Abstract Recent advances in AI-driven drug discovery have led to widespread narratives suggesting that a single model or platform can generate viable therapeutic candidates and, when combined with automated laboratory systems, rapidly progress to clinical development. These narratives often imply that AI-driven design coupled with robotic execution can substantially compress the path to Phase I trials and accelerate the treatment of complex diseases within a few years. Howeve

Intellicite Labs traces its origins back to late 2023, before the current wave of large language model–driven systems had fully taken shape. In November 2023, Dr. Melinda B. Chu developed and documented an early architecture for what would later become known as an “autonomous scientist” system—an integrated, multi-model framework designed to emulate how real scientific discovery occurs across domains. This work was formalized in a USPTO provisional filing and submitted the f