitute for microscopy if that is not possible. RDTs are disposable tests that can only diagnose one species of Malaria. There are a few drawbacks with RDTs. The quality of the different brands varies a lot. They also need to be transported and often stored at specific temperatures, which is difficult in most areas in Africa. The diagnosis of an RDT takes around 25 minutes. There are many more problems, but these are the core issues in the diagnostic field of Malaria.
Describe your solution to this problem: MOMALA offers a solution: Automated diagnoses of Malaria. The MOMALA-app is a smartphone application that is able to detect Malaria parasites in a microscopic image of a blood smear. By attaching the phone’s camera to the microscope’s ocular, the app can automatically make pictures of a thick blood smear and analyze it. The algorithm features a convolutional neural network that has been trained to classify white blood cells, and the three most prevalent plasmodium parasites in Kenya: P. falciparum, P. ovale and P. malariae. By moving the slide around, the app will analyze multiple fields until it has enough data to give a reliable quantitative diagnosis following WHO guidelines. The MOMALA-app is an In Vitro Device meant for professional use by laboratories and clinics, where it can help with speeding up the diagnostic process and improve the overall quality of healthcare system.
Why are you going to win The Spindle Award for Best Innovation?
MOMALA is a state of the art innovation that will have a great impact on the Malaria diagnostic situation in Africa. Our eHealth app will deliver quality and fast diagnoses. Through our scalable solution, more people can be diagnosed properly which will decrease the disease burden in Africa. Together with Amref Health Africa, we will be able to create a strong, reliable and sustainable brand that will focus on delivering quality diagnostics to the low resource environments in Africa.