From Prompt to Drug: Toward Pharmaceutical Superintelligence
Abstract
The convergence of generative artificial intelligence (AI) platforms and automated laboratory systems is ushering in a new era of drug discovery, in which a plain-language prompt can initiate a fully autonomous, end-to-end drug development program. This article explores the recent evolution of AI technologies and presents a "prompt-to-drug" pipeline, where AI not only generates novel hypotheses and designs optimized drug candidates but also orchestrates synthesis, validation, and clinical planning in a closed-loop system. By highlighting key breakthroughs, case studies, and the technological infrastructure required for this paradigm shift, we outline a vision for scalable, efficient, and unbiased drug discovery.
Fields of Study & Subjects
Computational Drug Discovery Methods
Machine Learning in Materials Science
Scientific Computing and Data Management
Publication details
- Journal / source
- ACS Central Science
- Publisher
- American Chemical Society (ACS)
- Volume
- 12
- Issue
- 3
- Pages
- 265–279
- Publication date
- 2 February 2026
- Language
- EN