César de la Fuente’s lab utilizes Codex and ChatGPT to explore genomic data for potential antimicrobial molecules. The research focuses on analyzing both extant and extinct genomes. The system searches for sequences with characteristics that could be effective against drug-resistant infections. The models are used to identify potential candidates.
ChatGPT is used to refine the search and prioritize sequences. Codex is used to generate sequences based on the refined search criteria. The research team is exploring a wide range of genomic data to identify novel antimicrobial compounds.
This work demonstrates the potential of combining large language models with genomic analysis. The goal is to accelerate the discovery of new drugs to combat the growing threat of antimicrobial resistance. The system’s output is used to guide further experimental validation.
This research highlights the application of AI models in drug discovery. The system’s architecture allows for rapid screening of genomic data. Source: https://openai.com/index/using-codex-chatgpt-to-search-for-new-antimicrobials