Utilizing Machine Learning & Artificial Intelligence to Understand RNA Structure-Function & Interactions with Small Molecules
Time: 9:15 am
day: Pre-Conference Workshop Day
Details:
As drug discovery remains the focal point of the RNA-targeting drug discovery community, novel approaches are being developed to better identify and understand the features of targetable RNA and small molecules. As the field moves forward, artificial intelligence and machine learning are incorporated into drug discovery. However, questions surrounding their use still remain. Join this workshop to understand how AI is being used to carry out drug discovery, as well as the advantages and disadvantages od using AI and machine learning.
- Understanding the molecules and RNA structures found in cells and how it causes the mechanism of action
- Utilizing digital support to look for data and predicting structural confirmations
- Can these experiments be reproduced on a regular basis?
- Using AI models and computational tools to understand RNA-small molecule interactions and achieving proof-of-concept
- The advantages and disadvantages of using artificial intelligence and machine learning for drug discovery
- How is AI & machine learning changing how we carry out drug discovery in the space?
- What are the benefits of using AI and how has it transformed what is being done?
- Understanding the multi-dimensional chemical space using machine learning
- Where is the data coming from that informs the computers about the multi-dimensional space? How applicable is the data set to the problem that needs to be addressed?
- Using machine learning to select molecules from compound banks and determining which molecules have a functional effect
