AI for Drug Discovery
Developing AI to assist with drug discovery from plants is increasingly important due to several key factors that enhance pharmaceutical research and development efficiency and effectiveness.
Here are some of the main reasons why AI integration is pivotal in the field of drug discovery, particularly from botanical sources:
▪ Complexity of natural compounds
▪ Speed and efficiency
▪ Cost reduction
▪ Enhanced predictive analytics
▪ Global biodiversity utilisation
▪ Personalised medicine
▪ Integration of multidisciplinary data
The use of AI in drug discovery from plant sources represents a significant leap forward in pharmacology, offering a path to more efficient, cost-effective, and potentially revolutionary medical advances. As AI technology evolves, its role in uncovering new, effective plant-derived medicines will likely become increasingly vital, pushing the boundaries of traditional pharmaceutical research and healthcare possibilities.
Conclusion
We will use AI to explore the therapeutic potential of the vast plant repository at the University of Pretoria, which contains about 11,000 plant samples. This will primarily involve the development of machine learning algorithms to predict which plant compounds are likely to yield beneficial pharmacological properties, thereby demonstrating the practical application and relevance of AI in drug discovery.