Projects / Top Talent Project

Eradicating Malaria with Ethnopharmacology and Artificial Intelligence

Project Kickoff: May 22


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This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

You can find our upcoming AI Innovation Challenges at https://omdena.com/projects

The problem

Malaria continues to be a severe public health issue globally, particularly in regions with limited resources and access to effective healthcare. The disease is caused by Plasmodium parasites transmitted to humans through the bites of infected Anopheles mosquitoes. Despite considerable efforts and some progress in malaria control, the disease’s persistence, a resurgence in some areas, and the emergence of resistance to existing antimalarial drugs and mosquito control methods pose significant challenges. These challenges hinder the global fight against malaria, necessitating new and innovative solutions to effectively manage and eventually eradicate the disease.

Impact of the Problem:

  • High Mortality and Morbidity Rates: Malaria is a major cause of death and illness worldwide, particularly in sub-Saharan Africa. It disproportionately affects the most vulnerable populations, including children under five and pregnant women. The disease’s burden extends to overwhelming health systems, increasing hospital admissions, and requiring substantial medical resources.
  • Economic Impact: The disease has a profound impact on the economies of affected countries. It impedes individual productivity and burdens families with healthcare costs, while also deterring tourism and discouraging foreign investment. The economic burden of malaria is estimated to cost billions annually in direct healthcare costs and lost productivity.
  • Resistance to Current Treatments: The emergence of resistance to antimalarial drugs and insecticides used to control mosquito populations is a pressing issue. As vectors and parasites become resistant to current methods, the effectiveness of existing treatments diminishes, leading to an urgent need for new antimalarial agents and vector control strategies.
  • Impact on Indigenous Communities: Many indigenous communities are disproportionately affected by malaria due to their geographic locations, often in rural or remote areas with poor healthcare infrastructure. Moreover, traditional knowledge of herbal medicines and natural remedies used by these communities is underutilized in the global health strategy against malaria.

This project’s goal to accelerate the discovery of new active ingredients for mosquito vector control and antimalarials through the synergy of Artificial Intelligence and traditional knowledge addresses these challenges directly. By harnessing advanced AI techniques to analyze global databases of traditional medicine and collaborating with indigenous communities to ethically integrate their knowledge, the project aims to develop novel, effective solutions for malaria prevention and treatment. 

The project goals

The primary goal of this project is to expedite the discovery of new active ingredients for mosquito vector control and antimalarials by leveraging the synergy between AI and traditional knowledge. This initiative will unfold over a series of planned phases:

  • Data Synthesis and Analysis: The first phase involves utilizing advanced AI techniques to analyze and synthesize data from global traditional medicine databases. This stage is critical for extracting valuable insights from vast amounts of indigenous knowledge and scientific research, serving as the foundational data for developing new antimalarial solutions.
  • Collaboration with Indigenous Communities: In parallel with data analysis, the project will engage directly with indigenous communities. This collaboration aims to ethically integrate traditional knowledge into modern health solutions, ensuring the preservation of cultural heritage and contributing to enhanced global health strategies.
  • Model Development and Testing: Utilizing the insights gained from the initial data synthesis and community collaboration, AI-driven models will be developed to identify and predict the efficacy of potential compounds for malaria treatment and mosquito control. 
  • Blueprint Design and Presentation: The final phase of the project involves designing a blueprint for the developed tool, which will be presented at the United Nations Summit in September. This presentation aims to showcase the project’s innovative approach and potential impact on global health, seeking support and collaboration for further development and deployment.

Thus, this project aims to deliver a groundbreaking system that significantly advances the discovery and development of new malaria treatments and vector control methods. By combining AI with traditional knowledge, this initiative is expected to lead to more effective and culturally respectful health solutions, having a profound impact on malaria prevention and treatment worldwide.

**More details will be shared with the designated team.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities



Eligibility to join an Omdena Top Talent project

Finished at least one AI Innovation Challenge

Received a recommendation from the Omdena Core Team Member/ Project Owner (PO) is a plus



Skill requirements

Good English

Machine Learning Engineer

Experience working with Machine Learning, and/or Data Analysis is a plus.





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