Traditionally, bringing a new drug to market takes over a decade and billions of dollars, with a high failure rate in the early stages. Artificial Intelligence is flipping this script by analyzing molecular structures and biological data at speeds human researchers cannot match.
AI contributes to the pipeline by:
- Target Identification: Scanning vast databases of proteins to find the best “lock” for a new medicinal “key.”
- Predicting Toxicity: Using machine learning to forecast side effects long before a drug enters animal or human testing.
- Repurposing Existing Meds: Identifying new uses for already-approved drugs by uncovering hidden biological pathways.