Photo credit: The Future of Eye Care: How AI is Changing Ophthalmology
Introduction
On Wednesday, the 11th of June 2025, Research and Innovation Agenda hosted Dr. Paul Owusu Donkor, a Senior Lecturer at the University of Ghana School of Pharmacy. Dr. Donkor holds a PhD from Tianjin University of Traditional Chinese Medicine and specialises in Pharmacognosy and natural product research. He has previously served as Head of the Department for Pharmacognosy and Herbal Medicine and is currently the Chairman of the Board of Directors for the Pharmacists Credit Union. His research focuses on medicinal plants and their applications, including the treatment of neglected tropical diseases like River Blindness. The interview, hosted by Dr. (Alhaji) Abubakari Sidick Ahmed, put a spotlight on Dr. Donkor’s search for existing drugs that might work against River Blindness in a study dubbed, “Using AI to Find New Treatments for River Blindness: Machine Learning and Molecular Docking for Drug Repurposing Against Onchocerciasis”.
Understanding River Blindness
River Blindness affects approximately one billion people worldwide, primarily in developing countries across Africa, Asia, and the Americas. It is among the category of diseases called neglected tropical diseases (NTDs). River Blindness is quite prevalent in Ghana and according to statistics shared by Dr. Donkor, between 2010 and 2022 alone, there were over 100,000 people with the condition in the country. The disease is caused by the parasitic worm Onchocerca volvulus and is transmitted through blackfly bites, leading to severe itching, skin issues, and, ultimately, blindness. Currently, Ivermectin has been the most reliable drug for the treatment of River Blindness. However, increasing reports of drug resistance and negative side effects, including nephrotoxicity and sometimes hepatic toxicity have necessitated the search for alternative therapies.
The Study: A New Approach to Drug Discovery
Dr. Donkor’s research team is employing a cutting-edge approach that integrates artificial intelligence (AI) with traditional drug discovery methods. Instead of spending years developing new drugs, the team is investigating whether existing medications can be repurposed to treat River Blindness. This innovative strategy aims to dramatically shorten the drug development timeline from between 10 to 15 years to just 3 to 5 years. Dr. Donkor explained that this drug repurposing or repositioning approach combined three technologies:
Machine Learning: Utilising AI algorithms to analyse large datasets of existing drugs to identify patterns that may indicate potential effectiveness against the parasite.
Molecular Docking: This computer simulation technique reveals how potential drugs interact with the parasite’s targets, specifically the Glutamate-Gated Chloride Channels, (GGCC) which are crucial for the parasite’s survival.
Big Data Analysis: The research examines 602 anti-infective drugs, narrowing down candidates based on their chemical properties and potential efficacy against River Blindness.
Current Stage and Future Directions
As of now, the team has identified 14 promising drug candidates, with three leading drugs showing significant potential: Cridanimod, Diminazine, and Vandetanib. These candidates not only exhibit mechanisms similar to ivermectin but also present lower resistance rates, making them viable options for further testing. This further testing would involve two additional stages, having gone past the in-silico stage which utilises advanced computer simulations and AI algorithms to analyse existing drug databases, identifying potential candidates that may effectively target the parasite causing River Blindness. Following this is the in-vitro stage, involving laboratory testing of these candidates in controlled environments to assess their efficacy against the parasite in a test-tube setting. Finally, if these results prove promising, the research will move into the in-vivo stage, where the drug candidates will be tested in live organisms to evaluate their safety and effectiveness in real biological systems.
The next step includes laboratory testing of the identified candidates, with the hope of moving into clinical trials if results prove promising.
Implications of the study
Dr. Donkor emphasised the importance of this research. He stated that with the burden of River Blindness being particularly heavy in rural areas where stagnant waters create ideal breeding grounds for the blackfly vector, the study will help to mitigate the impact of this neglected tropical disease on vulnerable populations.
The implications of this research extend beyond just River Blindness as it sets a precedent for how AI and machine learning can revolutionise drug discovery for neglected diseases, potentially saving millions of lives.
Dr Donkor expressed optimism about the benefits to the entire country, “So the advantage we then have is that our FDA, our Ministry of Health, our Ghana Health Service can then incorporate this easily or seamlessly into our healthcare management regime. And so, the advantage we have now is that in a shorter time we are able to move on or switch into more effective alternatives in managing Onchoceriasis and this is a big deal. Exactly, a very big deal, in fact.”
Challenges
Dr. Donkor however highlighted logistic constraint as a critical challenge, noting that procuring necessary materials and navigating regulatory hurdles can greatly impede progress. He anticipates additional challenges, such as the potential for unexpected setbacks during the research process. He advocates for a need for collaboration through data sharing and cross-talking to overcome these obstacles.
Conclusion
Dr. Donkor and his team’s work exemplifies the innovative spirit of Ghanaian researchers, showcasing how local expertise can address global health challenges. The interview on Research and Innovation Agenda did not only shed light on the urgent need for effective treatments for River Blindness but also highlighted the potential of AI in transforming the future of medicine. Indeed, technology can lead the way in creating a more efficient and effective pathway for discovering life-saving treatments.
Research and Innovation Agenda (RIA) is a collaborative effort between Radio Univers and the Reseach and Innovation Directorate (RID) of the University of Ghana to share ground-breaking findings and innovations of researchers of the University with the public. The interviews have offered opportunity to these researchers to demonstrate how they are contributing to solving societal problems through impactful research.
Source: Barbara Balangtaa (Producer- Research and Innovation Agenda, Radio Univers)