Large Language Models and Their Applications in Drug Discovery and Development: A Primer.

Area of Science:

• Pharmacology
• Translational Medicine
• Artificial Intelligence

Background:

• Large language models (LLMs) are increasingly influential across scientific domains.
• Their potential in specialized fields like clinical pharmacology and translational medicine is significant but requires focused exploration.
• Understanding LLM capabilities is crucial for advancing drug discovery and development.

Purpose of the Study:

• To provide a comprehensive primer on the applications of LLMs in clinical pharmacology and translational medicine.
• To elucidate the fundamental concepts underpinning LLMs relevant to these scientific disciplines.
• To guide researchers on leveraging LLMs for enhanced research and development efforts.

Main Methods:

• Exploration of LLM fundamental concepts.
• Review of potential applications across the drug discovery and development pipeline.
• Identification of practical use cases in medical writing and quantitative analysis.

Main Results:

• LLMs can facilitate target identification and aid preclinical research.
• LLMs assist in clinical trial analysis and quantitative clinical pharmacology workflows.
• LLMs support medical writing tasks, accelerating analytical processes.

Conclusions:

• LLMs present transformative potential for clinical pharmacology and translational medicine.
• Researchers can utilize LLMs to optimize various stages of drug discovery and development.
• A clear understanding of LLMs empowers scientists to enhance their R&D endeavors.